the 3 insights defining modern analytics

3 Insights Defining Modern Analytics The current data landscape, key trends, and the future of business intelligence !and data analytics.

The technology landscape has created entirely new sets of demands on data analysts.

WHY WHAT

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Business users demand complete, readily accessible information, on any device, at all times.

WHY WHAT

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New technologies in data warehousing

WHY WHAT

•  MPP, columnar, Hadoop, in-memory •  Increased power of MySQL infrastructure

via IaaS like AWS and Softlayer

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Data management techniques in the new era of big data

WHY WHAT

•  “Collect & store everything” philosophy •  ELT vs ETL — complex analytics

should happen automatically and on the fly

•  Details define value and drive action

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The missing innovation cycle

WHY WHAT

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BI needed a new architecture… not just a different way to distribute an application.

WHY WHAT

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Data analytics isn’t easy, it’s getting more complex every day. Don’t trade complexity for self-service.

WHY WHAT

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Empower the data analyst.

WHY WHAT

•  Resources aren’t increasing with complexity – that’s a conundrum

•  Same people, more data, more complexity

•  The data analyst is expected to do more

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BI shouldn’t be consumed only via the software. It should be everywhere.

WHY WHAT

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How does a modern analytics team overcome these obstacles?

3 Insights…

WHY WHAT

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1 Data modeling is extremely important

WHY WHAT

•  Analysts should do analytics, not reporting

•  True efficiency is reached by not repeating work or duplicating efforts

•  Extending data everywhere needs a single source of truth

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2 Exploit the power of the underlying database

WHY WHAT

•  Big data isn’t easily moved (increased latency)

•  Value in details only comes from live access

•  They’re expensive and powerful, exploit the investment

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3 Distribute everything through the web,

securely.

WHY WHAT

•  BYOD and other trends remove standardization of devices (phones, laptops, etc.); the browser is the only solution for consistency

•  Collaboration is core to success with data; the web is inherently collaborative

•  Data everywhere needs a web architecture: the web was built to be connected

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WHY WHAT

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