Real-Time Analytics: 10 Ways To Get It Right - InformationWeek

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8/20/2015
12:06 PM
Lisa Morgan
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Real-Time Analytics: 10 Ways To Get It Right

While real-time analytics is getting more affordable, it's still not right for everything. Here are 10 ways to get the most from real time, near real time, and batch use cases.
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Meet Evolving Regulatory Requirements 

Information that companies in heavy industries once calculated annually is now calculated in a matter of minutes. Instead of submitting a table of values and list of responses periodically, the underlying information must be accessible on demand and transparent for audit purposes.
'The compliance systems have usually resulted in more spreadsheets with more external links requiring more drive space. This is not sustainable as the complexity and number of environmental regulations increase,' said Philip Black, data information management specialist and product marketing strategist at Wood Group Mustang. 'In order to meet [the new] requirements, companies are using environmental analytics to turn vast amounts of data into actionable information.'
By combining domain-specific knowledge with big data, energy companies can see the relationships between data points that were difficult to pinpoint using spreadsheets.
'In industries such as refining, petrochemical, and manufacturing, where high-frequency measurements and short-term compliance are required, [real-time] environmental analytics are being used to provide predictive guidance as to whether or not operations need to be adjusted to prevent problems. Estimates have always been used, but due to the complexity of the regulatory calculations, they have not been accurate enough to use for predictions,' said Black.
Compliance requires faster issue identification and resolution. Batch data historically has been stored in multiple systems, and even if the data was stored in one place it was not necessarily connected to other operational information. Using analytics to review the raw, high-frequency data, hidden issues can be spotted and correlated with external information sources, such as production levels, accounting, or even meteorological data stores.
'Instead of manually sorting through spreadsheets to answer questions such as 'Why do I have more problems in Q3 than Q1?' or 'If production was lower last month, why did we have more compliance issues?' you can simply [run a query],' said Black.
(Image: Willenhallwench via Pixabay)

Meet Evolving Regulatory Requirements

Information that companies in heavy industries once calculated annually is now calculated in a matter of minutes. Instead of submitting a table of values and list of responses periodically, the underlying information must be accessible on demand and transparent for audit purposes.

"The compliance systems have usually resulted in more spreadsheets with more external links requiring more drive space. This is not sustainable as the complexity and number of environmental regulations increase," said Philip Black, data information management specialist and product marketing strategist at Wood Group Mustang. "In order to meet [the new] requirements, companies are using environmental analytics to turn vast amounts of data into actionable information."

By combining domain-specific knowledge with big data, energy companies can see the relationships between data points that were difficult to pinpoint using spreadsheets.

"In industries such as refining, petrochemical, and manufacturing, where high-frequency measurements and short-term compliance are required, [real-time] environmental analytics are being used to provide predictive guidance as to whether or not operations need to be adjusted to prevent problems. Estimates have always been used, but due to the complexity of the regulatory calculations, they have not been accurate enough to use for predictions," said Black.

Compliance requires faster issue identification and resolution. Batch data historically has been stored in multiple systems, and even if the data was stored in one place it was not necessarily connected to other operational information. Using analytics to review the raw, high-frequency data, hidden issues can be spotted and correlated with external information sources, such as production levels, accounting, or even meteorological data stores.

"Instead of manually sorting through spreadsheets to answer questions such as 'Why do I have more problems in Q3 than Q1?' or 'If production was lower last month, why did we have more compliance issues?' you can simply [run a query]," said Black.

(Image: Willenhallwench via Pixabay)

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GinaA474
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GinaA474,
User Rank: Apprentice
9/3/2015 | 12:15:30 PM
Great examples of real use case scenarios
The customer experience example with iHeart radio really shows the power of analytics. 
shamika
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shamika,
User Rank: Ninja
8/27/2015 | 7:07:01 AM
Re: Real time analytics
"Online customers are notoriously impatient". Correct. I am one of them too. They expect the solution to be on their fingertips. In my opinion this is especially applicable for financial institutes.
shamika
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50%
shamika,
User Rank: Ninja
8/27/2015 | 6:57:53 AM
Real time analytics
I agree with the concept that bank uses. However as you said batch processing will take place towards the close of business which is a concern at the moment. I think there will be a solutions for this soon.  
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