Thanks to the digital revolution that is sweeping the world and India in particular, data scientists are now the most sought-after professionals by big corporations as well as startups. Companies across industries are rewarding good data analysts and scientists with desirable career growth and salaries.
59% of companies plan to increase positions requiring data analysis skills
”If you torture data long enough, it will confess.Ronald CoaseClifton R. Musser Professor of Economics at the University of Chicago Law School
These numbers craft a tell-all
5,00,000 Projected Job Openings For Data Scientists In 2018 by NASSCOM
92% of Fortune 500 organizations will need to exploit big data by 2020 to stay in the game. Analytics Firms In India are Facing a Shortfall of over 2,00,000 skilled Data Analysts. Projected growth in global data generated each year is 40%.
Connect these three dots. You will then understand the relevance of Data Analytics Expertise in the industry today.Show Me How
Data Analytics certified individuals break into the $100,000+ pay and are among the highest-paid professionals globally
The latest generation of visualisation tools is easy to adopt and offer an immediate business advantage and effective storytelling. They can also be a useful way of establishing best practice ways of looking at your data.
There is a misconception that working with data requires advanced programming skills. This might have been the case in the past, but with the rapid developments in technology the barriers have been lowered.
By combining raw data, a set of hypotheses and people with domain knowledge, analytics experts can quickly test iterative processes to create a working solution. Such quick delivery enables you to decide whether a long-term implementation is right for your business.
More data often means more insight. But it isn't always simple to obtain; data diversity requires tackling disparate sources, varied data sets and unstructured data. Employing the current wave of data blending tools, you can bridge the gap between all these sources.
R & Python Basics for Analytics
R & Python are the most robust environments for Data Analytics in the industry today.
The goal is to communicate information clearly and efficiently to users. This is perhaps the most common application of Data Analytics.
Advance your data-crunching skills and refine your ability to work with messy, complex datasets.
Learn to manipulate and prepare data for analysis, and create visualizations for data exploration. Finally, you’ll learn to use your data skills to tell a story with data.
Supervised and Unsupervised Algorithms
Understanding the difference in these two and how the industry looks at them.
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