Agile Analytics: 11 Ways To Get There - InformationWeek

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Data Management // Big Data Analytics
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4/26/2016
07:06 AM
Lisa Morgan
Lisa Morgan
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Agile Analytics: 11 Ways To Get There

The accelerating pace of global business means that enterprises need more agile data-related systems and practices. Becoming more agile -- and succeeding at it -- isn't always easy given existing technology investments, constant technological evolution, and lingering cultural obstacles. No matter how agile your company is or isn't now, consider these important points.
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Consider Scalability 

A common problem enterprises face is scalability. A lot of times the notion is dismissed, given the availability of massively scalable technologies such as Hadoop. However, Hadoop isn't a panacea for everything -- nothing is. Yet, organizations continue to search for silver bullets and in doing so disregard details that can hurt them competitively. 
'Most enterprises have broken analytics stacks that don't scale. Their data is growing exponentially and the consumption is growing linearly -- and that gap is only growing,' said Zubin Dowlaty, head of innovation at big data and analytics solution provider Mu Sigma, in an interview. 'We're seeing a lot of clients that are unable to scale.'
(Image: geralt via Pixabay)

Consider Scalability

A common problem enterprises face is scalability. A lot of times the notion is dismissed, given the availability of massively scalable technologies such as Hadoop. However, Hadoop isn't a panacea for everything -- nothing is. Yet, organizations continue to search for silver bullets and in doing so disregard details that can hurt them competitively.

"Most enterprises have broken analytics stacks that don't scale. Their data is growing exponentially and the consumption is growing linearly -- and that gap is only growing," said Zubin Dowlaty, head of innovation at big data and analytics solution provider Mu Sigma, in an interview. "We're seeing a lot of clients that are unable to scale."

(Image: geralt via Pixabay)

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