Data Transparency & Governance in the Analytics Supply Chain
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  Mark Marinelli   Mark Marinelli
Chief Technology Officer


Thursday, April 21, 2016
08:30 AM - 09:15 AM

Level:  Business/Strategic

Solving complex, data-driven problems can be approached in a number of ways, but it is clear that the analytics supply chain is broken. IT would like to get out of the business of being an analytics service center and business would like to be more self-sufficient and address their own questions. With the rapid adoption of self-service data preparation tools, there is finally an answer to alleviating both these pain points. Since data no longer lives in silos, domain expertise and knowledge exists within a larger ecosystem of stakeholders at a company, so collaboration and transparency, coupled with proper governance controls, are key components of success. Both IT and business need the ability to view and easily share workflows in order to understand the underlying business logic that led to an answer and facilitate problem solving by leveraging their collective knowledge.

In this presentation, we’ll focus our discussion on how self-service data preparation and advanced analytics can help your organization:

  • Blend complex data from multiple sources to empower users to quickly build sophisticated analytic applications through intuitive data flows.
  • Arrive at faster business insights through collaboration tools, enabling both data architects and non-technical consumers to easily view workflows and business logic.
  • Improve transparency by removing the “black box” and provide actionable, accurate answers that all parties can trust.
  • Ensure governance and data quality through data provisioning.

Mark Marinelli, Chief Technology Officer at Lavastorm, is responsible for driving product innovation and development strategy for the company’s self-service data preparation and advanced analytics technology. A 20-year veteran of the analytics software industry, his extensive experience spans software development, product management, and product strategy from early multidimensional databases to modern data analytics technologies.

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