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Modern Data Management for Federal Modernization

  1. Modern Data Management for Federal Modernization ATARC Webinar Ravi Shankar, Sr. Vice President and CMO Denodo
  2. Speakers Ravi Shankar Senior VP & CMO, Denodo
  3. 3 The Leader in Data Virtualization Denodo DENODO OFFICES, CUSTOMERS, PARTNERS HQ - Palo Alto, CA. Global presence throughout North America, EMEA, APAC, and Latin America. LEADERSHIP ▪ Longest continuous focus on data virtualization – since 1999 ▪ Leader in Forrester 2018 Wave – Big Data Fabric, Leader in Forrester 2018 Wave - Data Virtualization ▪ Challenger – Gartner Data Integration MQ 2019, Highest Growth - Top 10 Data Integration Vendors ▪ Winner of numerous awards CUSTOMERS ~700 customers, including many F500 and G2000 companies across every major industry have gained significant business agility and ROI. FINANCIALS Backed by $4B+ private equity firm. 60+% annual growth; Profitable.
  4. 4 Architectural Challenges that Limit Data Use and Sharing ETL Inventory System (MS SQL Server) Product Catalog (Web Service -SOAP) BI / Reporting JDBC, ODBC, ADO .NET Web / Mobile WS – REST JSON, XML, HTML, RSSLog files (.txt/.log files) CRM (MySQL) Billing System (Web Service - Rest) Portals JSR168 / 286, MS Web Parts SOA, Middleware, Enterprise Apps WS – SOAP Java API Customer Voice (Internet, Unstruc)Mainframe (Batch Jobs) Big Data (Hadoop) Cloud Storage (JSON) Cloud Data (JSON) IT Focuses on Data Collection, Data Storage, Data Movement & Synchronization Data Consumers Focus on Data Usage, Analysis & Visualization No One Focused on Data Delivery – So create 100’s to 1K’s of brittle direct connections and replicate large volumes of data
  5. 5 Data Management Challenges • Need for timely inter-agency data sharing  Significant increase in restrictions & complexity of requirements in data sharing → agency struggles to deliver in a mely fashion • Increased risk from regulations, compliance, data privacy and security  Exponential increase in regulations effecting data across geographies, departments and industries • Ensure operational continuity amidst technology evolution  Migration of legacy systems to cloud, modernization of data and applications; ability to easily adopt new technologies like AI/Machine Learning
  6. 6 Objectives for Modern Data-Driven Agency  Single entry-point to explore and query ALL data • Users don’t want to waste time searching across different data sources • IT doesn’t want their users having access to all their production systems  Reduce / eliminate the roadblock for data sharing • Users don’t want to have to learn to code (SQL, Python, Java, etc) • They want to use the tools they’re most comfortable with  Implement security & governance across multiple systems • Leadership wants to reduce the amount of data that’s copied across the org • Minimize the risk of a data breach & avoid creating multiple versions of truth
  7. 7 A Modern Approach to Data Management 7 Abstracts access to disparate data sources Acts as a single repository (virtual) Makes data available in real-time to consumers DATA ABSTRACTION LAYER “Enterprise architects are finding that traditional data architectures are failing to meet new business requirements, especially around data integration for streaming analytics and real-time analytics.” The Forrester Wave: Enterprise Data Virtualization, Jan 12, 2018
  8. Business Need Solution Benefits A Defence Agency Enables Multi-Site Secure Data Sharing Case Study • Eight sites are involved, each independently managed and operated. • Large number of dependent applications, operating on highly secure networks. • Data sharing typically involved replicating data from facility to facility. • Person-to-person exchanges via email and phone required to stay in sync. • Ability to securely share data in real time between the sites without replication of data. • Ability to maintain consistency in describing data between key business entities. • Ability to easily consume several types of data, and expose data as a “service.” • Implemented Denodo data virtualization as a “Single Source for Data.” • Compliments existing data warehouse strategies. • Data stored in multiple systems – Oracle, SQL Server, MS Access. • Different types of data shared – Word and Excel documents, Widgets (SharePoint, Portlets). • Data exposed through web services (SOAP, REST), JDBC / ODBC. • Data consumed as XML, web services. 8 The agency is responsible for safeguarding national security through the military application of nuclear science.
  9. 9 Architecture: Multi-Site Secure Data Sharing
  10. What is Data Virtualization?
  11. 11 Data Virtualization: Unified Data Integration and Delivery • Data Abstraction: decoupling applications/data usage from data sources • Data Integration without replication or relocation of physical data • Easy Access to Any Data, high performant and real-time/ right- time • Data Catalog for self-service data services and easy discovery • Unified metadata, security & governance across all data assets • Data Delivery in any format with intelligent query optimization that leverages new and existing physical data platforms A logical data layer – a “data fabric” – that provides high-performant, real-time, and secure access to integrated business views of disparate data across the enterprise
  12. 12 Gartner’s Logical Data Warehouse Architecture
  13. 13 Gartner Hype Cycle: DV and LDW are Mature Technologies “Data Virtualization and Logical Data Warehouse have less than 2 years to reach Plateau of Productivity”
  14. 14 “Data Virtualization” is the 3rd Most Used Technology within an Organization Which Information Tech is Your Org Currently Using?
  15. How Data Virtualization Works?
  16. 16 Consume in business applications Combine related data into views 2 3 DATA CONSUMERS Enterprise Applications, Reporting, BI, Portals, ESB, Mobile, Web, Users, IoT/Streaming Data Connect to disparate data sources 1 DISPARATE DATA SOURCES Databases & Warehouses, Cloud/Saas Applications, Big Data, NoSQL, Web, XML, Excel, PDF, Word... Less StructuredMore Structured SQL APIs – REST, ODATA, GraphQL XML over SOAP Web/ Data Services Dedicated connectors JDBC ODBC APIs Read & Write DATA VIRTUALIZATION DATA CONSUMERSAnalytical Operational CONNECT COMBINE CONSUME Share, Deliver, Publish, Govern, Collaborate Discover, Transform, Prepare, Improve Quality, Integrate Normalized views of disparate data Dynamic Query Optimization Cache MPP Acceleration Machine Learning Data Services Data Governance Data Catalog Centralized Security
  17. 17 Big Data Queries Faster with Denodo Platform Performance comparison of 5 different queries 1. Data Virtualization delivers better performance without need to replicate data into Hadoop. 2. Data Virtualization leverages Data Source Architectures for what they are good at. Impala Hadoop- only Runtime (s) Denodo Runtime w/ Query Opt (s) Denodo Runtime w/ Cache (s) Data Volumes Query 1 199 120 68 Queries 1,2,3,5 • Exadata Row Count: ~5M • Impala Row Count: ~500k Query 4 • Exadata Row Count: ~5M • Impala Row Count: ~2M Query 2 187 96 88 Query 3 120 212 115 Query 4 timeout 328 69 Query 5 46 91 56
  18. 18 Cloud Logical Data Warehouse: Multi-location Architecture Amazon RDS, AuroraUS East Availability Zone EMEA Availability Zone On-prem data center
  19. Who uses Data Virtualization?
  20. Business Need Solution Benefits Agency Accelerates Data Warehouse Modernization and Transition to Data Lake Case Study • Wanted to reduce their Oracle footprint & spend through DW modernization and migrating some of their data to Hadoop • Re-write all 1000+ reports that were in PL-SQL • Convergence goal to migrate and merge data centers • Migrate off of IBM-hosted Data Center and merge with with AESIP • Reduced costs for leveraging Hadoop and convergence of data centers • HW/SW savings of $4+M per year • Easier to embrace new cloud platforms and data sources • 97% improvement in time to build API • Enabled end-users to develop reports faster and easier • Faster response to user requests for data • DV provided as a logical data layer • Ability to migrate data to other platforms without impacting applications • DV becomes single source for data • One place to go and get any data • Results presented in a useable format • Can access & view results from any tool / data source. 20 Agency develops and maintains state-of-the-art supportability analysis and Life Cycle Logistics decision support software tools to assist acquisition Program and Product Support Managers.
  21. Business Need Solution Benefits Agency Enables Asset Tracking for Non-National Aerospace Systems Case Study • Connect to several source systems to bring IT application inventory data, IT project data, and the system which tracks what software is running on each server together to form a set of dashboards for IT executive team • Users have one place to go for data • Ability to view all asset data for the very first time • Implemented Denodo as a single source for data • Deployment done in 2 weeks by 2 people (vs. a project that was projected to take over one year with a staff of 20 people) • Reduced IT costs by eliminating duplicate applications 21 Agency is a component of the Department of Transportation. It is tasked with providing the safest, most efficient aerospace system in the world.
  22. Try Data Virtualization
  23. 23 • 14 Day Free Trial • Different buying options – 2, 5, and unlimited data sources • Test Drive Denodo on the cloud – AWS, Azure, GCP Get Started with Denodo on AWS GovCloud (US) Today!