Data Science & Analytics coupled with Machine Learning & Artificial Intelligence are the common ‘buzzwords’ or ‘trending topics’ one hears these days. Many corporations and companies alike, want to work with or in the fields of Data Science, Data Analytics and Artificial Intelligence.
Some of the topics that pop into mind here are:
- Forecasting, Predicting and Profiling Models through Statistics or Machine Learning
- Text Analytics and creating customized Chatbots
- Image Processing and creating models like Facial Detection and Recognition Systems
Now we explore why companies are looking forward to work on topics and fields mentioned above and concentrating on data-driven technologies.
Extensive amount of Data
By 2020, the accumulated volume of data will increase from 4.4 zettabytes to roughly 44 zettabytes or 44 trillion GB. This data contains valuable information that can be harnessed by businesses today. Data Analysis and Model Creation can help to analyze this data and makes sense of it.
High Economic Returns
As mentioned earlier, huge amounts of data from various sources like Social Media, Ecommerce sites, Search Engines are being generated regularly. This valuable data has to be stored and analyzed properly to make profitable decisions for the business. Access to and the economic output from this Data Storage is directly proportional to the business revenue of these Data Companies. Hence, Data Science & Analytics is shaping out to be a profitable industry.
DATA IS THE NEW OIL : This statement is credited to the famous mathematician Clive Humby from back in 2006, but has recently picked up more steam after the Economist published a 2017 report titled “The world’s most valuable resource is no longer oil, but data”.
To further look at this analogy we need to answer the following questions
Which is the most recognisable or popular company today?
This is a no-brainer. Everyone knows or has heard of Google. As the popular saying goes – ‘Google knows everything’. At the recently held ‘Race360’ – an Artificial Intelligence Conference, the India Head of a well known international Bank said “Even though, I am using the basic phone (not a smartphone), Google knows who I am. I cannot fool Google”.
What he meant by this statement was, Google – with its access to the data stored, used and accessed everyday, is at the forefront of companies relying on Data Science & Analytics and this data is regularly used for generating revenue through various means and methods.
Which is the biggest social media network in the world?
With around 2.23 billion Monthly Active Users (MAUs), it is clearly in the lead against other popular networks. Facebook’s MAUs are liking, sharing and commenting on the posts, photos and videos daily. This valuable data is regularly harnessed for services that have a global reach and scale.
From the Google and Facebook example, we realize that Data Science & Analytics is a viable and crucial technology with access to revenue generation. All of that while improving the user’s experience and making them happy for their data contributions.
In summation, we can see the clear cut connection between Data Science & Analytics and revenue generation. Many corporations and companies are reaping the benefits of the advantages one gets by implementing the right avenues under Data Science & Analytics.