Applications of Big Data Analytics in real life

Today, millions of users click pictures, make videos, send texts, and communicate with each other through various platforms. This results in a huge amount of data that is being produced, used and re-used everyday.

In 2013, the total amount of data was 4.4 zettabytes. This is likely to increase towards 44 zettabytes by 2020 (One zettabyte is equivalent to 44 trillion gigabytes)

All of this ‘Data’ is a precious resource, which can be harnessed and understood by deploying certain techniques and tools. This is the gist of Big Data and Data Analytics. Using Big Data and Data Analytics, many organizations are able to gain insights into the customer mindsets, trending topics, imminent next Big things, etc.,

Let us take a look at how Big Data Applications has influenced various industries and sectors, and also the ways in which they are benefited from the same.


The education industry is required to upkeep and maintain, a significant amount of data regarding faculties, courses, students and results. Requisite analysis of this data can yield insights that enhance the operational efficiency of the educational institutions. This can be put to avail in numerous ways.

Based upon a student’s learning history, customized schemes can be put into place for him/her. This would enhance the student results in entirety. Similarly, the course material too can be reframed based upon what students learn quicker, and the components of the course material that are easier to grasp. As a student’s progress, interests, strengths, and weaknesses are grasped in an improved manner, it helps suggest career paths most lucrative for him.


Healthcare industry generates a significant amount of data and Big Data helps the industry make a prediction for epidemic outbreaks in advance. It may also help postulate preventive measures for such a scenario.

Big Data may help with the prediction of disorders at an early stage, which can act as a preventive measure against any further deterioration, and makes the treatment more effective as well.


Governments of all nations come across a significant amount of data every day, as enabled by sources such as the various databases pertaining to their citizens and geographical surveys.

By putting Big Data Analytics to the best avail, the Governments can come to recognize the areas that are in need of immediate attention. Similarly, challenges such as exploitation of energy resources and unemployment could be dealt with better. Centering down upon tax evaders and recognizing deceit becomes easier as well. Big Data also makes occurrences of food-based infections easier to determine, presume, and work upon.


There are various ways in which Big Data makes transportation more efficient and easier, and the technology withholds a vast potential in the field.

As an example, Big Data can be used to access commuters’ requirements of different routes and can help implement route planning which reduces the waiting times. Similarly, traffic congestion and patterns can be predicted in advance, and accident-prone areas can be identified and worked upon in a suitable manner.

Uber is a brand that puts Big Data Analytics to avail. They generate the data about their vehicles, each trip it makes, the locations and drivers. This can be used for making predictions about the demand and availability of cabs over a certain area.


Data in the banking sectors are huge and enhances each day. With a proper analysis of the same, it is possible to detect fraudulent activities such as misuse of debit or credit cards or money laundering. Big Data Analytics help with risk mitigation and bring business clarity.

As an example, Bank of America has been using SAS AML for over the past 25 years. The software is based upon data Analytics and is intended towards analysing customer data and identifying suspicious transactions.

Weather patterns

Weather satellites and sensors are located across the globe and collect a significant amount of data, which is then used to keep a tab on weather and environmental conditions as well. By use of Big Data Analytics, the data can be used for weather forecast and understanding the patterns of natural disasters in a better way. It can also come across as a resource for studying global warming.

The Governments can put in efforts in advance towards preparing themselves in the event of a crisis. It may even help determine the metrics related to the availability of drinking water across geographies.

Media and entertainment

People own and have access to digital gadgets that they use to stream, view, and download videos and entertainment based applications. This significant amount of data generated can be harnessed and some of the prime advantages that can be derived from putting this data to the best possible avail involve making a prediction of audience taste and preferences in advance. This can be further used towards making sure that scheduling of media streams is optimized or on-demand.

The data can also be used to study customer reviews and figuring out the factors that don’t delight them. Targeting advertisements over media become easier as well.

As an example, Spotify is a provider of on-demand music and uses Big Data Analytics to analyse data collected from the users across the globe. The data is then used to give some fine recommendations for a user to choose from. This is based upon the user’s browsing history and the most preferred videos seen by users of the same geographical region or the same demographics.

In terms of Big Data, it is important that the organizations are able to use the data collected to their best advantage in order to gain a competitive advantage. Merely a collection of the data is not enough.

In order to ensure efficient use of Big Data, Big Data solutions make the analysis easier. Application of Big Data expands further still to fields such as aerospace, agriculture, sports and athletics, retail and e-commerce.

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Data Analytics and Big Data – An Overview

2019 has seen an advent of technologies and practices that were not of great importance or significance in the recent past. Talking on these lines, it is common practice for a large number of organizations to invest in Big Data Analytics in order to improve their operational efficiency. These analytics make way for improving revenue streams and provides the business a competitive edge over their rivals.

In order to pick the right Big Data Analytics applications best suited for its requirements, a business has many options at its disposal. A very commonly used choice among them is Descriptive Analytics which is primarily a way to visualize the historical data by means of querying. A more complex alternative to descriptive analytics is Predictive and Prescriptive modeling which is oriented towards the future. This essentially means to make decisions by anticipating business opportunities in advance. It is intended to make way for higher profits in targeted marketing campaigns and helps in customer retention. It can also help prevent eventualities such as equipment failure and such

Predictive analytics reveal patterns that indicate future situations based upon historical data sets while Prescriptive analytics work along with predictive analytics and stipulates the actions that will be most advantageous as per the scenarios predicted.

Using Big Data Analytics tools, analysis of massive amounts of data derived from varied source is made simpler and can be used for predictive and prescriptive analytics. These tools are essentially software products that render support for applications for predictive and prescriptive analytics, which run on Big Data computing platforms. They can be used for processing systems that run in parallel on servers, distributed storage which is scalable and technologies like NoSQL databases and Hadoop. They enable users to analyze large amounts of data, sometimes on a real-time window.

Alternately, Big Data analytical tools offer a framework for techniques of data mining. These techniques analyze data and bring certain patterns to fore. Correspondingly, a few analytical models can be created which may be used as a response to the identified patterns. As the models become a part of operations, business efficiency is enhanced.

As an example; A significant amount of shipping delivery data which pertains to traffic, weather, and vendor performance in the past can help make a model which enables selection of best-suited shipping contractors in a certain place. This helps minimize chances of delayed delivery or the goods coming across damage along the way.

Big Data Analytics tools can be used across different kinds of data types. This can include structured data which is stored within fields that are consistent and transactional data which is stored within relational databases. These tools can also use semi-structured data like mobile application web server log files or unstructured data like documents, text files, text messages, emails and posts on social media.

Talking about Big Data tools; some of the functionalities that must be included before a business makes the right choice are:

  • Analyst algorithms and models used should be current.
  • The tools must easily run over Hadoop, which is a Big Data platform.  Similarly, they must operate over high-performance analytics systems.
  • The tools must be adaptable and versatile. This would enable them to avail structured and unstructured data alike from many sources.
  • The tools should be scalable and must be in a position to analyze even more data as it is fed within the system.
  • Integration with data visualization and presentation tools must be simple for the analyst to accomplish.
  • The tools should enable easy integration with other technologies.

The tools must also have methods and algorithms necessary for supporting a characteristic suite of data mining techniques. This must include:

  • Methodologies for clustering and segmentation, which divides a huge selection of entities into smaller groups, based on characteristics or similarities which may not be initially anticipated. This can help create resources for targeted marketing.
  • The tools must also ease classification, or division of data into classes that are predefined. These attributes may either be pre-selected or defined based upon the results of the clustering model.
  • Regression analysis brings to fore the relationship between dependent variables, and a single or multiple independent variables. They help determine the ways in which the value of the dependent variable is dynamic, with respect to the independent variables. As an example, a prediction of the future value of a property can be made, using information such as its location, average temperature in summers, square footage and mean incomes.
  • Item set mining and the association may be used for the purpose of finding relevant relationships among variables as per statistics whenanalyzinga large data set. The relationships may be used by call center agents to offer schemes based upon caller’s segmentation, or upon the time period for which he has been associated with the organization, or on the nature of the complaint.
  • Similarity and correlation – The algorithms that score similar can be used to determine similarity among entities in a cluster.

Additionally, vendors also provide some algorithms which support each of these methods. Let us now take a short overview of Advanced Analytics Tools market.

Evolution of tools for advanced analytics markets has come a long way. Capability and ease of use of the tools are variable.

A few of the tools offered by well-placed vendors such as Oracle, IBM, and SAS have a history associated with them. Similarly, tools provided by Microsoft, Dell and Sap are relatively recent. Apart from them, a few of the top companies who offer products for Big Data Analytics are Alpine Data Labs, Predixion and Angoss.

Tarams has a strong Data Engineering and Analytics practice specializing in building enterprise data warehouses and data lakes starting from the ground up, both On-premise and Cloud.

Our engineers have extensive experience in building comprehensive analytics solution using various ETL & BI tools (like Pentaho, Tableau, Oracle), big data platforms and frameworks (like Kafka, Spark, HDFS), cloud services (like Snowflake, Redshift), web & mobile analytics (like Amplitude, Pyze) and business system integrations (like Salesforce, Zendesk).

Data Analytics Team
Tarams Software Technologies Pvt Ltd.

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Trapped in Cloud Migration Dilemma? 15 Factors to Consider to Take Wise Decision!

2017 was a roller coaster ride for enterprises in technology space. Recent IoT trends were the talk of the town and contributed to numerous transformations across industries. Consumer products such as connected devices and wearables were the bellwethers of these transformations.

The IoT industry size was valued at USD 800 billion in 2014. Technological proliferation and exponential increase in venture investments are expected to boost the global market over the next decade. Significant penetrations of internet and advancement in electronic industry have further propelled the growth of the Internet of Things (IoT) industry and gives a strong visibility to the compelling IoT technology trends in 2018.

The IoT market is expected to touch USD 6 trillion by 2021, at a Compound Annual Growth Rate (CAGR) of 26.9%. With this growth, market will witness new business models & use cases along with immense changes in improved customer experience, productivity & workflow.

Now that, we know IoT will be one of the primary crusaders to drive digital transformation in 2018 and beyond, let’s have a quick sneak peek on the top IoT trends in 2018.

In 2018, enterprises will be looking at the ‘cloud’ not just as a tool, but they will be exploring better ways to use it to accomplish their technology goals

Penetration of cloud technology into enterprise IT had brought remarkable transformations to the business realm in the past , and today cloud technology has opened new ways to maximize big data usage to optimize business revenue cycle management.

Cloud technologycontinues to skyrocket with advanced usage of cloud-based solutions for Analytics, Mobility with streamlined collaboration, IoT, etc., due to its cost-effectiveness and high-speed connectivity. As per IDC, 50% of all IT spending in 2018 will be cloud-based and Deloitte predicts that spending on IT-as-a-Service for data centres, software and services will reach $547 Billion by the end of 2018.

We have compiled a list of cloud trends that businesses need to be prepared for in the coming year.

The Rise of Saas, Paas, and IaaS market

Software as a Service (SaaS), where software applications are centrally hosted on cloud – meant to be licensed on a subscription basis, will rise to 18% CAGR by 2020 as per a survey.

Platform as a Service (PaaS) will be the most rapidly growing service that enables companies to develop, host and manage apps over a common platform that will grow to 52% adoption in 2020, as quoted by KPMG.

Infrastructure as a Service (IaaS) where virtualized computer resources are provided online, will grow with a market size of $17.5 Billion in 2018, as per a report by Statista.

2018 will be a golden year for cloud adoption where collaboration and social media democratization will become seamless and industries will witness exponential growth in adoption.

Cloud to Cloud Connectivity

The market is set to be flocked with multiple providers who are ready to share APIs to multiple cloud solutions and cross-functional applications. Enterprises should be looking forward to not limiting themselves to a single cloud service provider.

With the increase of consumer data inflow from disparate sources, consumers also expect faster data connection from network providers. 2018 will be the year when companies will show strong anticipation to move on to 5G networks.

Faster internet connectivity will compel users to demand fast-loading and high-responsive services and apps. Savvy enterprises will enforce highly responsive SaaS and PaaS in their application portfolio so as to ensure faster delivery that would eventually lead to higher traffic, new revenue generating models and value added service.

And all this becomes possible with embracing cloud-based platforms for products and services that allow businesses to gain agility through virtualization.

Pricing War leads to Vivid Cloud Usage

2018 will witness a growth in the volume of cloud service providers; while on the other hand, the market will display a drop in demand. However, it’s the law of nature- with the increase in supply, demand always goes down! Thus, with increased supply, the market will encounter a rigorous price war. Moreover, numerous providers will offer cloud space for free just to gain valuable consumer data.

Crowd Sourced Platform

Despite using insecure, costly and slow cloud space, users will start using crowdsourced platform to keep the cost low and avail optimum cloud benefits.

Sharing strangers’ and friends’ storage will be a common practice and people will start moving out of applications like DropBox and Google Drive. Similarly, businesses will also look ahead utilize crowdsourced platforms to maintain and build large-scale solutions.

Cloud will be the key to cost containment

Cost containment is a technique to cut down costs to essential expenses to limit within financial budgets. The growth of cloud adoption across the industry will be the main idea for long-term cost-cutting IT strategy by lowering the infrastructure expenses and improving ROI. It is predicted to be a norm in 2018.

Cloud Cost War will be at Pinnacle

Giants like Amazon and Google will be leading the war that actually will have substantial collateral damage to the mid-sized and small-scale service providers. AWS has already announced its lowered prices in the 2017 and Google has introduced its Committed Use Discounts (CUD) which gives the flexibility to the buyer to avail highly reasonable price for a committed use contract.

Cloud to On-Premise Connectivity

Businesses will move on to applications hosted on an on-premise based server while showing affinity towards shifting a chunk of their application portfolio on to the cloud to enable smooth customization and here are the reasons why:

  1. Although, on-premise deployment will ensure network security when it comes to data flow, numerous contemporary security solutions work best on the cloud.
  2. Over the years, the enterprise data has expanded at a multiplier level and transferring them on to the cloud remains a tough ordeal for most of the enterprises.
  3. Complete migration of the entire enterprise data takes a lot of time and does not display any short-term profitability.

Cloud Security Threats

Security concerns will become a major roadblock for numerous businesses to move their data onto a cloud. As per a report by Identity Theft Resource Center (ITRC), USA, 2017 saw 29% rise in security attacks as compared to 2016.

Today, user data is much more vulnerable than ever before, thus even Google brought in its 2-step verification process. As per IDC, global security revenue will grow up to $101.6 Billion in 2020. Another report reveals that security spending will touch $93 Billion in 2018. This will be the year when cybersecurity companies will be on their toes to engineer advance cloud security solutions.

It is predicted that, IT, security and cloud teams will associate to develop new working models to redefine cloud security services to reduce vulnerabilities. By bringing automation, speed, and integration with cloud security services, redefinition on how to approach cloud security for success will be implemented.

Cloud Security Threats

Cloud-based Containerization

Containerization in cloud computing will be implemented by most of the vendors. The phenomena allow the admins to create safe containers on the devices that enable smooth, safe and secure installation and deployment of the application.

Furthermore, cloud solution providers will offer independent container management system that would differentiate their platforms from another cloud container system.

It could reduce the vulnerability of data loss or threat and will be a popular trend in 2018 and beyond.

Cloud and the IoT

IoT as a technology completely depends on the cloud. IoT devices like electronic sensors, home appliances, cars, wearables, etc. communicate and store hefty information. With IoT devices becoming ubiquitous, cloud adoption will be on the rise.

Serverless will gain grounds

The adoption of serverless cloud architecture will enable CIOs to run applications without the burden of on-premise operating servers. Moreover, developers find it convenient to access and extend cloud services when it comes to addressing multiple use cases and application issues.

Serverless cloud architecture also needs less time and effort and simplifies software updates.

Edge computing: the next multibillion-dollar technology

Edge computing will leave no stones unturned, when it comes to operating close to IoT based devices and machinery such as automobiles, home appliances, turbines, industrial controllers, etc. and optimizing the cloud usage. Edge computing will be required to run the real-time services as it operates close to the sources and streamlines the inflow of traffic from these sources. Edge computing is an additional middle layer between the devices and the cloud that keeps the devices away from the centralized cloud computing.

Thus, the public cloud service providers will move towards IoT strategies that will include edge computing as an integral part.

Our Final Verdict

As far as technology advancement is concerned, possibilities are limitless. With evolving IT infrastructure, cloud adoption will be really fast. CIOs will be keen to consider the most advanced offering from the cloud space. However, security concerns will still haunt the CXOs and multiple enterprises will remain deprived of great opportunities.

The market will observe an affinity of enterprises towards hybrid cloud model. A handful of companies may also consider private cloud solution as an option.

At Tarams, we engineer solutions for intuitive visualization of cloud data keeping security and performance as the crux of our cloud-based solutions. Our cloud architects help you to efficiently mine data to develop better analytics, data mining best practices and improve decision making.

We forecast a strong proliferation of cloud technology in the upcoming years and recommend organizations to actively participate in its development, adoption and security.

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9 Emerging IoT Trends that will Disrupt Business in 2018 and Beyond

2017 was a roller coaster ride for enterprises in technology space. Recent IoT trends were the talk of the town and contributed to numerous transformations across industries. Consumer products such as connected devices and wearables were the bellwethers of these transformations.

The IoT industry size was valued at USD 800 billion in 2014. Technological proliferation and exponential increase in venture investments are expected to boost the global market over the next decade. Significant penetrations of internet and advancement in electronic industry have further propelled the growth of the Internet of Things (IoT) industry and gives a strong visibility to the compelling IoT technology trends in 2018.

The IoT market is expected to touch USD 6 trillion by 2021, at a Compound Annual Growth Rate (CAGR) of 26.9%. With this growth, market will witness new business models & use cases along with immense changes in improved customer experience, productivity & workflow.

Now that, we know IoT will be one of the primary crusaders to drive digital transformation in 2018 and beyond, let’s have a quick sneak peek on the top IoT trends in 2018.

Trend# 1

Fragmentation in IoT: Big Rock Challenge

While the venture capital is booting the IoT space, there has been a significant influx of network technologies & solutions into the market, developing a highly fragmented scenario within the IoT landscape.

First, well-known wireless networking technologies such as 5G, WiFi, Bluetooth, Zigbee are currently available to support IoT based solutions. Such vivid internet technologies connecting different groups creates interoperability complexity across the various networks.

Second, attaining IoT-enabled automation and predictive analysis to design industry-specific applications, needs a suite of processes to derive & analyze data from disparate devices. Furthermore, the connected equipment with different form factors and operating systems magnifies the complexity.

Thus, the major roadblock in such a fragmented ecosystem that interconnects different technologies will be the interoperability and integration of these processes to achieve the desired end result.

Trend# 2

Window of Vulnerability will be Wide Open

Cybersecurity will be a hot issue in 2018. Fragmentation will lead to extreme integration and interoperability complexities. This threat will not only remain limited to network security, but it will be a major challenge in managing and controlling connected assets.

Moreover, securing all the assets in an ecosystem without any standard industry regulation will be a big challenge.

Finding a solution that can secure all data sources and keep the data safe from all the vulnerabilities will be main goal of the year and one of the hottest IoT Industry Trends in 2018.

Trend# 3

Edge Networking will be less of a Trend and More of a Necessity

An exponential rise in data glut via IoT results in enterprises needing to find cost-effective ways to monetize consumer data.

So, Edge Computing will leave no stones unturned when it comes to operating close to IoT based equipment and sensors with different form factor and OS such as wearable, automobiles, home appliances, turbines, industrial controllers, etc. and optimizing the cloud usage. Edge computing will be required to run the real-time services as it operates close to the sources and streamlines the inflow of traffic from these sources.

Edge computing will minimize a big chunk of complexity when it comes to the cloud handling, managing data from disparate sources and delivering real-time services.It will be one of the most required and in-demand IoT industry trend that will that will take the entire industry by storm.

Trend# 4

Enterprise Mobility: de Facto IoT Companion

The current trend of mobile platforms getting ubiquitous in enterprises, will result in enterprise mobility playing a crucial role in IoT device management.

Today’s mobility landscape is all about collaborating workforce with BYOD model but with increased addition of IoT based sensors and wearable technologies into the workflow. It is quite evident that IoT and enterprise mobility- as a team, will play a serious game that will matter to the business goals.

As known, mobility and IoT in enterprises, are still in their infancy and their mix will continually evolve. The next mobility projects will get developed with cutting-edge technology in compliance with the business that is built around deriving value from IoT based devices.

The first movers have already begun to refine while the late-comers will directly jump into the blend. IoT industry trends in 2018 will witness a strong convergence between IoT and enterprise mobility.

Trend# 5

The Year of Bells, Dings & Whistles

For retailers, current IoT trends will play a crucial role in improving customer engagement and salesin 2018, 2019 and beyond. Current year will be the year when customers will hear more alerts about offers, incentives and other news regarding office, home & shopping.

In-store beacons will flourish and help retailers to identify a nearby mobile app user and approach with a personalized message. Location-based IoT beacons, sensors and analytics solution will drive the retail space by empowering marketers to send direct personalized messages to customer’s phone, wearable or adaptive in-store digital signage display.

Plus, IoT will tell where customers are spending time inside the store, giving marketers valuable data about customer behaviour and preferences.

Industry experts say that about 79% of retailers will start to use the IoT technology to transform their business in better way that is going to one of the productive IoT industry trend that is going to stay forever.

Trend# 6

Data Deluge Ahead: the Rise of Machine Learning & Advanced Analytics

Just as the abundance of data will push enterprises to the edge computing, it will also push them to machine learning. Machine learning and AI will be the leading technologies to manage the data flowing from IoT devices.

The year will also witness a steady growth in advance analytics solutions to provide a real-time streaming of data from IoT devices. Multiple analytics solution providers will be seen making noise in the arena.

Undoubtedly, the data deluge will give birth to numerous new entrants in machine & IoT analytics space to churn and manage valuable data insights.

Trend# 7

Blockchain and IoT to Dominate Headlines in 2018

The IoT devices, as they increase in abundance, lack standard authentication protocols to secure enterprise data. The probability of intruders penetrating through the vast array of IoT devices into the infrastructure is way higher than ever before. Hence, for widespread adoption of IoT, it is crucial that the industry should look at establishing standardized trust & authentication across all aspects of its ecosystem.

This is where the distributed architecture of blockchain proves to be the lifesaver to tackle trust and security challenge.

The distributed ledger in Blockchain empower the IoT devices to maintain standard identification, authentication, seamless secure data transfer and prevent duplication with any other malicious data.

The operation costs of IoT can be cut down through blockchain since there is no intermediary. The convergence of blockchain and IoT will improve customer experience, simplify workflow, cater to limitless opportunities.

Trend# 8

IT and OT will Walk Together

Operational technology (OT) and Information technology (IT) are conventionally separate organizational units. But, this trend is likely to change in 2018. The extreme inception of IoT into shop floor has compelled OT and IT teams to work closely to deploy IIoT solutions.

Today, analytical tools are majorly used by end users such as plant operators and field workers. Thus, operational decisions can be derived real time to optimize future performance.

IoT solutions will be deployed and driven by business operational teams, more than IT teams. Meanwhile, the OT teams will take the IIOT charge in 2018 and will be one of the greatest IoT trends.

Trend# 9

Investors to Break the Bank

The market is going to see a lot of money in the IoT space. The past has shown eye-popping investments and 2018 will show a relative trajectory. And as said before by 2021 the business spending in IoT will touch $6 Trillion.

Enterprises will continue to invest in IoT hardware, services, software, and connectivity and its going persist as an evergreenIoT trends. Almost every industry will be benefited from its rapid growth.

The biggest slice of funding until 2021 will go into hardware making especially sensors and modules but is also predicted to be outstripped by the fast-growing services category.

IoT’s indisputable impact will allure more venture capitalists towards highly innovative projects. They will continue to break the banks with the promise of IoT by underlining its caliber to improve customer experience and revenue in almost every industry.

Tarams Final Verdict

As a technology consulting and product engineering firm we strongly believe that these 9 trends will play a game-changing role in 2018. However, we also expect new trends to unfold that aren’t on the horizon yet.

We also believe that 2018 won’t be a silver bullet year for IoT but will be a year of preparation for building a widespread and robust foundation for the technology in next five years.

Readers, if you have thoughts on these or if you think that we have missed on any other trends that you believe will propel IoT, please comment below, we would enjoy hearing from you.

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How Mobile APPs Play a Game-changing Role in Education Industry

Smartphones are getting ubiquitous and there is a surge of Educational Applications for Android, iOS, and Windows Devices. These Apps focus on student academic learning needs while utilizing smart gizmos like tablets and smartphones for classroom learning and school activities. Students are finding this trend helpful and undoubtedly are drawn towards using a smart gadget for everything. On the other hand, the educational apps can be the perfect way to motivate students and help them focus on quality learning.

According to a Pearson Student Mobile Device Report, the use of tablets made students perform better in their academics and 79% of the polled students also agree that tablets make learning more fun. Access to information is crucial and thanks to these apps, which are integrated on their tablets and smartphones, it is easily available.

These mobile applications have brought tremendous changes in the education industry, as most of the EdTechs, institutions, and educators are adopting mobility as their primary Digital Transformation strategy. Let us have a quick tour to how Mobility Technology can help reshape the Education Industry.


Smartphones are our constant companions today. We are all connected through various apps that have reduced the distances of our physical world tremendously. Students too are hooked onto smartphones constantly, whether to chat, play games, or watch a video on the move.

Maneuvering this addiction towards a healthy habit, educational apps are on the rise. They do not limit the classroom to walls and they move with you wherever you choose to go. This freedom of portability is a major advantage in the learning process and many students are reaping the benefits of this mode of learning.

Round the Clock Availability

Educational Apps have another glaring advantage over traditional teaching establishments. Unlike institutes & schools, the apps are active round the clock. Even when limiting ourselves to a time-bound learning, apps help us with relaxed & performance-based learning.

Educational Apps have another glaring advantage over traditional teaching establishments. Unlike institutes & schools, the apps are active round the clock. Even when limiting ourselves to a time-bound learning, apps help us with relaxed & performance-based learning.

Time-bound learning is not impactful, as students get distracted easily and are unable to focus consistently for long hours. Thus, educational apps are the best for this issue, as they are available 24/7, and the students can learn as per their convenience.

Interactive Learning

The gadgets of today, with the Educational Apps and other features, are fast becoming a staple feature in every student’s life. Reading reference books and visiting the library are slowly diminishing in importance. These gadgets and helping students learn in an efficient manner. Unlike traditional teaching techniques and methodologies, Interaction with the apps is designed to suit students of all skill levels and cater to a variety of teaching methods, such as webinars, video tutorials, and even educational games.

This interaction helps students fight monotony and urge them to visualize what they learn.

Effectively Utilizing Leisure

Learning on educational apps, is one of the smartest choices for capitalizing leisure productively. The student’s leisure time can be used to learn something new with the help of entertaining tools, like games and puzzles.

One need not feel the burden of sitting through classrooms/classes to learn, when they can use the leisure time in an efficient and constructive way.

Get Individualized Learning

A teacher plays a remarkable role in building a student’s career, however the teacher can’t give individualized attention to every student. A teacher can typically address 10-20 students effectively in a session. And it is a tough ordeal to ensure that each and every student is engaged in the session.

In an educational app, the student gets all the focus they need. The time they engage with the app is all their own.

Track Performance

Tracking the performance or progress of a student, is essential for the students and the concerned educators. Having a legitimate plan and tracking methodology will only benefit the student by indicating the next steps in the learning process.

The inbuilt analytics show the details of the learning hours, the topics covered, the status of the current topic, etc., This detailed analytics at such a granular level is essential for proper guidance and the education apps are leading by example here.

Instant Personalized Updates

The Educational app is designed to send personalized messages, updates, etc., based on the student’s choices. It can also update on upcoming campus events, customized lessons, pending lessons, etc.

Online Study Material

Educational Apps on Mobile/Tablets offers students the opportunity to access thousands of reference and educational material online. This is possible owing to the digitalisation effort by numerous institutes and organizations.

This is a welcome change to many students who do not have access to good quality libraries or the economic freedom to own expensive books and study materials. Physical storage too is diminished and the geographic location of any student is immaterial

Mobility in Education through the advent of educational applications, has more benefits to offer than those that have been listed above. A quiet revolution is in the making, with students and educators alike, gradually drifting towards an industry that is foraying into a paperless and well networked sector. Today, the world of education is more than a passive activity; educational apps are making phenomenally active improvements and thrives to change the face of education sector.

Undoubtedly, educational apps solve critical problems in the education management systems across the globe but many clients, educational institutions and concerned students have a common issue despite owning cutting-edge educational apps.

Considering the capability of a connected smartphone or a tablet, handing students such powerful unmonitored, unmanaged and unprotected devices is a major concern for EdTechs and Institutions. Students were found to be indulged more in tampering educational app settings, playing games, using social media apps, online stores which are potential distractions from the intended learning.

Such scenarios result in problems due to misuse of these devices. Efficient use of educational apps, must ensure and avoid the download of malware and illegal or inappropriate content on their devices. Such misuse of technology is a concern and EdTechs and institutes alike must address the issue

This is where the actual potential of mobility can be harnessed.

An obvious solution to avoid distractions and ensure focused learning is by restricting students to only prescribed learning applications and content. This can be done with advanced mobility solutions. It helps the learners to remain focused by:

Blacklisting irrelevant websites and apps

Blacklisting includes prohibiting students from all unwanted applications and URLs such as games, social networking sites and more. This feature prevents misuse of study time for non-productive purposes. It restricts the students to tamper with the device settings and secures the preconfigured settings required to run the educational apps smoothly.

Network and Geo-Fencing

Through network fencing, schools can apply policies to the student’s devices when they enter the school’s Wi-Fi network. The policies could comprise of allowing whitelisted apps to open in the device. Geo-fencing features allow schools and institutions to monitor the student device and prevent unnecessary use of data and alert the admin when a device crosses the school boundary without authorization.

Remote Access to the device

This mobility feature allows the EdTech client or Institute to remotely control and access student’s device to update additional device information, file sharing, message broadcasting or troubleshooting for any error.

Mobility solutions incorporate robust features to make the student’s handheld safer for academic learning and help the schools and institutions to get the most out of their pedagogy.

If you are an EdTech, an institute, a parent or an educator, it’s not only important to have a robust educational app that caters to an innovative learning experience but to create a platform that meant for dedicated and prescribed learning, this is where you unveil the real success in the learning industry.

At Tarams, we leverage our big data with deep analytics capabilities to develop interactive educational mobility solutions. With proficiency in developing custom educational mobile app solutions, we deliver cutting-edge learning experience to the student that creates a brand identity in your target market.

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Augmented Reality in Education – The next BIG thing?

Hollywood pioneered the use of Augmented Reality (AR) way before it gained popularity in the Digital front. From Sci-Fi fantasies to Dinosaurs, everything was given a fresh breath of life thanks to the advancements in AR. Over time the gaming industry sniffed an opportunity and their advent into AR, gained tremendous interest across most Tech Industries. Companies clamoured over one another and App developers went into a frenzy designing and developing AR aspects towards delivering a whole new user-experience level.

Mobility is a classic example where AR is trying hard to augment our lives for the better

Undoubtedly Augmented Reality is the next wave in the digital world and it has been gaining momentum over the last two decades. Its emergence has been inspiring and every industry today is busy exploring their advantages in AR. The effect of AR in our lives will only increase and every industry will incorporate it within their environs to touch new heights of success.

AR in Education

The Marketing and Entertainment industries were the forebearer to drive the revolution in bringing AR to our homes. Having said that, the Education Industry will surely follow suit to harvest the plethora of advantages AR has to offer. The global landscape of the Education Industry Sector is braced for the inevitable change that is waiting to happen owing to AR’s surging popularity. According to statistics, AR adoption curve for education is on the rise and expected to touch $8 Billion in market size by 2021.

AR as a technology is constantly disrupting the learning methodologies and has made it more engaging and transformational. Today, 71% of the U.S. population in the age group of 16 – 24 years use smartphones and most (if not all) of them are using them to connect on social media, gaming, shopping and other virtual activities. That is a huge population segment waiting to be converted to a customer base.

The overwhelming growth potential of AR in education is quite evident. Digital and Lively information about any topic makes complex information easier to understand. This in turn decreases your learning curve and improves your productivity.

Let us explore how AR can empower educators and learners.

Showcasing the Impossible: realizing the “Aha” moment

Imagine a live volcano or the surface of the moon or even a frazzled Tyrannosaurus Rex right in front of you, in YOUR CLASSROOM! This incredible experience is possible today with the advent of AR

The greatest aspect of this technology is that you can give today’s students an “aha” moment that earlier was not possible by mere explanations and talking. There are plenty of examples of AR content that fulfil this criterion. Have a look at the AR apps in the following video to understand how learning has been made more interactive.

Expeditions AR - Bringing the world into the classroom

Taking a step back: Why AR?

We’ve established that AR is hot right now and it is being touted for tremendous growth and utilization across industries. However, taking a step back; is it necessary? Is it really helping people, in this case; students? Why can a student not understand and experience the topics through regular technology in their current mobility device? After all, our current mobility devices like smart mobile phones and tablets are highly capable and efficient in scaling models, basic 360° rotations and manipulations.

The answer is Perspective and Interaction.

A situation or topic or object can be viewed in multiple perspectives and having the power to physically view ALL the sides is a great advantage. Humans are interactive creatures and it has always been a proven method of learning, be it toddlers or adults.

Well-designed augmented reality models will empower the learners to view models, similar to their natural settings. Enhanced perspective with closer sensitization results in a better learning curve. This allows students to have an interactive and practical based learning with AR models they can examine the models with more precision and accuracy.

Augmented Reality Education Solar System on CARpet

Boost Engagement Levels

Students have different learning curves. Some learn or understand a topic far quicker than the others and some are more relaxed in their approach to grasp the essence of a topic.

Interactive and Active Engagement is the need of the hour to boost the learning curves and AR has come a long way in achieving that. Augmented reality is rapidly penetrating student’s lives and the convergence of AR with the learning landscape scenarios results in learners engaging with content that is highly relevant to their pedagogy and in line with how they use the digital media content.

For Example: AR developers have made learning chemistry more interactive and fun with a holographic periodic table.

AR is unique, where students can perceive tests and exercises as part of the story and they can learn and understand better. It allows students to learn visually which is immensely interactive and emotionally engaging.

AR developers talk about creating “lively” content in AR and it is possible to bring “learning” to life, empowering students to engage with virtual content which has a great deal of freedom from mere text, images or video content.

Recently, a start-up is developing an advanced learning platform that allows you to visualize the human body holographic & 3D format as shown below.

Stimulate the Senses

Well-planned AR platforms will not be static with just a 3d model, but rather enriched with touch controls and 3D sound effects which has a multi-sensory impact on the learning of a student. Institutes can bring animals into the classroom which are lifelike and make real sounds. Moreover, the narrative and touchscreen controls can easily control the screen information overlays.

Curiscope Virtuali-Tee: Bring Learning to Life with this Augmented Reality T-Shirt

Cost Effectiveness

Physical 3D Models and Shapes, being currently used in many Schools and Institutions come with a heavy price tag. They are bulky and also involve logistics expenses. Moreover they also come with high maintenance criterion.

In this context AR can be a lifesaver! It helps you deploy 3D shapes using the AR platform. We are not promoting the replacement of the legacy physical models but an upgradation with the inclusion of AR models with meagre investment can open new doors for great pedagogies.

Furthermore, in subjects like history, it becomes near impossible to bring real models to class. This is where AR can help in letting your students have strong sensitization to the real world lifelike models and monuments.

Final Verdict

It is not a fallacy that learners who are more motivated and engaged always grasp a subject faster and learn better.Their focus on the learning process is improved as educators grab the attention of their students and keeps them engaged and glued to the learning content using AR.

AR in education possess a huge upside for all learners and educators. Furthermore, students get platforms to visualize complex concepts of various topics and opportunities to gain practical skills by interacting and manipulating content.

If you are an EdTech or an educational institute, then it’s high time you jump on the bandwagon to embrace AR and create transformational content that not only caters to a differentiated learning experience but can radically improve your learner retention and and help you get the most out of your learning and development investments.

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Evolution In Machines – What Next?


Humankind as we know and experience today, has evolved over millennia from our primitive biological ancestors to our current biological selves. This evolution has gone through many stages and phases that has lead to our dominance and success on this planet.

The evolution and advancement of Cognition and Language played a significant role in establishing Humans as the dominant species while having a profound effect on the Humankind’s Evolutionary Journey.

Cognition or the ability to learn and gain knowledge through a ‘thought process’ helped humans thrive better and more efficiently than other species. This resulted in the early discovery, invention, and development of societies, tools, agriculture and other advancements. This cognitive ability enabled us to develop and communicate with a common language that irreversibly gave us a boost towards becoming the dominant species on earth.

Language, or a systematic approach to clearly communicate within a species – has shaped to what we use now, over thousands of years. Different communities and societies developed and shaped different languages that we have come to know today. Despite the differences, it is evident that ‘language’ was crucial to the development of humans as a social.

A combination of language and cognition enabled early humans to rally forces, build societies, understand obstacles, explore their surroundings while analyzing them, etc., The ability to instruct and impart played a crucial role in the development of civilizations and societies. This development can be broken down into three steps

  • The ability to express one’s thoughts and ideas
  • The ability to understand the expressed thoughts and ideas
  • The ability to function, based on the said thoughts and ideas

These enabled early humans to gather masses and work efficiently and productively. Tasks that were near impossible to be done by a small group or a single human could now be handled well; thanks to the amassment of more humans. Many modes of communications were used to achieve the desired results – primitive signs, early languages, non-verbal pictorial representations (early writing systems), etc., However, amongst these modes, the one that stood the test of time to emerge the forerunner was ‘language’ in the form of Speech. This clearly has been at the helm of our evolution and steered us to our current position on earth.

This evolution has also interfered with and altered the evolutionary paths of all the elements that surround us or make up our planet; flora, fauna, rivers, mountains, language, writing, science, human inventions, etc. Human inventions and discoveries, especially have evolved with a similar pace as that of our; tools, agriculture, cooking, trade, engines, automobiles, computers, space travel and everything in between these and around these. At every stage of this human evolution and endeavour there has been one stand out invention or discovery that propelled us into the future; faster and further; Stone tools to iron tools in the early stages, agriculture and cooking when we started societies, weapons, and trade when we started building civilizations, engines, and mechanics for our industrial revolutions, electronics and computer science for our modern age. etc.

Amongst the discoveries and inventions, ‘Electronics and Computer Science’ have had a far-reaching effect on our population and have impacted our day to day life drastically. Over the years they have become very personal to us and they have proliferated our lives and environments drastically. From television sets, radios and telephones to personal computers, mobile phones, and satellites, we are surrounded by electronics and computer science every day. They have about them a uniqueness; we communicate with them and to them in ways that were not done before with other inventions.

Today we see ‘machine learning’ and ‘artificial intelligence’ enabling us to add cognition and push them towards a cognitive revolution. We are enabling machines to learn from experiences and make judgments on their own; making them more independent and more useful to us. We already have machines that can suggest the movies we like, drive cars, detect cancer early, etc, and this is possible due to the idea of cognition that we have built into those systems using machine learning and artificial intelligence.

We have made these modern machines different from other earlier machines because of their ability “think” and the way in which we are able to “communicate” with them. We do not use levers or knobs, reminiscent of early machinery; instead, we type out messages or instructions in a language familiar to us. This mode of communication has evolved over time; from punching to typing to clicking to voice.

Machines understanding human language through our speech is the next big step in the evolution of electronics and computer science. The combination of cognition and voice recognition in devices have ensured that we can communicate; not just instruct, and in a language that we use and understand best.

Most early machinery and devices were designed and developed to ease the user in its usage. Until recently, using advanced personal devices required us to be in physical contact with the device, know basic operations and understand its basic layout and structure. This made devices unreachable or unrelatable to many. The combination of cognition and voice recognition will now enable us to use devices with just our voice, making it accessible to many, thus breaking down the barrier many might have faced earlier

The applications of such devices are immense. We believe, like the events that helped humans as a species, leapfrog in its evolution; cognition and voice recognition in machines will change the way we interact with devices and how they will have a lasting impact on our lives.

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Top Big Data Analytics trends in 2019

2018 bought to fore a range of changes with reference to data. The significance of information within organizations was on a rise, and so were megatrends such as IoT, Big Data and Machine Learning. Integration and governance of cloud are significant data initiatives which achieved a new high as well.

What big data has in store for 2019 hence comes across as a point of interest.

The top trends are likely to be in continuation of what was witnessed in 2018. We can also look forward to new developments which pertain to even more data sources and types. The need for integration and cost optimization will increase, and the organizations would be using even more advanced analytics and insights.

Let us take a look at the top trends in big data analytics in 2019.

1. Internet of Things (IoT)

IoT was a booming technology in 2018. It has significant implications on data and a number of organizations are undertaking efforts to tap the potential of IoT. The data offered by IoT will reach a high, and it is likely that organizations will continue to face a difficulty in putting the data to avail with their existing data warehouses.

The growth of digital twins is likely to come across issues of a similar nature. Digital twins are digital replicas of people, places or just about any kind of physical objects. A few of the experts estimate that by the year 2020, the numbers of connected servers will exceed 20 billion. In order to substantiate the value of the data, it would be essential to integrate it into a modern data platform. This would have to be achieved by the use of a solution for automated data integration, which would enable unification of unstructured sources, de duplication and data cleaning.

2. Augmented Analytics

In 2018, a majority of qualitative insights were not taken into consideration by data scientists, following analysis of large amounts of data.

But as the shift towards augmented data gains a greater prominence, systems will use machine learning and AI to yield some insights in advance. This will, with passage of time come across as an important trait of data analytics, management, preparation and business process management. It may even give rise to interfaces, wherein users will be able to query data using speech.

3. Use of Dark Data

Dark data is the information that organizations, collect, store or process as well as resulting from their everyday business activities, but are unable to use for any applications. The data is collected vastly with the intention of compliance and while it takes up a significant amount of storage, it is not monetized in any way to yield a competitive advantage for a firm.

In 2019, we are likely to see even more emphasis on dark data. This may include digitalization of analog records, such as old files and fossils in museums, following their integration into data warehouses.

4. Cost optimization of the Cloud

Migration of a data warehouse to the cloud is less expensive than saving it on-premise, but the cloud can be further optimized still. In 2019, cold data storage solutions, such as Google Nearline and Coldline will be coming into prominence. This will let organization save 50% of expenses towards saving the data.

5. Edge Computing

Edge computing refers to processing information close to the sensors and uses proximity to the best advantage. It works towards reducing network traffic and keeps the system performance optimal. In 2019, edge computing will come to fore and cloud computing will become more of a complimentary model. Cloud services will go beyond centralised servers and become a part of on-premise servers as well. This augurs well for cost optimization and server performance alike for organizations.

A few of the experts believe that with a decentralized approach, edge computing and analytics comes across as a potential solution for data security as well. But an important point to be noted in this regard is that edge computing enhances the number of potential access point for hackers. A majority of edge devices are lacking in IT security protocols as well, which makes an organization more vulnerable to hacking.

Advances in edge computing have paved the way for even more requirement of a flexible data warehouse that can integrate all data types in order to run the analytics.

6. Data Storytelling

In 2019, with more and more organizations transferring their traditional data warehouses to the cloud, data visualization and storytelling are likely to advance to the next level. As a unified approach for data comes to fore as aided by cloud based data integration platforms and tools, it would enable even a larger number of employees to reveal accurate and relevant stories based upon the data.

With an enhancement of business integration tools that enable organizations to overcome issues related with data isolation, data-storytelling will become reliable, and in a position to influence business outcomes.

7. DataOps

DataOps came across as a prominent trend in 2018, and is expected to gain even more importance in 2019. This is in a direct proportion of the enhancement of complexity of data pipelines, which calls for even more tools for data integration and governance.

DataOps is characterized by application of Agile and DevOps methods across the lifecycle of data analytics. This initiates from collection, followed by preparation and analysis. Automated testing of the outcomes is the next step, which are then delivered to enhance the quality of data and data analytics.

DataOps is preferred because it facilitates collaboration of data and brings about continuous improvement. With a statistical process control, the data pipeline is monitored to ensure a consistent quality of data.

In order to leverage these trends to their optimum advantage, vast numbers of organizations are coming to realize that the traditional data warehouses call for an improvement. As resulting from a larger number of endpoints and edge devices, the number of data types has increased as well. Use of a flexible data platform hence becomes imperative to efficiently integrate all data sources and types.

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TypeScript and React – A perfect Match

Today, while we extensively use social media like facebook, twitter or others; our screen, page, feed, etc., is constantly being updated with the latest news, shares, articles, or other latest updates. This is an essential element contributing towards the success of any social media platform. If one were to stop and think about this; it seems very simple and rudimentary, but they are in fact highly expensive in terms of performance. These continuous live update of the front end are technically called DOM operations and they are crucial for the smooth performance of a page.


A Javascript library for building UIs comes as a welcome relief to overcome this issue and it is currently one of the popular libraries in JavaScript. React makes it painless to create interactive UIs. The component logic is written in JavaScript instead of templates, so we can easily pass rich data through the application and keep the application state out of the DOM. The declarative style of React component makes it easy to debug.

However, all the React components are written in JavaScript and they are coupled with the problems associated with javascript.

To tackle this tricky problem a combination of React and TypeScript can be used as it is efficient and it can improve the maintainability of React projects considerably.


Every programmer who has ever written code knows the challenges and inadvertent delays caused while compiling or while run the code. It could be missing integer, a misplaced letter or simple improper use of casing. These tiny, but critical errors on the programmers part, can lead to frustrating time delays which in turn could seriously affect the outcome of your solution. Especially when it comes to JavaScript, the time taken to identify and solve a problem is larger because of its ‘dynamic typing’ nature.

TypeScript lets you write JavaScript the way you imagine and process command or task. It is a typed superset of JavaScript that compiles to plain JavaScript. It is also pure object-oriented with classes, interfaces and it is statically typed like C# or Java.

Another popular JavaScript framework Angular 2.0 is written in TypeScript. It helps javascript programmers to write object-oriented programs and have them compiled to JavaScript, both on the server side and client side.

Salient features like type definitions – make it easier to refactor the variable names, which is a hard task in JavaScript, while Intellisense (Autocomplete and type error detection) – supports TypeScript and is an effective time-saver during compilation.

For example, TypeScript avoids unintentional errors like typos. Javascript will accept any attribute name to that object but TypeScript allows only the available attributes of the type.

In the below code, there is a typo. The programmer has typed inrecieve instead ofreceive

Advantages of TypeScript:

Typescript will provide compile-time errors for most common problems in a React project, such as:

  • All required properties for a React component is not supplied from parent
  • Property supplied as a different type from the parent component
  • The extra property which is supplied to React component from the parent (This will avoid proptypes library which is commonly used in react projects)

If we are using Visual Studio code (VS code) for the react-typescript combination, even the above-mentioned problems will be shown as inline errors which further reduces the time taken to figure out the mistakes.

See the screenshot from VS code:


  • Autocomplete features for typescript is well advanced than JavaScript.
  • State of a react component is defined as a TypeScript interface. This will avoid problems due to null values in states of react component. Typescript will throw an error at compile time if we did not give the default state values at initialization.

Drawbacks on TypeScript:

Even though there are many advantages, TypeScript also has some drawbacks when we start using it in on a large scale. Without the type declarations for the exported attributes and methods for a third party library, we do not get to fully utilize the benefit of TypeScript. So if there is a library which does not have any type definitions, we need to write it our own or look for alternative libraries which provides type definitions. From our experience in web projects, most of the type definitions are available as node modules, thanks to the contributors of open source community. If the project is a React- Native project, things get complicated further due to the availability of type definitions.

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How Can Oracle’s 2019 Java SE Licensing Affect You?

In 2018, Oracle, a leading American multinational computer technology corporation, released a new pricing model for the Standard Edition of Java SE commercial. The company announced that in January 2019, the users of Java Open Source shouldbuy a license for them to receive updates. The news triggered many businesses to take a closer look at their Java Open Source usage and attempt to plot action plans for the Java development kit migration in 2019.

In this article, we’ll analyze every single little detail about Java SE licensing update and consider all the necessary factors to consider as the changes are implemented, including the parties that will be affected by the changes, the actions commercial Java SE users can do to stay compliant to the critical updates, and all the changes in general.

What Are the Changes to the Commercial Java SE Model?

Users have previously known three Java SE products, namely the Java SE Advanced Desktop, the Java SE Advanced, and the Java SE Suite. Before the changes, these three models required users to avail of upfront licenses and annual support. Just this January, those models were replaced by two new models, namely Java SE Desktop Subscription and Java SE Subscription, and they are subscription based.

The important changes include:

  • New Java SE Subscription Pricing
  • New Java SE Subscription Licensing Structure
  • Changes to Public Updates

Which Parties Will Be Affected by the Changes?

Not only the legacy Oracle customers but also all the commercial Java Open Source Code users are expected to be greatly impacted by this change. The good thing about this change though is that customers who use the old Java Open Source Code models will not be forced to shift to the subscription model. Although the two models are the only Java Open Source Code options available for new customers in 2019 and perhaps in the coming years, old customers do not necessarily have to switch to them. However, there may be a number of different reasons to consider a switch. Considering this, it’s important for commercial Java SE users to be aware of the difference of the licensing and pricing.

If you’re using Java SE for non-commercial use under a restrictive scenario, you may have the right to use the Java Open Source Code without paying any fee. However, activating Java’s ‘commercial features’ requires a license. For this reason, it’s advisable to check that you are not using commercial features and that you are abiding by Oracle’s Java licensing policies.

What are the Details of the New Java SE Licensing Structure?

With the new model, you no longer have to purchase a license upfront and pay an annual fee for Java Migration. You will, instead, pay a monthly subscription under terms of one to three years for desktop or server licensing and support. Failure to renew the subscription after the given time period will result in the user losing rights to any commercial software downloaded throughout the subscription period and access to the updates of Java Migration SE and to the Oracle Support.

How Are Java SE Licensing Requirements Calculated?

In the new Java SE subscription models, customers get to choose between desktop and server deployments. Desktop deployments use a Named User Plus metric while server deployments use a processor-based metric to calculate the Java Migration SE license requirements.

The metrics above have the same definition as the standard Oracle technology products. However, NUP minimums still don’t exist. A number of desktop computers and laptops will most likely count NUP licenses in organizations.

What Java Licensing Looks Like?

To answer this question, the guardian should have the right data on the JDK environment. Here are some of the important questions to ask about Java licensing.

  • Where was Java used?
  • Where was Java installed?
  • Which version of Java do you have in your environment?
  • What are the applications that are integrated with Java?
  • How many users are there?

The End of Oracle’s Java Public Updates

According to Oracle’s Java Updates Roadmap, the public availability of the updates will be open again in January 2019, and it did open last month. This means that Java SE 8 commercial users will not receive any critical update after last month, and this can put business operations at risk. In this situation, businesses can either purchase Java subscription licenses or completely move Java SE onto an alternative platform like Oracle OpenJDK or vice versa. The Oracle JDK to open source JDK migration involves using OpenJDK environment and making the open source migrationsuccessful.

Action Items

If you’re an existing Java SE user, it’s important for you to conduct internal assessments of your current Java development to not only ensure your compliance of the license but also determine if shifting to the new subscription model is more cost-effective.

If you want your requirements for commercial use to grow, you need to consider shifting to the subscription model. Should you switch, you are free to use the CPU or NUP based subscription. This is to determine which among the desktop or server-based subscriptions is better for your environment. Your choice depends on your licensing requirements.

If you feel like you need assurance for being a commercial user, it’s advisable for you to conduct an internal assessment. This is because of the organizations that run Java SE’s free version.

To secure your safety, let your legal team confirm that the Java licensing policies of Oracle allow your team to use Java SE without purchasing the commercial licenses.

Tips for Java Migration

Not all Java users know the ins and outs of Java migration, but experts know the right processes involved in Oracle JDK to open source JDK migration to make the open source migration smooth and successful with the open source Java development kit.

Before OpenJDK Migration:

Before the OpenJDK migration, it’s advisable to develop a continuous integration JDK environment to build a JDK source code online and run open source migration and unit tests against an open JDK environment.

It’s also ideal to prepare a list of dependencies with the use of build tools like Java development kit migration and then perform inventory analysis.

During OpenJDK Migration:

Conduct a performance test on your app that runs an open source migration. Make sure the performance test scripts have been appropriately updated when pushing the JDK source code online.

Also, thoroughly test any Oracle JDK to open source JDK migration and beware of the quirks with the algorithm of the memory management between the Java Development Kit Migration

After OpenJDK Migration:

Double check the Oracle JDK to open source JDK migration and the JDK environment if every aspect of the Java development kit migration has been successful.

The Java development kit migration is not an easy task – not even for the experts. Nevertheless, it’s a doable task that can be successfully performed with the right open source Java development kit.

We here at Tarams Software Technologies help companies migrate from Oracle JDK to OpenJDK. We understand the need of the hour and our in-house experts are always ready to answer your queries and assist you in achieving your business goals.

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