ASUG Illinois-Chicago Chapter Meeting | Nov 6, 2014 ‘Big Data’: Peeling the onion of assumptions, confusion, and potential issues. Thomas McGinnis, Ph.D. - Grand Valley State University

We’ll address several questions in this session…  How did we get here? … a brief history of the terms and context  How big is big? … what does big data mean, and not mean  What does this mean to me and my organization?  What does the future hold? LEARNING POINTS

History Today Big Data BW BI

 The Term ‘Big Data’ was coined in 2001 … why is it so ‘hot’ now? Many different things have come together …  Business Changes  Global competition  Technology as a commodity  Leveraging underutilized assets  Technological Changes  Storage price deflation  Device form factors  Connectivity (sources of data)  Societal Changes  Millennials  General attitudes about sharing information The Latest Buzz

How Big is Big? Image: MB  GB  TB  PB  EB  ZB  YB 1 billion gigabytes = 1 exabyte 1 billion terabytes = 1 zettabyte 1 trillion terabytes = 1 yottabyte 2013 estimate = 4 yottabytes

From Gartner: Part 1: high-volume, high-velocity, high-variety data, (high-veracity?) Part 2: Information assets that demand cost-effective, innovative forms of information processing. Part 3: To provide enhanced insight and decision making. Big Data Defined

Business Intelligence: An umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance. Advanced Analytics: Solutions used to build analysis models and simulations to create scenarios, understand realities and predict future states. Business analytics includes data mining, predictive analytics, applied analytics and statistics, and is delivered as an application suitable for a business user. Data Warehousing: A storage architecture designed to hold data extracted from transaction systems, operational data stores and external sources. The warehouse then combines that data in an aggregate, summary form suitable for enterprise-wide data analysis and reporting for predefined business needs. Other Terms …. Big Data Business Intelligence Advanced Analytics Data Warehousing Definitions from

What does the future hold? Analytic Capabilities (tomorrow) Business Applications Business Applications Business Applications Business Applications Business Applications (today) Analytic Capabilities Analytic Capabilities Analytic Capabilities Analytic Capabilities

 Strategic Issues  Strategy Itself  Governance  Talent  Data Analytics  Predictive  Behavioral  Interpretation/discovery  Enterprise Information management  User Expectations  Costs  Tools Key Organizational Challenges We Face

What does this mean to you and your organization? Now the fun part…..

 How & why we got ‘here’  What Big Data means  What Big Data doesn’t mean  The organizational challenges we will face  We have common issues/concerns  It’s still early day’s, diligence is needed to set and stay on course KEY LEARNINGS

Thomas McGinnis Grand Valley State University GVSU’s ERP Initiative: ERP Course work BPR Configuration ABAP Business Intelligence TERP 10 Contact Information

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