BEGIN:VCALENDAR VERSION:2.0 PRODID:-//hacksw/handcal//NONSGML v1.0//EN METHOD:PUBLISH BEGIN:VEVENT DTSTAMP:20260310T220128Z DESCRIPTION:Click for Latest Location Information: http://edw2018.dataversi ty.net/sessionPop.cfm?confid=121&proposalid=9317\n

Regardless of your org anization’s level of analytics maturity, self-service analytics and d ata preparation have provided unprecedented agility for both business analy sts and data scientists. However, the combination of a lack of data governa nce and impact on BI/IT teams - controlling data utilization, providing acc ess to data and understanding data lineage - has produced internal chaos. M any now face a lack of control and trust in non-curated data, a lack of eff iciency in both operational processes and duplication of efforts, and a lac k responsiveness by IT due to the burden of constant data access requests. At the same time, line-of-business leaders are looking to evolve their data strategy and enable more people access to more data to evolve from defensi ve data tactics (improving operational efficiency and mitigating compliance risk) to more offensive data insights (identifying growth opportunities).  
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\nToday’s organizations need a centralized data i ntelligence solution with an integrated data marketplace that provides easy  but controlled access to any data type, putting trusted, governed dat a into the hands of employees with reduced data security and compliance ris ks. Employees can easily find and access trusted data, which frees up IT re sources and improves customer satisfaction within the business. The result is more trust, more data, and more minds.  
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\nAdvancement s in enterprise data preparation with progressive collaboration, socializat ion, and machine learning characteristics are the drivers behind data intel ligence adoption. As a result, companies are experiencing improved operatio nal processes, insightful data-driven decisions, and better business outcom es.  
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\nIn this presentation, Datawatch Chief Product Off icer Jon Pilkington will share:

\n\n An understanding of how the self-service analytics movement has adversely i mpacted the trust and confidence in data outcomes due to a proliferation of unsecured, ungoverned data sources\n Insight into the evolutionary step in team-driven, enterprise preparation&n bsp;and analytics that combine advanced data preparation features (e.g . automation, cataloging, stewardship, and governance) with social media pl atform attributes and machine learning to create an intelligent data proces s\n Best practice guidelines for organizing and optimizing data discovery and p reparation for users to collaborate, share, and reuse governed datasets\n A data strategy model that enables both defensive and offensive approaches to operational excellence and analytic insights\n\n DTSTART:20180426T093000 SUMMARY:More Trust, More Data, and More Minds – How Team-Driven Analytics C an Make Self-Service, Governance, and Collaboration a Reality! DTEND:20180426T102959 LOCATION: See Description END:VEVENT END:VCALENDAR