Big data, big governance

Traditional data governance is all about establishing a boundary around a specific data domain. This translates to establishing authority to define key business terms within that domain; establishing business-driven decision making processes for changing the business terminology and the rules that apply to them; defining content standards (e.g., metadata and […]

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Is effective data governance possible in an era of big data?

.@philsimon on the new challenges of data governance.

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ESP can determine if big data is eventful

Many recent posts on this blog have discussed various aspects of event stream processing (ESP) where data is continuously analyzed while it’s still in motion, within what are referred to as event streams. This differs from traditional data analytics where data is not analyzed until after it has stopped moving and has […]

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Event stream processing: Think "rapid"

What sends a data management product to the top of the “hot” list? In a word – speed. Especially when that speed can gracefully accommodate the huge world of streaming data from the Internet of Things. One of SAS’ hottest (and recently enhanced) products, SAS Event Stream Processing is an […]

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Social media: The case for event stream data

@philsimon on the need to adopt new tools to understand events.

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Analyzing the data lake

In my previous post I used junk drawers as an example of the downside of including more data in our analytics just in case it helps us discover more insights only to end up with more flotsam than findings. In this post I want to float some thoughts about a two-word concept […]

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Data management lessons from Google

@philsimon says that, yes, we can learn a great deal.

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Junk drawers and data analytics

In the era of big data, we collect, prepare, manage, and analyze a lot of data that is supposed to provide us with a better picture of our customers, partners, products, and services. These vast data murals are impressive to behold, but in painting such a broad canvas, these pictures […]

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Analytics lessons from Amazon

.@philsimon on what we can learn from Seattle's juggernaut.

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Hadoop is not Beetlejuice

In the 1988 film Beetlejuice, the title character, hilariously portrayed by Michael Keaton, is a bio exorcist (a ghost capable of scaring the living) hired by a recently deceased couple in an attempt to scare off the new owners of their house. Beetlejuice is summoned by saying his name three times. (Beetlejuice. Beetlejuice. Beetlejuice.) Nowadays […]

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