SESSION 308 Wednesday, March 25, 3:00 PM - 4:00 PM Track: Industry Insights

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1 SESSION 308 Wednesday, March 25, 3:00 PM - 4:00 PM Track: Industry Insights Service Desk and Big Data: What's Expected From You Judy Benda-Schnurr Director, Long View Robin Bell CTO, Long View Session Description Long View's CTO and director have conducted numerous engaging and productive roundtables on Big Data, and they want to share the results with you! In an interactive panel discussion, Judy Benda-Schnurr and Robin Bell will discuss basic information gathering, the need to federate both structure and unstructured data, and C-level engagement with, in, and around Big Data. They will focus on three areas in particular: business intelligence (reports and dashboards), advanced analytics, and Big Data (volume, velocity). (Intermediate) Speaker Background Judy Benda-Schnurr has more than twenty years of experience in the service desk industry. A strategic and innovative speaker, Judy has presented at international HDI conferences and local chapters events, as well as authored articles for several publications. Her experience includes ITIL instructor, ITSM consultant, management consultant, and enterprise reengineering expert. Robin brings years of IT experience. He has been the management consultant for significant industries in a technical and leadership capacity. He is one of the founders of Long View Systems, which is entering its 15th years of business. He oversees all technical direction and leadership for Long View. He also conducts regular CIO round tables. This past year he has focused on Big Data. An industry expert and excellent presenter, author and leader!

2 Session 308 Robin Bell Judy Benda-Schnurr Introduction Robin Bell: CTO; Judy Benda-Schnurr, Director Long View Systems Define Long View s technology strategy Oversee Research and Development program Part of the Gartner Executive Program, and sit on Gartner s Symposium and IT Expo advisory board Passionate about Big Data! And More Passionate About Service Desk Optimization!!

3 Big Data What is it? Volume Velocity Big Data Variety Complexity Big Data What is it? Social Computing Volume Pattern Based Analytics Context Aware Computing Velocity Big Data Variety Search/Mobile Social Networking Complexity Documents Transactional Data IT/OT Images Audio Text Video Enterprise Systems

4 Big Data: Hype or Reality expectations Big Data 2013 Big Data 2012 Big Data 2014 Shift is from managing data to making decisions. Are you? Peak of Inflated Innovation Trigger Expectations Years to mainstream adoption: Trough of Disillusionment time Slope of Enlightenment less than 2 years 2 to 5 years 5 to 10 years more than 10 years As of September 2013 Plateau of Productivity obsolete before plateau This chart is a composite, derived from Gartner published Hype Cycles. The particular combination and comparison of items made here has not been reviewed by Gartner Big Data By The Numbers Big Data searches on Gartner rank 2 nd Spending is forecasted to soar from $13B in 2013 to $114B in 2018 Recent study finds only 27 percent of Big Data initiatives are successful Gartner Survey shows 73% of respondents have either invested or planning to invest in technologies to address Big Data

5 Big Data BI / Analytics ranked #1 for spending in CIO Survey BI / Analytics ranked as highest priority in CIO Survey Big Data is Real Big Data Analytics not yet mature Oil & Gas Financial IT Predictive Analytics used for Drilling wells Distributed Fiber Acoustic sensors can produce 3 terabytes/hour Process control networks generate Compliance - BASEL 3 requirement to report daily cash position Data Center infrastructure Log Data Incident/Service Request data (service desk, not help desk)

6 What Is Long View Doing? Procurement and Licensing Practice Overall sentiment from clients: Where is my money going? What insights do we need? Analysis of $$ spent What it was spent on Who it was spent with Buying patterns, product refreshes Insight into when purchases occur to maximize discounts What support do we need? Did Market analysis on vendors that could satisfy uses case criteria and integrate with existing systems Looked at SaaS vendor solutions to maximize time to value Vendor worked with Long View team to normalize data for Analysis Long View Analytics Client spend dashboard: spend by category

7 Long View Analytics Client spend dashboard: spend for End User Products Long View Analytics Client spend dashboard

8 Long View Analytics What s next? Phase I Time to value, 4 months Analytics is not real-time, data is refreshed every 24 hours Additional phases Adding Services Adding Client data that isn t Long View s Incorporating Smart machine technology (AI) to generate further queries Getting Started Next steps Informal HDI member poll indicates greater than 90% of you have not been asked to supply Service insight to your business Look for opportunities with data you own Understand your company Meet with your stakeholders and business units regularly Begin building your use cases what are the insights your customers are asking for? Look to the cloud market to help you but please work with your IT to do it

9 Thank you for attending this session. Don t forget to complete an evaluation form!

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