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Available dates

Nov 28—30, 2019
3 days
Hyderabad, India
INR 135000 ≈USD 1903
INR 45000 per day

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About the course

The rapid proliferation of the Internet and related technologies has created an unprecedented opportunity for enterprises to collect massive amounts of data regarding customers and all aspects of their business operations. Yet the reality is that most organisations today are (i) “data rich” but information and knowledge poor”, and (ii) not harnessing the full potential of their data, which is perhaps the second most important asset after human capital. Internet based applications such as social media, website usage tracking and online reviews as well as more traditional technology applications like RFID, Supply Chain Management (SCM), Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) provide access to vast Participants of this programme will discuss both the bigger picture of the relationship between data mining and cross-functional business efficiencies; and they will familiarise themselves with tools like SAS Enterprise Miner/Text Miner, XLMiner, WEKA, and social media listening tools such as Trackur, NodeXL, and SentiStrength. This programme blends qualitative thinking with quantitative techniques.

WHAT YOU WILL LEARN

  • Improving the decision-making process (quality & relevance)
  • Aligning insights and strategy
  • Realising cost efficiency
  • Improving competitiveness
  • Producing a single, unified view of enterprise information
  • Synchronising financial and operational strategy
  • Effectively increasing revenue through data

Trust the experts

Anitesh Barua

Biography Barua, Anitesh Assistant Professor, Department of Information, Risk, and Operations Management Anitesh Barua received his B.E. from Jadavpur University (India) and his M.S. and Ph.D. from Carnegie Mellon University. His research and teaching interests include measuring business value o...

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Course reviews

Navin P, General Manager from Greater New York City Area

4.7
Course quality: very good
Instructors: very good
Other (e.g. materials, infrastructure): very good
Primary takeaway: Predictive Analytics can be simple to implement and a game changer for every product. Application of it becomes real and a view into applicability of it being universal becomes apparent
Things to improve: Look to give the team more conseptual application based cases and less toolset tutorials. Even asking individuals to start with a real life sample and using one to be solved would be an effective view
Industry:tv and media

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