Extract Real-Time Operational Insights from Big Data

by   |   September 29, 2015 8:45 am   |   0 Comments

As the amount of data, the number of sources, and the speed at which data is generated continue to grow, the time that organizations can afford to wait for insights is shrinking. Massive amounts of data are pouring in to organizations, but very little of it is evergreen. For much of that data, the value lies in gleaning insight from it and applying that insight to the business as quickly as possible. Hesitate, and that crucial insight can become worthless.

This is especially true for the operational insights that machine data can provide. If you don’t know how your IT operation, for example, is functioning right now, you don’t know how it’s functioning. In today’s fast-moving business world, knowing how it functioned an hour ago is as irrelevant as knowing how it functioned last year.

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As Forrester Research asserted in a 2014 report, “Business won’t wait. That is truer today than ever before because of the white-water flow of data from innumerable real-time data sources. Market data, clickstream, mobile devices, sensors, and even good old-fashioned transactions may contain valuable, but perishable insights. Perishable because the insights are only valuable if you can detect and act on them right now.”

To keep the business running, Java developers, DevOps, and IT Ops personnel need real-time insight into their machine data. This streaming data in motion can hold the key to valuable insights, but for that data to have any value at all, the business has to be able to act on those insights in the moment.

It’s well known that in-memory analytics is a popular approach for keeping up with time-series data, but getting that unrelenting stream of data that is constantly arriving from applications and infrastructure under control is only half the battle. What’s less well-known is how to glean insight from your machine data using in-memory analytics.

Join us Today (9/29/15) at noon for a Live Q and A with Albert Mavashev, CTO at jKool. An expert in streaming analytics, Albert will answer your specific questions about how to glean insight from your machine data using in-memory analytics and share tips that will enable you to quickly understand your customers’ needs, improve diagnostics, identify trends as they are happening, be predictive, and take action in real-time. Albert will discuss topics such as enabling developers to stop diagnosing application problems and get back to developing, the financial and resource investments involved with gaining real-time insights into data, how streaming data analytics differs from Business Intelligence, and whatever other topics you wish to discuss.

To register for the Live Q and A, click here. After you register, you can begin posting your questions for Albert immediately.

In addition to the opportunity to ask your questions to an authority on real-time data analytics, everyone who registers will be entered into a drawing for a new Samsung Galaxy Tab 4 tablet computer.

We look forward to your joining us for a lively, informative discussion.



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