Turning the Corner: What It Takes to Build a Modern Data Warehouse
Live Webcast October 15, 2015
Watch the archive: https://bloorgroup.webex.com/bloorgroup/onstage/g.php?MTID=e3983398e33dc035f3c66fdb6006b380d
If necessity is the mother of all invention, then it’s no wonder the technology space moves so fast. From the consumerization of IT to the steady emergence of innovative solutions, organizations often struggle to stay afloat in the sea of options. As we march steady to the pace of Moore’s Law, analysts and business users expect quicker and easier access to enterprise data, and the data warehouse of yore must modernize to meet those demands.
Register for this Roundtable Webcast with Analyst David Loshin, Dwaine Snow of IBM, Heine Krog Iversen of TimeXtender and TJ Laher of Cloudera. This expert panel will discuss the market forces that brought data warehousing to its current state and the key factors driving today’s innovation. They will explore how new data types and sources are raising analytic expectations and changing the way enterprises design information architectures.
Visit InsideAnalysis.com for more information.
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6. Data Warehousing: Past, Present, Future
Dennis Jarvis
Tibet-5809 - Yak at Yundrok Yumtso Lake
kevin ryder
old tractor
Original data warehouses were slow but powerful
Second generation offered new functionality
Third generation? Agile, Automated, Adaptive
7. Agile, Automated, Adaptive: How So?
!Agile: How quickly does the warehouse
deliver value to key stakeholders? Can
new users be onboarded efficiently?
!Automated: Does your team need to do
much manual, tedious maintance? What
about documentation?
!Adaptive: How easily can the warehouse
be modified to add new data sets?
8. Data Warehousing vs Big Data Analytics
!Data Warehousing uses structured
(relational) data to enable accurate
reporting, and facilitate ad hoc queries.
!Big Data Analytics focuses on
“unstructured” (non-relational) data to
enable business analytics.
!These are two very different paradigms,
though there is some overlap.
9. Whither, the Warehouse?
!For the time being, the Data Warehouse
will surely remain the “golden source” of
curated, governed, trusted data for key
executive decision-makers.
!Forward-thinking organizations will find
ways to combine warehouse data with
insights derived from Big Data, via use of
dashboards and data visualizations.
10. Big Value, Big Hurdles for Big Data
!Big Data offers a second chance for the
data management industry
!Because machines don’t lie, Big Data can
provide built-in accuracy (except social)
!The toolsets for harnessing Big Data
remain relatively nascent
!Though tremendously powerful, the
open-source movement is volatile