ENTERPRISE BI AND DATA DISCOVERY, FINALLY

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1 Enterprise-caliber Cloud BI ENTERPRISE BI AND DATA DISCOVERY, FINALLY Southard Jones, Vice President, Product Strategy 1

2 AGENDA Market Trends Cloud BI Market Surveys Visualization, Data Discovery, & Self-Service Cloud BI in action Birst Overview Who we are What we do Customer success 2

3 INSATIABLE DEMAND FOR INSIGHT Source: Gartner/IDC 3

4 KEY TRENDS Growth is being driven by business users The trend is toward decentralization and user empowerment of BI and analytics - Gartner Innovation is being driven by business users ERP based BI no longer industry standard Business users run analytics and visualization applications 4

5 KEY TRENDS The Cloud is here, and it is everywhere Cloud BI is now mainstream 30% of companies plan to adopt public Cloud BI in next 2 years. - Dresner Advisory Services 5

6 MARKET TRENDS IN CLOUD BI 6

7 DEPLOYMENT PLANS GROW 100% 90% Plans for Cloud-based Business Intelligence % 70% 60% 50% 40% 30% 20% 10% 0% 60% 53% 73% 71% 75% 71% 10% 12% 9% 6% 8% 10% 6% 11% 11% 7% 9% 17% 8% 13% 16% 7% 11% 28% Public Cloud Hybrid Cloud Private Cloud No Plans Two Years Next Year Today Wisdom of Crowds Cloud Business Intelligence Market Study - Copyright 2013 Dresner Advisory Services, LLC 7

8 INTEREST REGARDLESS OF COMPANY SIZE 3.5 Importance of Cloud Business Intelligence by Organization Size ,000 1,001-2,000 2,001-5,000 5,001-10,000 10, Wisdom of Crowds Cloud Business Intelligence Market Study - Copyright 2013 Dresner Advisory Services, LLC 8

9 MARKET EXPECTS ENTERPRISE CAPABILITIES Cloud Business Intelligence User Feature Requirements Ad-hoc query Personalized dashboards End user "self service" Advanced visualization Data Integration/Data Quality tools/etl Production reporting Search Interface Data Discovery Data Mining and Advanced Algorithms In-memory support Pre-packaged vertical/functional Collaborative Support for Group- Ability to write to transactional Text Analytics Complex Event Processing (CEP) Social media Analysis (SocialBI) Cloud Business Intelligence User Architectural Requirements Relational database support Data Integration/Data Quality tools/etl Connectors to on-premise applications Automatic upgrades Multi-dimensional database support Data Virtualization Web Services API Multi-tenancy (single executable In-Memory data support Cloud application connections (e.g., Cloud Database Connectors (e.g., Big Data (e.g., Hadoop) access RESTful API Wisdom of Crowds Cloud Business Intelligence Market Study - Copyright 2013 Dresner Advisory Services, LLC 9

10 VENDORS BEHIND MARKET DEMAND Industry Support and Plans for Cloud Business Intelligence Architectural Features Relational database support Multi-tenancy (single executable supporting multiple customers) Multi-dimensional database support Connectors to on-premise applications and data (e.g., ERP, CRM) Data Virtualization Automatic upgrades Available Today 12 Months 24 Months No Plans RESTful/Web Services API Cloud application connections (e.g., Salesforce, Netsuite) Cloud Database Connectors (e.g., database.com, Redshift, SimpleDB, CloudSQL) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%100% Wisdom of Crowds Cloud Business Intelligence Market Study - Copyright 2013 Dresner Advisory Services, LLC 10

11 PERCEIVED LIMITATIONS Wisdom of Crowds Cloud Business Intelligence Market Study - Copyright 2013 Dresner Advisory Services, LLC 11

12 SECURITY REMAINS MAJOR OBSTACLE Business Intelligence Industry Support and Plans for Cloud Security SAS 70 AICPA Auditing Standard (now SSAE 16) ISO (Specification for Information Security Management System) HIPAA (The Health Insurance Portability and Accountability Act) PCI DSS (Payment Card Industry Data Security Standard) Available Today 12 Months 24 Months No Plans FISMA (Federal Information Security Management Act ) FIPS (Federal Information Processing Standard) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%100% Wisdom of Crowds Cloud Business Intelligence Market Study - Copyright 2013 Dresner Advisory Services, LLC 12

13 CLOUD BI REAL WORLD VIEWS 13

14 If you were to select a BI solution for a new environment today, which would you be most likely to select? No preference 32% Cloud BI 54% On-premise 14% COMPARING CLOUD AND ON-PREMISE BI: A SURVEY OF BUSINESS INTELLIGENCE USERS Dimensional Research

15 In general, how satisfied are you with your current BI solution? In general, how satisfied are you with your current BI solution? All 17% 38% 31% 12% 3% Traditional on-premise 14% 37% 31% 14% 3% Very Satisfied Satisfied Neutral Open source 11% 39% 43% 4% 4% Dissatisfied Very Dissatisfied Cloud 35% 45% 19% 0% 0% 20% 40% 60% 80% 100% COMPARING CLOUD AND ON-PREMISE BI: A SURVEY OF BUSINESS INTELLIGENCE USERS Dimensional Research

16 In your experience which of the following types of BU solutions In your had experience, a faster initial which implementation of the following types of BI solutions had a faster initial implementation? No difference 13% On-premise 4% Cloud BI 83% COMPARING CLOUD AND ON-PREMISE BI: A SURVEY OF BUSINESS INTELLIGENCE USERS Dimensional Research

17 Did your initial BI implementation have any cost overruns or unexpected costs? All 45% 56% Traditional on-premise 46% 54% Yes Open source 63% 37% No Cloud 32% 68% 0% 20% 40% 60% 80% 100% COMPARING CLOUD AND ON-PREMISE BI: A SURVEY OF BUSINESS INTELLIGENCE USERS Dimensional Research

18 Which of the following types of BI solutions are easier to use for business users Which of the following types of BI solutions are easier to use for business No difference 30% On-premise 11% Cloud BI 59% COMPARING CLOUD AND ON-PREMISE BI: A SURVEY OF BUSINESS INTELLIGENCE USERS Dimensional Research

19 In your experience, which type of BI solution enables better decision-making? Cloud BI 27% No difference 68% On-premise 5% COMPARING CLOUD AND ON-PREMISE BI: A SURVEY OF BUSINESS INTELLIGENCE USERS Dimensional Research

20 VISUALIZATION, DATA DISCOVERY, AND SELF- SERVICE 20

21 SELF-SERVICE BI Data Self Service Use Case Users A few application tables Single spreadsheets Application reports 20% Data Visualize data relationships Data Scientist Data Analyst Business Self Service Enterprise applications Un-structured data Disparate flat files 80% Data Give data analytic and historical structure Give data business context Visualize business trends Make operational decisions Knowledge Worker Operations Manager Executive Determine cause/effect Reporting Manager Disseminate insights TIME 21

22 BENEFITS AND DRAWBACKS Data Self Service Benefits Independence: organize and analyze data in personal perspective Business Self Service Benefits Single source of truth Powerful analytics Accurate decisions Organizational alignment Data governance Drawbacks Business relevance Accuracy: non-validated data Lacks powerful analytics (historical context / multiple disparate sources) Data anarchy / analytic silos Drawbacks Requires more sophisticated skills 22

23 BEST TOOLS Enable both Data Self-Service and Business Self-Service Power of business self-service at same speed as data self service Provide needed capability for different situations Meet needs of various different users / job roles in organization Single source of truth across the organization Ensure one-off analysis and production analysis decisions are in sync 23

24 BROAD MARKET DEMAND FOR CLOUD BI Key Drivers Overall cloud adoption Budget to business user Early adopter success Desire for faster decisions, rapid iteration analytics Ceiling of data discovery / visualization Key Impediments Vendors lack enterprise capabilities Perceptions abound for cloud security and control 24

25 ENTERPRISE CALIBER BI BORN IN THE CLOUD 25

26 A REAL NEED Because nobody likes to wait. 26

27 A REAL SCM ISSUE What do I Ship? When? To Whom? And I need to know NOW! There was no single version of the truth. We couldn t trust the data, and it just took forever. Fred Tiso, Group Director, Hardware Operations 27

28 COMPLEXITY Business need (we automated it) Technology 215 data sources: multiple applications, business processes that crossed applications Analysis across changing hierarchies: customers, regions, suppliers Run complex calculations across entire supply chain and provide instant results to end-users Add business meaning to cryptic data from 120+ suppliers, and join it with data from internal sources Time: ship date, order date, promise date, fulfillment date, etc joined to optimize delivery and inventory Real-time decision making across complex multidimensional supply chain Maintained by business analyst - part time With new data sources every week Multi-data source joins, conforming dimensions, composite keys Slowly changing dimensions Custom measures, custom attributes, scripted sources, function shipping Semantic Layer, Logical SQL Complex SQL, Multi-Pass SQL Interactive real-time dashboards Data model automation, automated warehousing, automated data loading 28

29 WORLD CLASS SCM via data model automation 29

30 ANSWERS. REAL FAST. Power 215 data sources 300 users 170 active dashboards Agility 1 business analyst managing complete solution 5 New data sources every week 1 Data warehouse / ETL / logical layer Speed 30 days for full deployment 12 minutes between each new Supply Chain Decisions 1 second dashboard response time 30

31 REAL RESULTS Increased inventory turns by 5X Days of supply reduced by 35% On-time shipments > 99% We tried every BI tool under the sun, but they didn t work for a variety of reasons Then we found Birst and knew it was the real deal. Fred Tiso, VP, Worldwide Operations 31

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