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The Do’s and Don’ts of Big Data Analytics

May 25

Free

Session Time and Date

Thursday, May 25th from 1pm – 2pm CDT

 

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Presentation Description

The only constant with Big Data is change. The data itself is not necessarily new but the fundamental paradigm shift is increased access to data. Advancements in technology vis a vis apps alongside the continued need for advanced programming skills have provided the tools that have allowed for this increased access. But increased access to data has resulted in exponential growth and the need for analytics both from an advanced and non-advanced perspective. Questions abound that with new Big Data technologies, the analytics discipline, itself, needs to undergo transformational changes. But does it?

In this session, we explore the four step process of analytics and how it can be applied to all analytical exercises and projects. Within the Big Data paradigm, we identify what is unique and new to this discipline versus what has remained constant over the many decades of applied analytics within such sectors as credit card risk and direct marketing.

The explosive growth of analytics is best manifested by the development of data science and business analysis departments within many organizations. Yet, unlike other disciplines such as marketing and accounting, which have strong academic foundations, analytics and in particular big data, analytics still relies on its practitioners in the formulation of knowledge as a foundation of learning for its practitioners. The key do’s and don’ts of analytics are discussed in the context of how they can be applied to both big and small data and their ultimate impact to businesses. Case studies and examples both reinforce and provide much richer detail in such key areas as the ability to define the right business problem. Alongside the business problem, we also highlight how the lack of due diligence and detail to the data leads to ineffective solutions even when the business problem has been correctly identified. Given all the discussion on Big Data, the challenge today is to determine what is the appropriate level of information. Gone are the days when practitioners used to extract everything.

Use of the right tools and techniques is also discussed but with emphasis on what is simple and understandable as it is these solutions that are more easily embraced by the marketing and/or business area. Simple is indeed better for most marketing solutions and the rationale for this is discussed in this session. At the same time, Big Data technology has altered expectations in the speed and delivery of solutions. Increasing reliance on automation, which include advanced techniques in machine learning and ultimately artificial intelligence, certainly can deliver on the goal of speed but at what cost. As businesses operationalize and automate more of their processes and methodologies, organizations are relying more strongly on black box solutions. Yet, despite the advantages of enhanced solution delivery, organizations are not always considering the negative impact of “black box” type solutions on being able to effectively analyze their decisions. The key to success is identifying what is the “optimal” compromise which balances the need for speed of the solution versus the ability to understand the details of the solution for effective measurement of the solution.

Other

Primary Speaker First Name
Richard
Primary Speaker Last Name
Boire
Primary Speaker Bio
Richard Boire's experience in predictive analytics and data science dates back to 1983, when he received an MBA from Concordia University in Finance and Statistics. His initial experience at organizations such as Reader’s Digest and American Express allowed him to become a pioneer in the application of predictive modelling technology for all database and CRM type marketing programs. This extended to the introduction of models, which targeted the acquisition of new customers based on return on investment. With this experience, Richard formed his own consulting company back in 1994, which is now called the Boire Filler Group, a Canadian leader in offering analytical and database services to companies seeking solutions to their existing predictive analytics or database marketing challenges. Richard is a recognized authority on predictive analytics and is among a very few, select top five experts in this field in Canada, with expertise and knowledge that is difficult, if not impossible to replicate in Canada. This expertise has evolved into international speaking assignments and workshop seminars in the U.S., England, Eastern Europe, and Southeast Asia. Within Canada, he gives seminars on segmentation and predictive analytics for such organizations as Canadian Marketing Association (CMA), Direct Marketing News, Direct Marketing Association Toronto, Association for Advanced Relationship Marketing (AARM.) and Predictive Analytics World (PAW). His written articles have appeared in numerous Canadian publications such as Direct Marketing News, Strategy Magazine, and Marketing Magazine. He has taught applied statistics, data mining and database marketing at a variety of institutions across Canada, which includes University of Toronto, George Brown College, Seneca College, and currently Centennial College. Richard was Chair at the CMA’s Customer Insight and Analytics Committee and sat on the CMA’s Board of Directors from 2009-2012. He has chaired numerous full day conferences on behalf of the CMA (the 2000 Database and Technology Seminar as well as the 2002 Database and Technology Seminar and the first-ever Customer Profitability Conference in 2005. He has most recently chaired the Predictive Analytics World conferences in both 2013 and 2014, which were held in Toronto. He has co-authored white papers on the following topics: ‘Best Practices in Data Mining’ as well as ‘Customer Profitability: The State of Evolution among Canadian Companies’. In Oct. of 2014, his new book on “Data Mining for Managers-How to use Data (Big and Small) to Solve Business Problems” was published by Palgrave Macmillian. In March of 2016, Environics Analytics acquired Boire Filler Group where his current role is senior vice-president of customized analytics. Check out our blog on “How to Get More Value from your Data https://www.regonline.com/Register/Checkin.aspx?EventID=1698332
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