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IBM Relay 2015: Open for Data
The document discusses the advantages of leveraging data analytics to drive business outcomes, emphasizing the need for sophisticated analytics across various data sources. It highlights IBM's comprehensive cloud data services portfolio, which aims to address the analytics challenges businesses face, including data preparation and access. Additionally, it outlines several use cases that illustrate how companies in different sectors utilize IBM's analytics solutions for improved efficiency and decision-making.
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IBM Relay 2015: Open for Data
- 1. text Presented by: Open forData Skyla Loomis Director, Cloudant Engineering
- 2. text Data is thenew basis of competitive advantage Leaders will leverage data to: Drive business outcomes Capture the time value of data Change the game by applying more sophisticated analytics across more disparate data sources in more parts of their organization by developing “speed of insight” and “speed of action” as core differentiators in their industry and profession by infusing analytics into everything employees touch.
- 3. text Imagine the possibilitiesof analyzing all available data Real-time traffic flow optimization Fraud & risk detection Understand and act on customer sentiment Accurate and timely threat detection Predict and act on intent to purchase Low-latency network analysis
- 4. text …but there areobstacles that keep companies from exploiting analytics for competitive advantage Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute for Business Value study. Copyright © Massachusetts Institute of Technology have a limited understanding of how to use analytics 38% Self-service analytics and expectations to drive better data- driven decisions are rising of the time is spent on data preparation 80% Making decisions rapidly is no longer a goal; it’s an imperative find it difficult to get data 24% Access to data sources is critical while maintaining governance standards
- 5. text Data Access Data Preparation Analysis Validation Collaboration Reporting DataScientists and Statisticians Business Users IT Business Analysts Even a simple analytics project has multiple steps and people
- 6. text Why make IBMyour cloud data standard Most Complete Portfolio • Champions of leading edge of technology • Deep ties to open source • Backed by IBM technology leadership • Fully managed 24 x 7 Integrated Experience • Seamless integrations • Unique product bundling • Provides cost efficiency • Reduces time to market • Comprehensive portfolio for end- to-end app development Deployment Flexibility • Industry leading support for hybrid deployments • No cloud lock-in • Pay-as-you-go • Secure infrastructure • Bare metal and virtualized performance MISSION To help people transform business & society by being the best place to build apps and gain new insights better and faster.
- 7. text We are addressingthe needs of new and traditional clients Web & Mobile Enterprise Demand for IBM Cloud Data Services growing by thousands of new developers per week 100s of Paying Customers 300% Growth Y2Y 50,000+ Users
- 8. text Understand your requirements •Data What kind of data are you managing, storing, transmitting or processing? Is any of your data highly regulated? What would happen if a loss occurred? Best suited for NoSQL, traditional RDMS, big data, cognitive, or a combination? Existing enterprise data, new data generated by application, or both? Where do you need your data stored? What are your scalability (data storage, concurrent user) requirements likely to grow to?
- 9. text Understand your requirements •Data What kind of data are you managing, storing, transmitting or processing? Is any of your data highly regulated? What would happen if a loss occurred? Best suited for NoSQL, traditional RDMS, big data, cognitive, or a combination? Existing enterprise data, new data generated by application, or both? Where do you need your data stored? What are your scalability (data storage, concurrent user) requirements likely to grow to? • Application What is your application maturity and pace of change? Primarily transactional or engagement-focused? Primarily web, mobile, both? Is this a new style or type of application? How much of your application platform do you already have in house for what you want to do? How important is availability?
- 10. text Understand your requirements •Data What kind of data are you managing, storing, transmitting or processing? Is any of your data highly regulated? What would happen if a loss occurred? Best suited for NoSQL, traditional RDMS, big data, cognitive, or a combination? Existing enterprise data, new data generated by application, or both? Where do you need your data stored? What are your scalability (data storage, concurrent user) requirements likely to grow to? • Application What is your application maturity and pace of change? Primarily transactional or engagement-focused? Primarily web, mobile, both? Is this a new style or type of application? How much of your application platform do you already have in house for what you want to do? How important is availability? • Company What is your team’s core competency? What do you want your team spending time on? Do you already own data centers? Do you have a global presence? Do you have strong operational experience and a devops culture? What’s your risk tolerance? How quickly does your team generally adopt new technology trends?
- 11. text CDS offers themost complete portfolio of data & analytics services on the planet
- 12. text With the mostcomplete set of open source services
- 13. text And aggressive investmentsvia acquisition • On July 23, IBM acquired privately-held Compose, based in San Mateo, CA • Compose extends IBM Cloud Data Services portfolio with 5 new open source DBaaS offerings • DBaaS makes it easier for developers to build and grow web and mobile apps • Acquisition further positions IBM Bluemix as *the platform* for data & analytics, with the broadest set of data services • Compose technology will accelerate the creation of future CDS offerings Acquisition Highlights IBM has acquired Compose, which provides MongoDB, Redis, Elasticsearch, PostgreSQL, and other open source databases as a service (DBaaS) for web and mobile applications
- 14. text More data centers,in more countries, than any other cloud provider SoftLayer AWS • “Bare-metal” and virtualized performance • Faster, more consistent so you can do more • Open, secure, and scalable • Secure, high-speed network • 40 data centers worldwide
- 15. text Varying levels ofservice & deployment options to meet unique users and data requirements Software • Select, purchase, provision and operate hardware & software • Complete control of every operating parameter Appliance • Expertly engineered hardware & software • Customer responsible for operation • Fixed configuration = less control Cloud Image • Expertly engineered cloud configurations • IaaS manages hardware • Customer has full control over software & operation Managed Service • IBM operates service and controls everything • IBM delivers on SLA • Customer concerns only with data control simplicity Customer Data Center (On-Premise) Cloud Data Center (Off Premise)
- 16. text Flexible deployment andpricing options enable users to maximize cost efficiency, control, and performance – Bringing technology and data to you and your users – Your data platform changes over time to • Optimize cost, compliance, performance – A data layer must adapt • No cloud lock in • Public cloud • Private cloud • Hybrid cloud – IBM cloud data services are fluid • Move or extend your data layer across different private or public cloud data centers • Without service interruption • Without re-coding SoftLayer US SoftLayer UK SoftLayer Canada Your Data Center
- 17. text More on afew of our IBM Cloud Data Service offerings Cloudant dashDB BigInsights on Cloud DB2 on Cloud Analytics for Apache Spark DataWorks Operational Data Store Analytic Data Warehouse Hadoop in the Cloud Hosted Database in the Cloud Fully managed Spark Hybrid Data Movement & Curation • Global data distribution • Massively scalable • Eventually consistent data model • Built for mobile, Systems of Engagement • SQL interface • MPP • ACID compliance • Columnar, in-memory performance • BLU augmented with NZ in-DB analytics • Bare metal performance • Build on reference architecture • BigInsights enterprise features • Power of DB2 • Fast Provisioning • Flexible pricing • No loss of DBA control • Built for Systems of Record • In-memory application framework for data processing and analysis • Built-in machine learning • Elastic scaling • Build on Spark • High Performance, Elastic compute, auto provisioned • Secure access to On- Prem data • Interactive shaping & batch execution
- 18. text Supporting Applications atWeb Scale Cloudant helps make your web and mobile applications more scalable and more available to users wherever they are. • Operational JSON NoSQL data store • RESTful CouchDB API • Advanced APIs • Replication & Sync • Incremental MapReduce • Geospatial • Lucene Full-text Search • Scalable, Highly Available Performance with cross-data center data distribution & fail over • Geo load balancing • Offline access to the data • Available as a fully managed cloud service and an on- premises software product – enabling hybrid deployments IBM Cloudant
- 19. text The combination ofCloudant’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 19
- 20. text A Large InvestmentResearch & Management Firm: needed a persistent data store to maintain and access financial analytical reports 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
- 21. text Use Case: InvestmentResearch & 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
- 22. text Supporting Applications atWeb Scale Fast, fully managed, cloud data warehouse that leverages integrated analytics to deliver answers as fast as you can think. dashDB’s unique built-in analytics, R predictive modeling and business intelligence tools free you to analyze your data to get precise insights, quicker. Built-in performance with in-memory technology Predictive modeling built into the database (linear regression, k-means clustering, Esri compatible, and more) Works with an ecosystem of apps and tools Integrated security and maintenance Scalable as your data sizes grow IBM dashDB 23
- 23. text 24 The Red 10is a data-driven marketing analytics firm in the UK. With dashDB, they are able to provide real-time analytics and updates to give an accurate view to the audiences With dashDB, they can provide 1) a live view of the UK&I markets, 2) new segmentation based on live contact views, 3) an instant view of all relevant information, and 4) the right message, at the right time, through the right medium. This enables growth for less and increased conversion across the sales funnel for their clients. Use Case
- 24. text The Red 10- Overview – Use case: The Red 10 is a data-driven marketing analytics company that works with 150 million items of data & 7 million records from over 1 million companies from over 1,000 sources. – Offerings: • DashDB for their data warehouse analytics platform. • Also actively looking to use Cloudant as a NoSQL database – Why dashDB? • Small analytics & data team – need to stay focused on their 1,000+ condition queries and driving value for their clients. Stay focused on providing the analytics, with IBM experts managing the environment • Provided fast time to value – customer was essentially sold after a month of working with our team • No capex budget – needed to leverage opex cloud economics 25
- 25. text Use Case: CloudAnalytics for Web & Mobile Build an app and analyze usage to: • Understand user behavior • Increase monetization Millions of users transact with Cloudant via REST Off-line mobile data access enabled by Cloudant Sync Perform analytics with dashDB • Data is continuously synched with Cloudant • Accessed by BI Tools such as Watson Analytics via Dataworks Data Center 2 (Active DR) Continuous, filtered replication & sync Continuous, filtered replication & sync Cloudant Sync (iOS & Android) dashDB data mart Continuous sync Dataworks BI Tool User HTTPS HTTPS HTTPS Data Center 1 (Active DR)
- 26. text Supporting Applications atWeb Scale Provision enterprise-scale, multi-node clusters on the cloud to meet your business needs. Access your provisioned clusters for simple database transactions, to augment your data warehouse, or to perform rich analytics. With BigInsights on Cloud, our clients can manage less and analyze more. For Production and POC deployments at scale in the cloud Delivers flexibility and efficiency with subscription pricing Scales to meet spikes in demand without on-premise infrastructure Drives enterprise-class, complex analytics on Big Data sets Available via the IBM Cloud Marketplace and Bluemix IBM BigInsights on Cloud 27
- 27. text A Pharmaceutical Company:embarks on treatment analytics with an IBM cloud-based solution
- 28. text Company Background: Aglobally distributed $10+ billion pharmaceutical company Need: • An analytics platform to execute against a time-sensitive project focused on the benefits of a pharmacological treatment of obesity • Analysis to be performed on Electronic Medical Records (EMR) data that the organization owns, but cannot fully analyze given system constraints. Success Criteria: • Apply big data technologies and analytical techniques without having to manage an analytical environment on-premises. • Gain the necessary insights regarding the relevance of pharmacological treatment of obesity, which would allow the organization to build an economic model for obesity treatments. Solution & Results: • The environment was provisioned and made available to the customer in less than 48 hours to begin executing against the project • An analysis to inform discussion about the relevance of pharmacological treatment of obesity, and to obtain costs estimates to build an economic model for obesity treatments. Use Case: Pharmaceutical Company
- 29. text Supporting Applications atWeb Scale Benefits include: • Convenience without the loss of control on cost effective infrastructure • 4 high performance hardware configurations & 2 database software tiers to match capability and affordability needs • Native encryption support configurable to ensure data remains secure in the cloud IBM DB2 on Cloud 30 Provides a DB2 RDBMS that is: • Provisioned via Bluemix • Hosted on IBM SoftLayer cloud platform virtual private nodes (not shared) • Administered by the customer DBA • Has an aggressive pricing model to take out competition (paid on a month-to-month basis via subscription model)
- 30. text Supporting Applications atWeb Scale What you get • Access to Spark’s next-generation performance and capabilities, including built-in machine learning and other libraries • Pay only for what you use • No lock-in – 100% standard Spark runs on any standard distribution • Elastic scaling – start with experimentation, extend to development and scale to production, all within the same environment • Quick start – service is immediately ready for analysis, skipping setup hurdles, hassles and time • Peace of mind – fully managed and secured, no DBAs or other admins necessary IBM Analytics for Apache Spark Spark is an open source in-memory application framework for distributed data processing and iterative analysis on massive data volumes
- 31. text Why make IBMyour cloud data standard Most Complete Portfolio • Champions of leading edge of technology • Deep ties to open source • Backed by IBM technology leadership • Fully managed 24 x 7 Integrated Experience • Seamless integrations • Unique product bundling • Provides cost efficiency • Reduces time to market • Comprehensive portfolio for end- to-end app development Deployment Flexibility • Industry leading support for hybrid deployments • No cloud lock-in • Pay-as-you-go • Secure infrastructure • Bare metal and virtualized performance MISSION To help people transform business & society by being the best place to build apps and gain new insights better and faster.
- 32. text © IBM Corporation33 IBMCloud Data Services is Open for Data
Editor's Notes
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- #5 Primary obstacles preventing widespread adoption of analytics Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute for Business Value study. Copyright © Massachusetts Institute of Technology Departmental experts and analysts are expected to drive better data-driven decisions, but lack the breadth of advanced skills needed for data management, building predictive models, and effectively communicating the correct conclusions. Making decisions rapidly is no longer a goal; it’s an imperative. Reducing the time to informed action requires a streamlined ability to draw compelling conclusions without reliance on too many people and the need to leverage multiple disparate tools. Self-service is increasingly becoming more important as business users are pressured and motivated to quickly find answers on their own. Self-service needs are increasing, but IT is concerned about maintaining corporate data governance standards. The expectation of today’s workforce is that they can access and analyze their data anytime, anywhere. And then getting insights to decision-makers quickly is critical to delivering fast, correct action.
- #6 Even a simple analytics project has multiple steps and people. Projects require multiple steps like accessing and obtaining data. Business units and individuals from IT and departmental analysts are needed to manage and prepare trusted and governed data sources. Providing this data to Analysts takes time and resources. Validation of this data is critical to avoid errors and poor decision making before the data is used by many to collaborate on the actual intent of the data itself before it is reported. If the data is wrong then the reporting will be wrong and decisions will be inadequate.
- #8 Developers of all types and sizes, in many industries are using IBM’s Cloud Data Services…for new mobile app development, for analytics and data warehouse modernization, and other applications. As a follow on to this meeting, we can see if we have specific customers that match your industry and or use case. Let’s look at why they’re choosing to build with IBM Cloud Data Services….
- #13 IBM cloud services aren’t solely based on IBM proprietary technology. Many of our offerings are built using open-source technologies like the ones listed here, among others. This allows us to innovate faster, and makes it easy for you to recruit technical talent; because many of these open source projects have large communities of developers from which you can hire. And for the developers you already employ, IBM’s leverage of open source technology helps you enrich their skillsets with the technologies they’re eager to learn. IBM also contributes back to open source projects. For example, we employ the largest number of Apache CouchDB project committers.
- #14 1. 5 new, immensely popular open source DBaaS offerings 2. Technology will make it possible to accelerate our roadmap – w, containerized… Further reinforces that Bluemix is where you go for data…
- #15 In order to meet your budgetary and service level agreement goals, cloud platform performance and availability it critically important. IBM’s cloud data services run on IBM SoftLayer’s “bare-metal” cloud platform. Benchmarks by IBM and other database companies have shown time and again that IBM SoftLayer is a better platform for data management workloads than virtualized cloud platforms like AWS and Azure. Faster throughput, lower latency, and more consistent performance. This saves you money; at say 5x better throughput, you only have to provision say 3 database server nodes instead of 15; or 6 instead of 30… Open, secure, and scalable Cloud infrastructure-as-a-service choices On-premises private cloud and systems Global cloud footprint Secure, high-speed network Expert services and tools 40 global cloud centers Secure integration to on-premises systems
- #17 CDS has on-prem versions of each of these offerings. One thing you can be sure of, is that your data layer will change over time. As data management performance, security, and regulatory requirements change, you’re likely to want to run data services on private, public, or hybrid cloud plaform configurations that change over time. IBM’s cloud services are built with this data layer flexibility and fluidity in mind. As your needs change, we can move your data layer components between or across any of the 40+ IBM SoftLayer data centers worldwide, or your private cloud platforms to accommodate your changing needs. Usually done without downtime, or re-coding. And with on-premise editions of all our cloud data services, you’re never locked into the cloud; you can move easily between on premise or cloud with IBM
- #18 IBM offers an extensive and highly differentiated set of cloud data services for handling a variety of workloads: Application development…especially good for mobile apps – Cloudant NoSQL operational data store Analytics services – of structured and unstructured data – dashDB Deep analytics on Hadoop – BigInsights on Cloud. Hosted Database in the Cloud – DB2 on Cloud All fully managed for you, integrated via the IBM Bluemix PaaS for ease of use and development, and running on IBM SoftLayer’s cloud with its bare-metal performance advantages. Let’s take a deeper look into the individual services.
- #19 Cloudant is IBM’s NoSQL operational data store on the cloud. We’re the innovator of the term “Database as a Service” (DBaaS). Cloudant’s JSON document database is perfect for applications that need the flexibility, scalability with a lot of advanced features inclusive of text search and geo spatial capabilities. And, it is fully managed for you. Cloudant helps make your web and mobile applications more scalable and more available to users wherever they are.
- #20 Comdata is an IBM client and a leader in payment solutions for the fleet management industry. Basically, they’re a credit card company. They issue the Fleet Management credit card that their customers’ truck drivers use to pay for gas and work-related expenses on the road. Comdata knew that mobile could make a major difference for their business, but they weren’t sure how. What they did know what this: Every day, fleet management companies worldwide spend about $85 million on fuel. And even though the fleet managers typically have pre-negotiated loyalty rates with many fuel chains, those rates are not advertised. In many cases, drivers don’t even have this information. As a result, nearly 54 percent of their customers’ drivers were paying more for gas than should. By delivering the right information to the drivers at the right place and time, Comdata could help its customers save up to $25K a month or $300k a year – potentially huge savings. To capitalize on the opportunity, Comdata did three things: They used mobile to envision a New Way to Work for its customers’ truck drivers. They imagined an intuitive, easy-to-use and always-on mobile app enabled with data from a myriad of sources – including their own Systems of Record, the MasterCard gas prices feed, local municipalities’ that held data on height and weight restrictions for bridges and overpasses, traffic bureaus and so on. With real-time access to this rich data, they knew that drivers could not only make better fuel purchase decisions but also optimize their routes to avoid traffic delays and construction and find the kind of amenities (e.g., truck stops with showers) that would make life on the road infinitely easier. With this vision in mind, Comdata worked with IBM Business Partner Point Source to bring the app to life, enabling a New Way to Engage with their customers’ drivers. Along the way, they interviewed actual truckers to create user journey maps. They solved the problem of how to quickly access and analyze massive amounts of data to reliably deliver the right insights to drivers at the right place and time by using IBM Cloudant to make complex geospatial map reduction queries across multiple systems running in IBM SoftLayer. And they used the IBM MobileFirst Platform to design an innovative app interface with a ‘1-click’ strategy that allows drivers to access the information quickly and easily, without creating unnecessary – and potentially disastrous -- distractions. With this new mobile-first solution, Comdata truly architected a New Way Forward for their business. In the past, Comdata was only able to analyze data after drivers' trips -- by uncovering insights from the Fleet Management card purchase data as well as known gas pricing data and data from gaming simulations designed to predict drivers' behavior. Now, they can now gather and analyze trip data in real time, saving their customers time and money and providing a much better experience for drivers, who can optimize their routes based on the amenities that matter most to them. Read the full Comdata case study (internal link): http://w3-01.ibm.com/sales/ssi/cgi-bin/ssialias?infotype=CR&subtype=NA&htmlfid=0CRDD-9R3SVS&appname=crmd http://www-03.ibm.com/software/businesscasestudies/us/en/corp?synkey=C048384M14201Z77
- #22 This is the sweet spot of our new Cloud Data Services platform – quickly delivering tons of data. We could easily integrate with their existing Netezza setup to make the most of their investment. The fact that these tools are cloud-based with no overhead, and can be used with current systems helped me change the conversation from a standard check-in to start selling. Now, this client has the Cloudant database up and running, and we are ready to broaden the conversation and start talking about using cloud-based data warehousing and analytics Company & Use Case Background Investment & financial services research firm Cloudant will be persistent datastore at the edge (pulling from multiple systems of records, starting with Netezza) to provide API & workload simplification. The company’s 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. Success Criteria Provide real-time access to data for a new system of engagement application for accessing and visualizing reports from Netezza through a custom API Support for high volume of user concurrency – something a warehouse environment like Netezza cannot provide Integration with other IBM products – like Netezza Solution & Results Cloudant’s schema-less architecture gives this firm the ability to store the data without needing a schema definition prior to inserting the data from Netezza, nor does it require a schema change when different data must be captured and processed With Cloudant, the firm is transforming how their users access data Detail on next slide
- #23 1. An end user requests a dataset to be visualized by a Customer Service. 2. The request is processed through a Customer API which queries Netezza (or any other data warehouse) for the requested data. 3. Netezza returns the requested dataset back to the Customer API. 4. The Customer 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.
- #24 dashDB is our Datawarehouse as a Service. It is a fully managed data warehouse on the cloud that leverages DB2 BLU and Netezza in-database analytics to help organizations get their insights very quickly without the need to provision any infrastructure.
- #25 The Red 10 is a marketing analytics firm based in the UK. They leverage dashDB to provide real-time analytics at the right time to the appropriate audiences.
- #26 We were able to reduce the queries from 1 day to 4 seconds with dashDB. Customer was sold after a month of working with the IBM team. They had to leverage the opex model and IBM was the perfect fit for their economics requirements.
- #28 Now, you can quickly provision multi-node Hadoop clusters on bare-metal hardware with our BigInsights on Cloud offering. It’s available via the IBM Cloud marketplace and Bluemix.
- #30 BigInsights on cloud comes pre-installed with BigR BigR allows parallelizing algorithms over the entire data set The APIs are similar to ones familiar to an R user Clients like R Studio can be used to send scripts to BigR to execute
- #32 Now, you can quickly provision multi-node Hadoop clusters on bare-metal hardware with our BigInsights on Cloud offering. It’s available via the IBM Cloud marketplace and Bluemix.
- #34 We’re all in the data business Data comes in many forms, and our platform speaks all of them. We are: Open source Open to how you want to run (public, private, hybrid) Open to where you want to run with 40+ data centers available world wide Open 24x7 so you can #sleepmore We are OPEN FOR DATA Thank you.