The Big Data Deluge: Creating Serious Business Problems. Analytics: Harnessing Big Data Deluge to Acquire Business Power



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The Big Data Deluge: Creating Serious Business Problems Analytics: Harnessing Big Data Deluge to Acquire Business Power

Predictive Analytics: The Holy Grail of Big Data Analytics

The Predictive Analytics Lifecycle

What is Predictive Analytics (PA)? Predictive Analytics is the science of analyzing business data to make predictions and forecasts about the future. These predictions are acquired by automatically learning and using a mathematical model called a predictive model. How is Predictive Analytics Associated with Big Data? Nowadays, the business data being used to learn the predictive model is big data which has the 3V s characteristics, i.e., high velocity, high volume and high variety. In essence, predictive analytics is a core subset of big data analytics. What are the Potential Benefits of Predictions for my Business? The predictions are valuable insights acquired after a comprehensive drill-down analysis of your big data. They answer the question what will happen next, which goes one step ahead than the traditional BI questions of what happened or what is happening. Give Me Some Examples of Business Predictions Telecom: Predicting Customer Churn in advance - Forecasting Consumer Subscriptions in advance Financial: Predicting Loan Defaulters and Fake Insurance Claims in advance Forecasting Cash Flow data for the future (upcoming) time period Pharmaceutical: Predicting the assignment of marketing personnel to doctors in advance - Predicting the usage pattern of a new medicine in advance FMCG: Predicting manufacturing bottlenecks and late delivery of goods in advance Will the Predictions Always Happen? Will They Always be True? NO. The predictions given by the predictive model are reliable to a certain degree of confidence. For example, a confidence of 80% means that out of 100 predictions given by the model, 80 are strongly expected to be true. So What is the Ideal Level of Confidence for Predictions? Any predictive model with a confidence 60% is a big deal. For example, suppose that I can predict with 60% confidence the consumers who are going to churn soon from my services. This means I can potentially convert 60% of churning consumers to non-churning consumers (before the churn actually happens).

I am Bought on Using Predictive Analytics. How do I Use It? The predictions are meant to supplement your strategic and tactical business executions. They are not meant for a wide enterprise revamp. You need to figure out how to best incorporate and use these predictions within your business strategies. What s the Monetary Benefit and ROI of using Predictive Analytics? There is always a monetary benefit of predictions. The actual amount depends on your business. In a large-scale business (Telecom, FMCG, Energy etc.), the benefit can easily run into millions. If the Monetary Benefit is High, How Come Predictive Analytics is not being Adopted Openly? Because predictive analytics is complicated. You need the right people and expertise, which is not easily available. You need to make a small investment in this new technology, which is not so easily acquired. You need to test the predictions within your business, for which most employees don t have the time. You need to figure out how to incorporate predictions in your business, which can make most managers nervous due to uncertainty of predictions. So, How to Go About it Then? Start Small. Get the predictive analytics team to work on a small subset of your data (as a POC) and dedicate only 1-2 employees to answer queries regarding your data. Analyze the POC results critically and take your time selling the idea to the higher management. If they are convinced, then start with the implementation of the predictive model with highest confidence. If results on real-life business data are good, then supplement your business execution with the predictions. You can take your time to start implementing the other predictive models (if any).

What is this Hands-On Workshop all about? This goal of this hands-on workshop is to convince you that Predictive Analytics is your need. For this, we will take you step-by-step through the process of Predictive Analytics. You will learn the theory of each step as well as its practical value through hands-on experience. What is Major Takeaway of this Workshop? The conviction that Predictive Analytics should be applied in your business and the core insightful knowledge of how to go about it. Why Should I Attend this Workshop? This workshop couples both theory and practical experience of the state of the art predictive analytics technology, which is gaining a wildfire adoption rate globally. It will help you to easily understand the technology, figure out why it is important and determine ways to implement it in your organization. Who Should Attend this Workshop? This workshop is feasible for a wide range of personnel: Business Managers, Technical Managers, BI managers, IT heads, Data Analysts, Data Scientists, Data Statisticians, Database Administrators, Data Analytics Head Which Datasets will be used for Hands-On Sessions? Real-life (masked) Industrial datasets. Which Tools will be used for Hands-On Sessions? State of the Art tools: R, Rapid Miner and IBM SPSS

Habib University Continuing Education Series - Big Data Workshop Predictive Analytics: Predicting Business Performance from Big Data June 13 th and 14 th 2015 9:30 AM 5:30PM @ Habib University Campus Workshop Fee: Rs. 20,000* Seats are limited * Discount for Corporate Groups, Students and Academics Workshop Schedule: Saturday 13 th June 09:30 AM 11:30 AM: Theory, Problem and Applications of Big Data, The Need for Predicting Big Data 11:30 AM 12:00 PM: Tea Break 12:00 PM 01:00 PM: Predictive Analytics on Big Data: Concept and International Industrial Use Cases 01:00 PM 02:00 PM: Lunch and Prayer Break 02:00 PM 03:30 PM: Predictive Analytics Process: Creating the Data Landscape through ETL 03:30 PM 04:00 PM: Hands-On: Explaining Corporate Big Data sets and Configuring The Tools 04:00 PM 04:30 PM: Tea Break 04:30 PM 05:30 PM: Hands-On: Creating Data Landscape with 2 Corporate Big Data Sets Sunday 14 th June 09:30 AM 11:30 AM: Predictive Analytics Process: Creating the Predictive Model 11:30 AM 12:00 PM: Tea Break 12:00 PM 01:00 PM: Hands-On: Predictive Modeling of 1 st Corporate Big Data Set 01:00 PM 02:00 PM: Lunch and Prayer Break 02:00 PM 03:00 PM: Hands-On: Predictive Modeling of 2nd Corporate Big Data Set 03:00 PM 04:00 PM: Predictive Analytics Process: Translating Predictions to Business Value 04:00 PM 04:30 PM: Tea Break 04:30 PM 05:30 PM: Hands-On: Extracting Business Value from Big Data Predictive Models

Workshop Leader: Dr. Tariq Mahmood, is the Chief Data Scientist for Big Data with NexDegree Pvt. Ltd., Data Scientist and Trainer with Innovative Management Services, both based in Karachi, Pakistan. He is also an Associate Professor at the Karachi Institute of Economics and Technology (KIET). He has around 10 years of professional and research experience in the domains of Business Intelligence, Data Warehousing, Data Mining and Advanced Analytics. He also has 6 years of professional and consultancy experience in Big Data Analytics, particularly using Open-Source technologies like the Apache Hadoop platform and NoSQL databases. Notably, Dr. Tariq has designed Big Data Infrastructures for the Healthcare, Telecommunication and Financial sector in Pakistan. He has conducted numerous training and workshops on Big Data, both for Government and Private Organizations, notably the one held at Mariott, Karachi www.pakistanciosummit.com/bigdataworkshop. He also heads the Big Data Research Group at KIET www.sites.google.com/site/bigdatabolt/bdaresearch with a multi-focus on discovering optimized infrastructures for Big Data applications, and of porting current data mining algorithms to the Big Data platform. His primary focus is to facilitate the spread of Big Data technologies in the corporate sector, both in Pakistan and across the globe.