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Powering self-service discovery with Hadoop and Data Virtualization


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Vizient delivers smart data-driven resources and insights from benchmarking and predictive analytics to cost-savings for their members. The firm employs a modern data architecture utilizing Hadoop with Data Virtualization to power their data discovery and analytics initiatives.

Discover Vizient’s success in:

· Helping members apply data and insights in new ways to achieve sustainable results
· Integrate Member Spend and Supplier Sales data from all Vizient organizations to identify opportunities for increasing contract utilization
· Enable Single source-of-truth and consistent view of data from distributed data assets

Don’t miss the opportunity to learn from this healthcare innovator!

Published in: Technology
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Powering self-service discovery with Hadoop and Data Virtualization

  1. 1. Powering Self-Service Discovery With Hadoop And Data Virtualization Chuck DeVries -- @daalis VP Technology Strategy and Enterprise Architecture
  2. 2. AGENDA - Who is Vizient - Modern Data Architecture - Self Service discovery examples - Recommendations - Q&A
  3. 3. 3 Who is Vizient? • Combination of VHA, University HealthSystem Consortium, Novation, MedAssets Spend and Clinical Resource Management and Sg2 • Experts with the purchasing power, insights and connections that accelerate performance for members
  4. 4. 4 Vizient serves thousands of health care organizations across the nation, from independent, community-based organizations to large, integrated systems including • Acute care hospitals • Academic medical centers • Non-acute community health care providers • Pediatric facilities Vizient members span the care continuum
  5. 5. 5 MEMBERSHIP BENEFITS • Harness powerful insights • Accelerate performance • Achieve scale and efficiency • Make innovative connections We measure our success by our members’ success. We fuel powerful connections that help members focus on what they do best: deliver exceptional, cost-effective care. Member-owned, member-driven • Be more agile • Build knowledge • Gain advocates on important policy issues
  6. 6. 6 Unmatched insight and expertise Top 14 Vizient serves the top 14 hospitals named to US News and World Report’s 2016-17 Best Hospitals Honor Roll ~$100B Vizient represents over $100 billion in annual purchasing volume — the largest in the industry. 200+ Vizient member hospitals have achieved remarkable improvements in quality and patient safety through our Hospital Engagement Network. More than 1/3 Vizient provides services to more than one-third of the nation’s hospitals. Information is inclusive of MedAssets Spend and Clinical Resource Management segment, including Sg2. We deliver brilliant, data-driven resources and insights — from benchmarking and predictive analytics to cost-savings — to where they’re needed most.
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  8. 8. Modern Data Architecture 8
  9. 9. Virtual warehouse Modern Data Architecture 9 Open Data Purchase Data Source [Raw] [Clean] Stage Hadoop Lake RDBMS Rules Process [Aggregated] Human Process Persist RDBMS ODS Data warehouse [Enriched] Serve Analytics Advisement Consulting
  10. 10. Business Intelligence Spectrum 10 Self service Enhanced Self service Analyst Desktop Workgroup Server Published Inside focus Small- Scale Outside focus Wide- Scale Discovered to Delivered
  11. 11. Examples of powering self service discovery 11
  12. 12. Unify disparate financial data marts relational sources Primary Use Case: Unify disparate accounting and finance data marts across various legacy organizations into a logical data warehouse Secondary Use Cases • Provide a unified source for key BI initiatives like the GPO Dashboard • Support reporting needs as legacy systems are migrated or replaced during integration of Vizient and L-MDAS (dbVision, etc.) • Provide a final resting place for archived legacy sources like Solomon, Epicor, etc. 12 VHA MedAssets UHC Unified balance sheet
  13. 13. Virtual Financial Data Mart Architectural Approach • Denodo was selected as the data platform in order to utilize the following features of the software: – Data Virtualization allows sources in various mediums and locations to be integrated without physically moving the data – Data Abstraction allows data to be represented consistently within the datamart while data sources are moved or replaced behind the scenes – Data Integration allows for a single seamless view to be created across a subject area (e.g. “Supplier Sales”) with varied data transformation rules for each data source within the subject area (PRS, dbVision) allowing a logical data warehouse to be created without the need to instantiate a physical on 13
  14. 14. Data Intake and Standardization Varied sources 14 Primary Use Case: Consolidate member data feeds and simplify member data submission experience Other Use Cases: • Support consistent internal data standards • Feed data to systems regardless of downstream tech stack • Metadata approach to security, rights of use • Ground for data governance and data mastering Architectural Approach • Data repository utilizes Hortonworks to persist input data as raw data that can be schematized for format and validation work. Paxata for Data Quality and data validation. Reuse overlapping datasets while allowing separate schematized views to be published as needed. Abstract data source from data use while preserving security and rights of use • Reporting components match vary by downstream product Goal of reducing onboarding time between 10% to 50%
  15. 15. Data Intake and Standardization Key Challenges • Successful consumption of many formats and business processes into shared delivery – Ensuring varied processes can be supported – Providing flexible mapping capabilities to support many formats • People change management – Be sure to manage how people experience the change as well as the technology of the change • Scalability/Configuration Management – Process and tool needs to support parallel development of this project and continued efforts to fold in other sources – Process guidelines are being authored to allow for multiple development efforts on the same datasets 15
  16. 16. Consolidated view of sales data Varied sources Primary Use Case: GPO Dashboard - Provide a consolidated view of supplier sales data across all customers of legacy Vizient & Med Assets organizations. Architectural Approach • Financial Datamart (on Denodo) for data source • Denodo TDE Exporter Tool for daily data extracts to Tableau: – Report Data – Report User Security • Tableau for report development and distribution 16 Over 400 active users across 6 departments with one story
  17. 17. Consolidated sales data view in virtual data mart Key Challenges • Balance between data timeliness and report performance – Tableau reports performed best utilizing the TDE format (cached/extracted dataset) as opposed to a live connection – This meant that the report caches required daily refreshes, and data extraction had to be appropriately tuned – Denodo features such as dataset statistics and indexing greatly contributed to this performance tuning • Provisioning user security at cell level – The requirement for some internal report users to be restricted to the members/customers to which they are assigned meant that a new report security approach was needed – Reliance on TDEs for report data necessitated the integration of security in the reporting layer – Tableau’s “data blending” feature allows user security to be specified within a separate dataset – This also supports reuse of the security view across logical data warehouse views 17
  18. 18. Integrate member spend and supplier sales Varied Primary Use Case: Contract Sales Analyzer Dashboard - Integrate Member Spend and Supplier Sales data from all Vizient organizations to identify opportunities for increasing contract utilization Other Use Cases: • Maintain consistency (Single Source Of Truth) with GPO dashboard regarding: – Supplier Sales Data – Dimension Data – User Security Architectural Approach • Data source utilizes Denodo to reuse overlapping datasets (sales, dimensions, security) while allowing separate virtualized views to be created for new datasets (member spend) which can be also be reused by future projects via a logical data warehouse • Reporting components match approach used by GPO Dashboard 18
  19. 19. Contract Sales Actualizer Dashboard Key Challenges • Successful integration of Exadata RDM as a data source for Denodo – Approach utilizes the strength of Exadata RDBMS for aggregating large quantities of data quickly – Denodo to integrate the data with similar legacy SQL Server data sources to create a comprehensive view of Vizient member spend • Scalability/Configuration Management – Advances were made to support parallel development of this project and continued efforts on GPO dashboard – Compartmentalization features within Denodo allow for code changes in each project to be version controlled and assessed for dependencies – Process guidelines are being authored to allow for multiple development efforts on the same datasets 19
  20. 20. Other examples Data Science comparatives – Determine groups analyze with various Machine Learning tools and publish via accessible sql Quick service virtual data marts to publish data via API or SQL to support consulting engagements Support for “test area” hack day data sets while maintaining security and confidentiality 20
  21. 21. Recommendations (AKA learn from my mistakes before your own) Mastering data is hard… publish trusted sources • One source to rule them all isn’t practical in a distributed architecture world... Use data services to make it “look like it’s together” (If it looks like it works... It works) • Don’t make your system complexity your users problem... Abstract complexity in layers Attaching and publishing isn’t point and click… you need to understand your use cases or your performance will suffer Don’t underestimate the people side of technology change... Usability and ease will win out (work will find a way) Hadoop is special but not that special... Hadoop is a source of data that has smarts, don’t treat it as if it’s just another SQL source but also don’t make differentiation your users problem 21
  22. 22. Our central focus is helping members apply data and insights in new ways to achieve sustainable results. Our success is ultimately defined by the success of our members in serving their patients and communities. Curt Nonomaque, President and CEO, Vizient
  23. 23. This information is proprietary and highly confidential. Any unauthorized dissemination, distribution or copying is strictly prohibited. Any violation of this prohibition may be subject to penalties and recourse under the law. Copyright 2016 Vizient, Inc. All rights reserved. 23 Contact Chuck DeVries at for more information.