Streaming data analytics is streamlining businesses

Stream analytics has been around for some time now, though, in the beginning, entrepreneurs were not very comfortable with what was deemed as a technology that would be effective in the future. But no more. Businesses today are streamlining their businesses so as to reap the benefits of the streaming data analytics. Those old production lines are giving way to the new ones and the new ones are being constantly monitored to make them even better and more effective.

By now, many companies have decided that big data is not just a fad, but a new fact of business life - one that requires having strategies in place for managing large volumes of both structured and unstructured data. And with the reality of big data comes the challenge of analyzing it in a way that brings real business value. Business and IT leaders who started by addressing big data management issues are now looking to use big data analytics to identify trends, detect patterns and glean other valuable findings from the information available to them.

However, when a technology becomes popular everyone wants to grab it thinking it would give them the desired benefits. But that doesn’t happen simply by owning stream analytics software or hiring a person to manage your big data. In fact, it can become counterproductive if you do not have a well thought of strategy suitable for your business. The Apache spark use cases are increasing day by day and it is very likely your business is also in its ambit but still, you would need some careful planning before jumping on to the bandwagon.

It can be tempting to just go out and buy a big a data analytics software, thinking it will be the answer to your company's business needs. But big data analytics technologies need to be handled with care and planning. Well-planned analytical processes and people with the talent and skills needed to leverage the technologies, are essential to carry out an effective big data analytics initiative. If you go out and buy the technologies just because somebody told you so would inevitably make your fingers burn. Buying additional tools beyond an organization's existing business intelligence and analytics applications may not even be necessary depending on a project's particular business goals.

You must use the information resources prudently to learn about big data analytics best practices from experienced users and industry analysts -- from identifying business goals to selecting the best big data analytics tools for your organization's needs. 

Technology selection is just part of the process when implementing big data projects.  It's crucial to evaluate the potential business value that big data software can offer and to keep long-term objectives in mind as you move forward. You would definitely need practical advice on using big data analytics tools, with insights from professionals in retail, healthcare, financial services and other industries and so on that are suitable for your own business.

A number of myths about big data have proliferated in recent years. Don't let these common misperceptions kill your analytics project. Many data streaming applications don't involve huge amounts of information. So if your business does not generate a huge amount of data, a suitable paradigm would be essential.

Online advertising platform providers are tapping Apache Spark stream processing capabilities to support more real-time analysis of ad data. So if you happen to be in the glamorous ad world you could tap the power of stream analytics but again you would need to calibrate your business potential and requirement.