Businesses today accept the reality that big data can be very valuable to their operations because of the many insights and information that it can give them. But if you think that you could only work with data that you have stored for some time, then you are definitely losing out on a lot of actionable insights that matter right now. You should be able to capture data in real time and analyze it.
Big data, according to Gartner, will cause companies to spend anywhere from $27 billion to $55 billion. That is pretty much a huge investment, but the payoffs are great because of the insights that could bring about great changes to your operations. IBM also estimates that we are currently generating around 2.5 quintillion bytes of new data daily, so why wait before analyzing every piece of data that comes your way?
Stream processing can help you do just that: analyze all the data as soon as they become available to you so that you are given timely and up to the minute insights. These insights are what make up your strategies and because you are able to analyze your data fast enough, you will be able to apply these strategies at a time when they would matter and have the best impact to you and your business.
All these while also ensuring that you are upholding data auditability and quality.
As early as 2009, IBM already had its System S product and one use case that they flaunted was to apply it to financial companies. The System S would be able to bring together all the currency movements, housing data, and stock trading trends and then add a layer of non-financial information such as headlines, weather conditions and other factors that affect financial data. System S could then crunch the numbers and give you insights about what’s happening out there very quickly and even involving bigger sets of data. Before the System S, most companies would have to contend with a far longer analysis time and limiting the scope of data involved.
In fact, with stream processing, you are able to analyze a constant stream of data even before it gets to a disk. It works with traditional data, as well as sensor and digital signals, videos, images, and other non-conventional data sources. The system makes use of data parallelism, which allows you to do parallel processing of your data. It also needs high compute intensity, which allows for an extremely high ratio between I/O and operations, and data pipelining, wherein data is distributed to consumers and users of that data.
Such a system is especially needed today when the amount of data is exploding and more and more business and IT leaders are finding it necessary to make decisions in real time. You simply cannot wait for data to be stored and analyzed and you certainly cannot work with a limited amount of data, and even outdated data.
So call Four Cornerstone and get a lead on how to use stream processing for your business.
Photo by Christoph Scholz.