On Demand Webinar

Data Lake Transformation: Merging BI, Knowledge Graphs and Search

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The number of innovative products and technologies in the analytics world is staggering.  Unfortunately, so is the effort and expertise required to use them together effectively. We’ve got core analytics, big data streams,  graph and even search technology. They’re all great, but each one is its own island of skills and tooling, with its own unique ecosystem.

What’s needed is not just a way to integrate these technologies, but to use them in a cohesive way that weaves together paradigms and creates opportunities where before was siloes.  And it all must be done by leaving data where it resides; No crazy ETL into new graph formats, pushing down queries and aggregates down to the DBs and infrastructure where it resides delivering both aggregate and detailed views of the data; providing a query experience based on a fusion of search, semantic reasoning and analytics; mapping relationships through observation, even when the links are not explicitly known; and using varied visualization techniques to understand the data, depending on the its detail level, structure and context.

Join GigaOm’s Andrew Brust, and special guests Giovanni Tummarello (Chief Product Officer and Co-founder) from Siren, for this free Webinar. You’ll discover how to bring that motley crew of feeds, files and tables euphemistically called a data lake into a discovered, navigable whole that lets you derive real knowledge and insight from data assets across your organization.

Join us for this Webinar and learn how:

  • Core analytics, search and graph technology can be used together
  • Doing so greatly reduces the risk of analytics project failure
  • Combining technologies can elegantly provide complimentary perspectives, rather than force awkward context switches
  • The Nirvana of data insight is achieved through technology synergy, rather than supremacy of a single approach

Who Should Attend:

  • CIOs
  • CTOs
  • CDOs
  • Business Analysts
  • Data Analysts
  • Data Engineers
  • Data Scientists
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