D wise overview

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Overview of d-Wise technologies, and their core competencies for building clinical systems and healthcare systems. technology expertise in SAS, entimo, Oracle solutions. Significant thought leadership on implementation of clinical data standards

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D wise overview

  1. 1. © d-Wise 2013 August 8, 2013 Page 1 August 8, 2013 Systems | Standards | Data | Process
  2. 2. © d-Wise 2013 August 8, 2013 Page 2 for Life Sciences & Healthcare • Systems Implementation • Systems Integration • Clinical Data Repositories • Metadata Repositories • Standards Implementation • Data Warehouses • Metadata Solutions • Business Intelligence • Data Analytics • Predictive Modeling
  3. 3. © d-Wise 2013 August 8, 2013 Page 3 Technology Founded in 2003 Privately Held Fortune 500 Customers Offices in US, UK
  4. 4. © d-Wise 2013 August 8, 2013 Page 4 Customized Technology Strategies Implementing Data Standards Integration of Clinical Systems Delivering SAS Solutions Aligning Technology and Process
  5. 5. © d-Wise 2013 August 8, 2013 Page 5 Domain Solution Technology SAS • Clinical data flow, from collection to submission • Clinical Data Standards • Clinical Systems landscape • Data Warehousing • Business Intelligence •Analytics and Reporting • Commercial Software • Open Source • N-Tier Architechture • Life Sciences Applications • Data Integration, Business Intelligence, Analytics • Validated SAS computing environment
  6. 6. © d-Wise 2013 August 8, 2013 Page 6  Unique combination of life sciences and technology experience to understand both your business process and technology challenges.  Experience with clinical data warehousing, programming, analytics and FDA submissions.  Extensive knowledge of CDISC, HL7 and other industry standards.  Experience planning, managing and delivering clinical trials.  Broad experience aligning strategic and tactical plans to help organizations address the challenges of technology adoption.
  7. 7. © d-Wise 2013 August 8, 2013 Page 7  Experience in data warehousing, analytic data marts, actuarial analysis, quality reporting, and physician profiling  Experience with all aspects of health insurance including claims, members, providers, be nefits, contracts, and rates  Management expertise in large- scale process improvement initiatives in the health insurance arena
  8. 8. © d-Wise 2013 August 8, 2013 Page 8  Have broad experience applying data warehousing domain expertise to build robust models for decision support. Our team can transform data warehousing from a contentious challenge to a value delivering asset.  Use a data-driven requirements gathering process comprehensively addressing the needs of the business users, IT, and enterprise architectures.  Use a technology agnostic approach that ensures the right solution for our client’s unique needs.  Have a deep expertise in data integration and ETL to build reusable modules.  Follow best practices definition to define platforms to help your data managers focus on the data rather than the tools.  Metadata driven data management approach streamlines interfaces and captures the right data about your data.  Define warehouse models for integrating disparate operational data sources for enterprise needs.
  9. 9. © d-Wise 2013 August 8, 2013 Page 9 d-Wise will help tackle your business challenges by…  Offering a unique combination of software development and industry knowledge  Providing the expertise in a broad range of technologies to find the optimal solution  Having a successful track record of building the right solution for your problem
  10. 10. © d-Wise 2013 August 8, 2013 Page 10  Extensive knowledge of data warehousing and business intelligence solutions  Broad range of experience with many different technologies  Unique software development perspective  Decades of experience developing and implementing SAS-specific solutions
  11. 11. © d-Wise 2013 August 8, 2013 Page 11  Experience with the design and development of large scale data warehouses  Data modeling to optimize the flow of data  Experience with both relational and non-relational databases  Experience with leveraging industry standards to optimize your technology  Experience integrating a range of products including JReview, WinNonLin, Oracle Clinical, DS Navigator and home grown data warehouses
  12. 12. © d-Wise 2013 August 8, 2013 Page 12  d-Wise developed an integration interface for a top pharmaceutical company to streamline data across their disparate solutions  d-Wise designed and developed an enterprise toxicology data warehouse populated with data from over a dozen diverse sources
  13. 13. © d-Wise 2013 August 8, 2013 Page 13  Integration of company’s technology to improve the flow of information  Development of custom reporting tools on top of existing solutions  Design and development of robust web based solutions for reporting and analytics
  14. 14. © d-Wise 2013 August 8, 2013 Page 14  Developed a large scale web based quality control system for over 3000 laboratory sites  Managed a full scale project to develop a health insurance automation reporting solution using a range of different technologies  Implemented a enterprise portal solution for a large life science company including the development of standard dynamic reports
  15. 15. © d-Wise 2013 August 8, 2013 Page 15  Decades of design and development of core SAS products  Experience implementing SAS solutions in large companies  Ability to develop custom plug ins to existing SAS technologies  Experience using SAS as a customer  Unique ability to assess current SAS architecture and provide plan to meet strategic vision
  16. 16. © d-Wise 2013 August 8, 2013 Page 16 Installation and implementation of SAS solutions including:  SAS Business Intelligence  SAS Data Integration (Metadata Server and Data Integration Studio)  SAS Drug Development  SAS Analytics Pro (BASE SAS, SAS/STAT, and SAS/GRAPH)  Implementation of Analysis tools including Enterprise Guide, JMP, and Web Analytics
  17. 17. © d-Wise 2013 August 8, 2013 Page 17  Analytical Workflows – automate the “smart” extract and staging of data for analysis by statistical tools and publish/capture the results back into SDD  Loading Large Data – a plug-in to compress and package directories of data for quick upload, then to decompress and recreate the folder structure within SDD  Loads Incremental Data – a workflow for loading incremental data into SDD and maintaining concurrency between the source system and the SDD repository
  18. 18. © d-Wise 2013 August 8, 2013 Page 18  Analytics propel the drug discovery process  Analytic processes: – are fed by clinical data – produce data and metadata – are critical to the overall process  Computational requirements may prescribe a dedicated system beyond your repository  How can this specialized system be integrated with the repository?
  19. 19. © d-Wise 2013 August 8, 2013 Page 19 SAS Drug Development Capture and Select input data with subset criteria (metadata driven) Perform smart extract (just what you need) Compute Publish computational results and (using just-in-time data) Metadata about the analysis Analytic System
  20. 20. © d-Wise 2013 August 8, 2013 Page 20  Customer outsources all data and reporting activities to CROs  CRO produce multiple folders containing lots of data – data that must be loaded into SDD – Loading this large volume of data is tedious & time consuming compared to loading a zipped archive  How can SDD support zipped archives?
  21. 21. © d-Wise 2013 August 8, 2013 Page 21 FIREWALL ROI: Reduced a 4 Hour Process to 15 Minutes SAS Drug Development
  22. 22. © d-Wise 2013 August 8, 2013 Page 22  Customer environment includes a local CDR and a SAS hosted SDD  Frequent, but minor, updates to large studies result in customer pains – Significant network traffic – Long upload times – Users waiting while data is extracted and uploaded  Would incremental uploads be faster?
  23. 23. © d-Wise 2013 August 8, 2013 Page 23 SAS Extract Callback Program Merge Data (ODM, CSV, SAS) FIREWALL SAS Drug Development SAS Merge ROI: Reduced a 12+ Hour Uploads to Minutes
  24. 24. © d-Wise 2013 August 8, 2013 Page 24  d-Wise thinks about SDD as a platform  Integrating remote systems can be made simple – clients can be introduced locally or remotely… depending on the needs  What is the role of an API?  Where do web services fit into this puzzle?  How does all this techno-speak translate into something valuable for the business?
  25. 25. © d-Wise 2013 August 8, 2013 Page 25  As a platform, SDD can be extended to bring new capabilities to the business  Extending doesn’t have to mean customizing – plug- ins can sit next to SDD without compromising the integrity, security, or compliance of the underlying system  Workflow and automation specialized for your approach to data management – SDD makes this possible through the API
  26. 26. © d-Wise 2013 August 8, 2013 Page 26 SAS Extract Callback Program Merge Data (ODM, CSV, SAS) FIREWALL SAS Drug Development SAS Merge ROI: Reduced a 12+ Hour Uploads to Minutes
  27. 27. © d-Wise 2013 August 8, 2013 Page 27 BioTechnology / Pharmaceutical Education Other Health Care
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