Making Advanced Analytics Work for You
- 1. Making Advanced Analytics Work for You This presentation is made as part of Data Analytics Internship by Prof Sameer Mathur IIM LUCKNOW
- 2. Overview Big data and analytics have rocketed to the top of the corporate agenda. That most companies are unsure how to proceed. Leaders are understandably leery of making substantial investments in big data and advanced analytics. As data-driven strategies take hold, they will become an increasingly important point of competitive differentiation.
- 3. HOW IMPORTANT IS ADVANCED ANALYTICS FOR PROFESSIONALS • Best-in-class companies and organizations in North and South America lead the way when it comes to predictive and advanced analytics. • On the other hand, the trend is much less important in telecommunications companies and the German-speaking region of Central Europe.
- 4. WHY ADVANCED AND PREDICTIVE ANALYTICS IS BECOMING SO IMPORTANT New big data technologies enable cost- effective storage, processing and analysis of large amounts of data Modern and intuitive user interfaces allow more user groups to draw insights and make informed decisions Advanced analytics software enables better analysis, and analysis of relationships and future events.
- 5. BIG DATA, THE REVOLUTION According to research by Andrew McAfee and Erik Brynjolfsson, of MIT, companies that inject big data and analytics into their operations show productivity rates and profitability that are 5% to 6% higher than those of their peers. Experience reveals that most companies are unsure how to proceed
- 6. Theory that certain knowledge is impossible • Leaders are understandably leery of making substantial investments in big data and advanced analytics. • They’re convinced that their organizations simply aren’t ready. After all, companies may not fully understand the data they already have, or perhaps they’ve lost piles of money on data-warehousing programs that never meshed with business processes, or maybe their current analytics programs are too complicated or don’t yield insights that can be put to use. • Or all of the above. No wonder skepticism abounds.
- 7. Traditional reports only show data. If the data is correct, then reports are highly likely to be reliable as well, as most modern environments are now quite mature and their reporting methods and concepts have reached a high level of sophistication. Today, a large number of standard algorithms and methods are available for specific use cases (e.g., customer classification), and new ones are constantly being developed. Finding the most appropriate one for a dataset depends largely on the abilities of the user and the software used. Furthermore, algorithms can also fail due to lack of data (e.g., the customer classification model). If an advanced analysis project shows that no results can be found, it should be aborted and the next project started.
- 9. Rather than undertaking massive overhauls of their companies, executives should concentrate on targeted efforts to source data, build models, and transform the organizational culture
- 10. That nimbleness is essential, given that the information itself—along with the technology for managing and analyzing it—will continue to grow and change, yielding a constant stream of opportunities.
- 12. Name: Soumyadeep Sengupta College: University of Engineering and Management , Kolkata Email: Soumyadeepsen97@gmail.com