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SmartData Collective > Business Intelligence > Data Analytics: The Potential Benefits of Real-Time Decisions
Business Intelligence

Data Analytics: The Potential Benefits of Real-Time Decisions

Brett Stupakevich
Last updated: 2010/12/15 at 12:55 PM
Brett Stupakevich
3 Min Read
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wallstreet3 300x243 photo (data analytics)

We live in an “instant” world where we’ve gotten very good at being able to tell when an “event” occurs. For example:

wallstreet3 300x243 photo (data analytics)

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We live in an “instant” world where we’ve gotten very good at being able to tell when an “event” occurs. For example:

  • News from a government agency could affect the price of a company’s stock.
  • The stock of a key product at a store is rapidly dwindling .
  • A valuable customer is shopping your website right now.
  • A competitor has just reduced the price of your best-selling item.
  • Purchases on a customer’s credit card seem to indicate fraudulent use.
  • There has been a surge of tweets about your company in the last 15 minutes.

However, knowing about an event has little value unless we act on that information. According to an article in Information Management magazine, companies are now focusing significant attention trying to improve their ability to react to real-time events using data analytics.

“Real-time analytics” offers speed, flexibility, and the potential to gain competitive advantage by responding to an event soon after it occurs. Just as the early bird gets the worm, acting quickly to respond to an event can help a company get a “leg up” on the competition.

For some organizations, real-time analytics has already demonstrated its value in the form of real profits and improved customer relationships. For example, real-time analytics is being used by brokers to make decisions about stock trades, – impacting profits – and by retailers to make decisions about marketing and customers – impacting sales and customer relationships.

Real-time analytics sounds straight forward. An event occurs, data relevant to the event is collected, the data is analyzed, and a decision is made whether or not to act in response to the event. But the entire process needs to happen quickly – in “real time” – which makes implementing real-time analytics more difficult than traditional BI decision support focused on longer-term strategic decisions.

In an upcoming post, we’ll discuss more about what real-time analytics is – and what it isn’t.

Steve McDonnell
Spotfire Blogging Team

Image Credit: Getty Images

TAGGED: data analytics
Brett Stupakevich December 15, 2010
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