Welcome to The Future of Analytics In Action IBM Corporation

Transcription

1 Welcome to The Future of Analytics In Action

2 Goals for Today Share the cloud-based data management and analytics technologies that are enabling rapid development of new mobile applications Discuss examples of how these technologies are being applied to transform a diverse set of industries Hear from you about your most pressing challenges to harness the data you have to provide additional value for your customers 2

3 Today s Agenda 8:30 am to 9:00 am Registration and Continental Breakfast 9:00 am to 10:00 am The Future of Analytics in Action: The Art of the Possible 10:00 am to 10:30 am Demonstration 10:30 am to 10:45 am Break 10:45 to 11:15 am Real World Insights: Comdata s Journey 11:15 to 11:45 am Open Q&A 11:45 am to 12:00 pm Wrap-Up 12:00 pm to 1:00 pm Lunch and Networking 3

4 The Future of Analytics In Action: The Art of the Possible

5 Why the Journey to Cloud-based Analytics? FASTER INNOVATION BETTER IT ECONOMICS LOWER RISK OF FAILURE Instant provisioning saves weeks of data center setup Pay as you go with no big up-front capital investments Fully managed 24x7 so you can focus on new development 5

6 The Future of Analytics From Our DBaaS Offerings Transactional DBaaS Analytic DBaaS Cloudant SQL DB dashdb BigInsights on Cloud NoSQL DBaaS Relational DBaaS Relational Data Mart Enterprise Hadoop 6

7 To our Business Analytics and Intelligence Offerings Predictive Analytics n n n SPSS Data Collection SPSS Modeler Gold Social Media Analytics Risk n n n n n n Algo Managed Services Algo Risk Content Algo Risk Reports Algo Risk Service Algo Pension Monitoring IBM Open Pages GRC Watson n n Watson Analytics Watson Curator Content Management n Business Intelligence n Navigator Cognos Business Intelligence Performance Management n n n n n n Cognos TM1 Cognos Concert Cognos Disclosure Management Cognos Quota Management Cognos Territory Management Cognos Incentive Management Compensation 7

8 IBM can help your organization deliver new insights at every level, and in every department, in your organization. Optmize staffing mix, reduce employee turnover Have real time visibility into stock levels Reduce churn by knowing what the cusotmers are saying Human Resources Operations Product Development Work on scenarios to align development resources Customer Service IT 8 Sales Access key customer information in the office and on the road Marketing Combine personal and corporate data to create fresh insights Provide discovery and planning tools to reduce errorprone spreadsheet work Finance Drive growth and profit through resource alllocation Manage rolling comply with confidence expenses

9 IBM voted #1 cloud provider by enterprise users Who would you choose as your cloud provider? Amazon Web Services Microsoft IBM Based on an April Research survey of more than 2,000 enterprise cloud users - commissioned by Microsoft 9

10 IBM s Latest Cloud Analytics Offerings and How They re Changing Analytics for our Clients Today. 10

11 IBM Cloudant 11

12 IBM Cloudant NoSQL Operational Data Store Innovator of Database as a Service (DBaaS) JSON document database IBM Cloudant For apps that need: - Elastic scalability - High availability - Data model flexibility - Data mobility - Text search - Geospatial Available as: - Fully managed DBaaS - On-premises private cloud - Hybrid architecture Build More. Grow More. Sleep More. 12

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14 The Future of Cloud Based Analytics: A foundation with dashdb Fully managed data warehouse in the cloud In-memory acceleration capabilities with columnar technology, advanced compression, and buffer pool technology In-database predictive analytics & R-support Integrated with Cloudant for analytics on JSON data from web & mobile apps True Load & Go approach no need to predefine indexes Built-in Netezza analytic algorithms BLU! Acceleration! Netezza! In-Database Analytics! Coming in 2Q! Enhanced Netezza Compatibility Oracle compatibility mode MPP Cloudant Database! as a Service! 14

15 IBM BigInsights on Cloud 15

16 IBM BigInsights Cloud Enterprise Hadoop as a Service Big Data easier, faster, richer Analyze petabytes of any kind of data on elastic compute clusters Easy to adopt Provisioned, hosted, scaled for you Native Hadoop enriched with: Faster performance ~4x faster than open source Hadoop Visualization tools Built-in R, streaming & text analytics Data protection & governance Easy to integrate Connect common 3 rd party BI tools Enterprise Capabilities Open source IBM BigInsights Cloud Visualization & Exploration Development Tools Advanced Engines Connectors Workload Optimization Administration & Security Open source Hadoop components 16

17 Watson Analytics 17

18 IBM Watson Analytics for smarter data discovery 100 s of new ques3ons asked each day through explora3on and discovery 10 s of insigh:ul discoveries presented to, and evaluated by decision makers 1 change, improves alignment, opera3ons and repor3ng; governed and scalable Watson Analy3cs Analy3c pla:orms and database sources Business user led analy3cs Advanced user and IT managed analy3cs 18

19 Watson Analytics Single Interface Explore > Predict > Assemble Quick start intuitive interface Guided discovery & visualization Key business driver insights Easy data upload and search capabilities Natural language dialogue Dashboard and storytelling authoring 19

20 IBM Cloud-based analytics summary 100s of Paying Customers 50,000+ Users Global Operations 300% Growth Y2Y 300+ CDS Team Members 20

21 Use cases and customer examples 21

22 Use Case: Cloud Analytics for Web & Mobile Build an app and analyze usage to: - Understand user behavior - Increase monetization Millions of users transact with Cloudant via REST Data Center 1 (Active DR) Continuous, filtered replication & sync HTTPS Cloudant Sync (ios & Android) HTTPS Off-line mobile data access enabled by Cloudant Sync Continuous, filtered replication & sync Perform analytics with dashdb - Data is continuously synched with Cloudant - Accessed by BI Tools such as Watson Analytics via Dataworks HTTPS Continuous sync dashdb data mart Dataworks Data Center 2 (Active DR) BI Tool User 22

23 Payment Processor leverages the advanced geospatial capabilities of Cloudant to build a new mobile application 23 The combination of Cloudant s advanced geospatial capabilities, security, and managed service give Comdata a competitive advantage in terms of the experience they can deliver to their end users IBM Internal Use Only

24 Use Case: Comdata Company Background - Payment processor and issuer of fleet fuel cards headquartered in Tennessee. Need - A mobile app that delivers a better experience for end users of Comdata s payment processing system. Success Criteria - Show locations of vendors that use Comdata s payment processing, enable offline usage, and optimize routes. - Complete within 20 months 20 months 24 Solution & Results - A new mobile application launched in 9 months! - Advanced geospatial capabilities give Comdata a competitive advantage - Cloudant s managed service means Comdata can keep overhead costs down - Comdata avoids the costs, overhead, or latencies of ETL by with the schema flexibility Cloudant s JSON document store provides 9months

25 Use Case: Comdata - Reference Architecture Mobile Devices MobileFirst on Softlayer Local Storage Cloudant MobileFirst adapter User profiles, preferences, point of interest, etc. Geolocation information originally stored in DB2 Comdata Firewall Relational Database 25

26 Use Case: Cloud Analytics for Agility How quickly can you create a 1TB data mart? - Average Oracle & Teradata data marts take >50 days to implement (ITG) Web & Mobile users What are you spending on QlikView per year? - Cloud faster, cheaper? Equip users with dashdb and Big Insights for modern, agile analytics SQL DB Aggregations Big Insights on the Cloud ODBC dashdb data mart ODBC BI Tool Users 26

27 A Large Investment Research & Management Firm needed a persistent data store to maintain and access financial analytical reports 27 Cloudant s schema-less architecture and horizontal scalability enables their users users to have real-time access to reports and analytics generated by IBM PureData for Analytics IBM Internal Use Only

28 Use Case: Investment Research & Management Firm Company Background - Global Investment & financial services research firm Need - Provide real-time access to data for a new system of engagement application for accessing and visualizing reports from Netezza through a custom API Success Criteria - Support for high volume of user concurrency something a warehouse environment like Netezza cannot provide - Integration with other IBM products like Netezza Solution & Results - Schema-less architecture enables the ability to store the data without needing a schema definition prior to inserting the data from Netezza. - Does not require time consuming schema changes when different data must be captured and processed - With Cloudant, the firm is transforming how their users access data 28

29 Use Case: Investment Research & Management Firm The architecture diagram of the Transient Query Result Storage (TQRS) use-case is shown below. The process and data flow are as follows: 1. An end user requests a dataset to be visualized by the firm s service. 2. The request is processed through an API which queries a Netezza data warehouse for the requested data. API 3. Netezza returns the requested dataset back to the API. 4. The API internally prepares the data for visualization and storage by converting it into JSON format. A small subset of the data will be sent to the calling application for visualization while the full dataset will be persisted into Cloudant. 5. The initial requesting application can now query, page, sort etc against the data in Cloudant until they are finished. 29

30 An Insurance Company uses Cloudant Local to create a persistent data store to manage customer policy information. 30 Having a need to have real-time visibility to customer data from different Systems of Record, the Insurance Company values Cloudant s ability to manage data from different systems and navigate the data with embedded search capabilities. IBM Internal Use Only

31 Use Case: Insurance Company Company Background - Global insurance company with annual revenues of over $40B and locations in the US, Europe, Latin America, China, and more Need - Improve customer experience for roughly 40 million customers by enabling the ability to efficiently search all data such as: personal information, policies, claims, etc. Success Criteria - To manage and search data from different Systems of Records without having to design a web app with a schema-first mentality - A solution that can be managed on-premises for sensitive customer information but still have the ability to move to the Cloud in the future Cloudant Managed or Local deployment Solution & Results JSON JSON JSON - Implemented Cloudant Local on-premises and then will move some applications to a public cloud deployment Auto Policy Auto Policy Auto Policy - Provided the ability to manage all the data in one location while enabling the full-text search capabilities Previously, the company struggled using SOLR with their existing solutions. 31

32 Use Case: Insurance Company Architecture Details 3: Develop apps leveraging Cloudant's API & enable systems of engagement to operate at webscale 2: Push 360 o data to Cloudant for mobile workers Cloudant Managed or Local deployment 1: Cloudant JSON data sent to Watson Explorer to index Watson Explorer 32 JSON Auto Policy JSON Home Policy JSON Billing Data CRM HTML RDMS FILE SHARES SOCIAL SHAREPOINT

33 Use Case: Insurance Company Deeper Look TIME SENSITIVE ANALYTICS PROJECT: Seasoned analytics and warehouse customer, but looking at new analytics project that must get off the ground quickly. Time to value, speed, simplicity, reduced risk of project failure are all important. Data Warehouse & Analytics Service! Data warehousing and analytics in the cloud! Cloud agility and flexibility! Analytics for cloud data, data marts, and development & test environments! 33

34 A Pharmaceutical Distributor creates an analytics dashboard with IBM Cloud-based analytics 34 IBM Internal Use Only

35 Use Case: Pharmaceutical Distributor Company Background - A globally distributed Fortune 500 Pharmaceutical Distributor Need - After acquiring another organization they needed to create a supplier spend analytics dashboard for synergy capture - Provide enterprise wide visibility to the global procurement team to facilitate negotiations with suppliers and track alignment on terms - Deliver the project in 10 weeks Success Criteria - Key focus areas: Cost savings with vendors, Compliance with suppliers, Identify growth trends - Time to value Solution & Results - DashDB + Information Server on Softlayer allowed us provide a cloud warehouse and hosted data integration tool - The IBM team delivered the solution in weeks and exceeded customers expectations. 35

36 Use Case: Pharmaceutical Distributor Architecture Details Pharma UK branch Netezza Rancho Cordova, USA 1 1 Infinium/ MBA Montreal, Canada 1 SAP Stuttgart, Germany 6 Softlayer Dallas Private Network 2, 3 36 Information Server 4 Tableau Server Softlayer Dallas Public Cloud 5 1. Connect to company 2. Extract from sources 3. Transform into target model 4. Load into warehouse 5. Analyze 6. Report & visualize

37 Use Case: Pharmaceutical Distributor Deeper Look New data warehouse environment. - Customer does not have an existing analytics / warehouse solution. - This is often coupled with lack of skills/resources, preference to opex environments, needs something quickly, does not have 100+TB environment. Extend / Modernize! Extend on-premises data warehouse environments to the cloud! Flexible, cost-effective growth! Hybrid cloud models support ground to cloud! 37

38 A Food Distributor had been using Oracle but required better insight into streamlining sales operations through their various channels/businesses 38 IBM Internal Use Only

39 Use Case: Food Distributor Company Background - An international food distributor with zero analytics or insight around financial data from different areas of the business Need - Required better insight into streamlining sales operations through their various channels (consumer, wholesale, pet food, retail)] Success Criteria - Traditionally, an Oracle Shop, but the marketing department brought in and required integration with Tableau - Someone to perform rapid provisioning of the data warehouse on the cloud without requiring any DBA expertise Solution & Results - They were able to access the data seamlessly using Tableau. - Without a DBA, they were able to load data into the dashdb data warehouse and used Watson Analytics in along with dashdb to perform even deeper analytics 39

40 Use Case: Food Distributor Architecture Details Softlayer Dallas Public Cloud The company s team created their own scripts to load the data Oracle database environment Arkansas datacenter Financial data 40

41 Use Case: Food Distributor Deeper Look COMPLETE CLOUD BASED ANALYTICS - New analytics project that leverages our offerings, Cloudant, dashdb, and SaaS based Analytics through Cognos. Cloudant Analytics! Easy synchronization of JSON to structured data! Allows analytics via standard BI tools! In-database predictive algorithms allow greater insight for Cloudant users than ever before! Data Warehouse & Analytics Service! Data warehousing and analytics in the cloud! Cloud agility and flexibility! Analytics for cloud data, data marts, and development & test environments! 41

42 A Car Manufacturer requires a data management or analytic solution to understand campaign effectiveness. 42 IBM Internal Use Only

43 Use Case: Car Manufacturer Company Background - A multinational car manufacturer is equipping their 2015 and later models with an "interactive" infotainment system. Need - A data management or analytic solution to understand campaign effectiveness. Success Criteria - Take unstructured data, automatically format it, and report against it in the cloud, allowing the company s marketing team & merchants to segment customers and measure campaign effectiveness. 43 Solution & Results - Provisioned a prototype environment of dashdb with Cloudant in 24 hours illustrating the speed and agility possible - Flexibility and power of the IBM portfolio was critical for the project s success - The car manufacturer is getting a lot of value and analytics from their infotainment systems.

44 Use Case: Car Manufacturer Architecture Details Vehicle Data - Bulk load of 6-8 million accounts, 28 millions cars (~1TB of data) - Deltas continued to be load for user/vehicle data Other Data Sources IBM Datastage - Softlayer Dallas - Data movement into SFDC and into dashdb JSON data to relational Cloudant Schema Discovery Protocol 44 IBM Cloudant - Softlayer Dallas - 3 node production cluster - 3 node dev cluster IBM dashdb - Softlayer Dallas - 4 TB production system - 4 TB dev system

45 Questions? 45

46 Demonstration

47 Let s Take a Break

48 Real World Insights: Comdata s Journey

49 Driving Smarter Fuel Choices 49

50 Questions? 50

51 Learn More 51