MWLUG2017 - The Data & Analytics Journey 2.0

2. THE THREE THINGS YOU ARE GOING TO LEARN 1. Big Data does not mean “Big Costs” 2. How mid-market / market-leading and growth companies have seen large benefits 3. Broader understanding of what’s possible to move their company through the journey © 2017 PSC Group, LLC

4. • Introductions • State of the Union – Analytics, BI & Big Data for the Mid-Market • Visualization • Data Warehouse as a Service • Cognitive Services • Machine Learning for the Masses • Wrap-up © 2017 PSC Group, LLC

5. JOHN HEAD • Chief Evangelist & Business Development • IBM Dual Champion - Collaboration and Cloud • 25 years experience • 19 Consulting, 6 sales • Speaker of 70+ sessions at conferences and user groups around the world • Specialize in Application Modernization & Integration • 5 year Lumity Exec Board Member • YWCA of Metropolitan Chicago Exec Board Secretary, Board Member © 2017 PSC Group, LLC

6. OUR METHODOLOGY MODERNIZATION, NOT MIGRATION Inventory Existing Application Portfolio Categorize and Prioritize Estimate Modernization Costs Determine Landing Platform Network Impact Analysis Data Center Impact Analysis Define Security Model on Landing Platform Establish Tools & Standards Application Transformation Data Transformation Sunset Legacy Environment Develop Support and Staffing Plan Application Modernized! Reduce Licensing of Legacy Environment Define Governance Model Modify Infrastructure Establish Development Environment Specify and Procure Production Hardware and Software Analysis & Design Prepare for a more data driven, mobile, social and dynamic future Identify opportunities to enhance processes, workflow and security Technical Analysis Business Value Analysis Cultural Change Analysis Develop Training Plan and Materials Train End Users on Modernized Application ANALYZE MODERNIZE © 2017 PSC Group, LLC

7. • Introductions • State of the Union: Analytics, BI & Big Data for the Mid-Market • Visualization • Data Warehouse as a Service • Cognitive Services • Machine Learning for the Masses • Wrap-up © 2017 PSC Group, LLC

9. WHY NOW? • Before 2014, Big Data/BI/Analytics was a game of the big enterprises • Infrastructure • Resources • Cost • “Reporting” was the Mid-Market sweet spot • Excel / Crystal / Tableau © 2017 PSC Group, LLC

10. WHAT CHANGED • Since 2014, the following has changed: 1. Acceptance of the cloud 1. Start-ups vs Mid-Market vs. Enterprise 2. Cost of Entry dramatically decreased 3. Need for specialization has decreased 4. Competitive Advantage of using your data is attainable © 2017 PSC Group, LLC

11. “BIG” MYTHS • “Big” in Big Data/BI/Analytics no longer means • Big Cost • Big Infrastructure • Big Maintenance • Big Teams • Big Data/BI Analytics is accessible to companies of any size © 2017 PSC Group, LLC

12. BUSINESS INTELLIGENCE MATURITY ROADMAP Fixed What is going on? Self Service Let me see what is going on. Monitoring Are we meeting our KPIs? Predictive How can we be more efficient? Increasingly Mission Critical Increasingly resource intensive © 2017 PSC Group, LLC

14. VISUALIZATION • (Data) Visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that might go undetected in text-based data can be exposed and recognized easier with data visualization software. © 2017 PSC Group, LLC

16. VISUALIZATION Traditional On Premises Tools • Visualization as an IT service • Excel to enterprise grade • Reliance on someone else providing the data service Cloud Based Tooling • Visualization as a Platform • API Architecture • Consumption of services © 2017 PSC Group, LLC

19. TURNING DATA INTO BUSINESS INSIGHTS IS CHALLENGING Common BI challenges include… Multiple data sources Data residing in SaaS solutions and other external locations is difficult to access and refresh securely End-to-end view Data often resides in disparate locations, making it difficult to see a complete picture of your business Right data for the right users at the right time Different roles have different needs and business users need the latest operational data © 2017 PSC Group, LLC

20. DATA SOURCES • Connect to cloud services you already use - popular SaaS solutions • Quickly start with solution-specific content packs which include • Explore data with fast data processing • Automatic data refresh is built-in © 2017 PSC Group, LLC

21. KEEP ALL YOUR DATA CURRENT • Real-time dashboards • Live connectivity • Automatic or scheduled refreshes Live query Popular SaaS Solutions Live dashboards and reports Dynamics Marketing BI SQL Server Analysis Services (SSAS) Secure Credential Store © 2017 PSC Group, LLC

22. CLOUD BASED BI BUILDER BI REST APIsBI Desktop Prepare Explore ShareReport Data sources SaaS solutions e.g. Marketo, Salesforce, GitHub, Google analytics On-premises data e.g. Analysis Services Custom content packs Corporate data sources or external data services Cloud services SQL, Stream Analytics… Excel files Workbook data / data models BI Desktop files Data from files, databases, Cloud, and other sources BI service Data refresh Visualizations Live dashboards Content packs Sharing & collaborationNatural language query Reports Datasets01001 10101 © 2017 PSC Group, LLC

24. THE VALUE OF DATA • With the success of Platform as a Service IBM is moving quickly to compete with their visualization and analytics platform. • Exclusive Access to the complete Twitter and Weather Channel data streams. © 2017 PSC Group, LLC

25. CASE STUDY: CHICAGO CHILDREN’S HOSPITAL • Goal: Reduce the readmission rate of patients and increasing the percentage of provider appointments offered during family-friendly hours. • Challenge: Large number of underlying data sources and methods for accessing data. • Solution: The team was trained to better understand how to proactively reduce readmission rates by digging into the data to determine if a patient is being readmitted for the same issue or a different one, if they’re seeing the same provider, the therapy that is being prescribed, and more. Likewise, they can evaluate key trends in relationship to provider appointments during family-friendly hours. © 2017 PSC Group, LLC

27. DATA WAREHOUSING AS A SERVICE • Data Warehousing as a Service (DWaaS) is an outsourcing model in which a service provider configures and manages the hardware and software resources a data warehouse requires, and the customer provides the data and pays for the managed service. © 2017 PSC Group, LLC

28. DATA WAREHOUSING AS A SERVICE "We are using Cloud Data Warehouse’s elasticity and scaling capabilities to scale up our systems when we need to do analytics on all the data we are collecting from thousands of devices, and then scale down, thus optimizing on cost without compromising performance." Roger Shih, Senior Technical Product Manager, Toshiba America Business Solutions © 2017 PSC Group, LLC

30. A MODERN DATA WAREHOUSE AS A SERVICE • Amazon RedShift • Microsoft Azure Data Warehouse • Google Big Query • IBM dashDB BI and analytics Data management and processing Data sources Non-relational data Data enrichment and federated query OLTP ERP CRM LOB Devices Web Sensors Social Self-service Corporate Collaboration Mobile Machine learning Single query model Extract, transform, load Data quality Master data management Box software Appliances Cloud SQL Server Box software Appliances Cloud © 2017 PSC Group, LLC

31. A MODERN DATA WAREHOUSE AS A SERVICE

33. MASSIVELY PARALLEL PROCESSING

35. CLOUD FLEXIBILITY

36. CASE STUDY: UK NATIONAL AIR TRAFFIC SERVICES (NATS) • Goal: Using ever increasing data volume to address compliance needs • Challenge: Providing a flexible on demand platform to handle more people while reducing pollution and risk. • Solution: Using a cloud data warehouse solution NATS were able to analyze a flight plan versus a flight’s actual trajectory and accurately model fuel usage and CO2 output to understand the effect of network influences and operational decisions. This enables the strategic management of the air traffic operation with more information to hand, and have more confidence in our decisions. © 2017 PSC Group, LLC

38. COGNITIVE SERVICES • Cognitive computing is the simulation of human thought processes in a computerized model. Cognitive computing involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works. © 2017 PSC Group, LLC

39. COGNITIVE SERVICES “What I excited about is that these tools will unleash the creativity necessary to ultimately help us gain market share in our industry.” Prashant Bhuyan, Co-Founder, Alpha Modus © 2017 PSC Group, LLC

42. COGNITIVE API SERVICES • Vision • Content Moderator • Emotion • Face • Video • Text to Speech • Speaker Recognition • Linguistic Analysis • Text Analytics • Translator • Knowledge Exploration Service • Recommendations • Search © 2017 PSC Group, LLC

43. COGNITIVE API SERVICES

45. CASE STUDY: HYPERFISH • Goal: Increase collaboration within an organization by helping to fill holes in personnel directory data. • Challenge: Users have no picture or can post any image. • Solution: Using cognitive services as part of their solution HyperFish are able to determine the number of people in a picture. If the likelihood of this being not equal to one, the user is asked to provide as alternative image. © 2017 PSC Group, LLC

47. MACHINE LEARNING • Machine learning is the subfield of computer science that gives "computers the ability to learn without being explicitly programmed.“ Evolved from the study of pattern recognition and computational learning theory in artificial intelligence,machine learning explores the study and construction of algorithms that can learn from and make predictions on data. © 2017 PSC Group, LLC

48. MACHINE LEARNING “The trouble is, data scientists rarely sit down and talk to business people. If a technical book company wants to sell more books, then the business question it really should ask itself is: how do people want to learn today?” Tricia Wang founder Constellate Data © 2017 PSC Group, LLC

50. CLOUD PREDICTIVE ANALYTICS • Drag and drop Predictive Analysis • Visual comprehension of the ideas and concepts • Cloud based • As complex as you need it to be • Accessible as a service © 2017 PSC Group, LLC

54. CASE STUDY: TACOMA PUBLIC SCHOOLS • Goal: Reduce school dropout rates • Challenge: Significantly improve the “dropout factory” 55% graduation rates. • Solution: The Tacoma public school district has delivered a dramatic turnaround – eight years ago five of the high schools were described as “dropout factories”, and five years ago just 55% of students graduated on time, compared to 81% nationally. But last year that had been boosted to 78%, ensuring that the district is recognized nationally for its educational achievements. The district is now developing the next level of data-driven improvement with the help of Machine Learning. © 2017 PSC Group, LLC

55. • Introductions • State of the Union – Analytics, BI & Big Data for the Mid-Market • Visualization • Data Warehouse as a Service • Cognitive Services • Machine Learning for the Masses • Wrap-up

56. THE THREE THINGS YOU LEARNED 1. Big Data does not mean “Big Costs” 2. How mid-market / market-leading and growth companies have seen large benefits 3. Broader understanding of what’s possible to move their company through the journey © 2017 PSC Group, LLC

MWLUG2017 - The Data & Analytics Journey 2.0

John Head

MWLUG2017 - The Data & Analytics Journey 2.0