It is no accident that we have recently seen a surge in the amount of interest in big data. Businesses are faced with unprecedented opportunities to understand their customers, achieve efficiencies and predict future trends thanks to the convergence of a number of technologies.
“Big Data” is one of the biggest buzzwords in the technology industry today – you can’t read the tech press or look at social media without seeing it. But what do we mean by Big Data, and what’s wrong with our old friend “little data” that has served us well for 30 odd years.
Data is growing and evolving in ways that legacy architects could not have imagined. We are seeing a shift from systems of record that are highly autonomous and rigorously constructed to make sure every piece of data is processed in-tact to data platforms that throw caution to the wind in exchange for performance and scalability. As data evolves and becomes more complex it begs the question, “What type of relationship are you seeking with your database?”
Analytics have become part of our everyday experience. If you have a Fitbit you can see analytics on your weight loss and step goals over weeks at a time. If you are a stock owner you likely get data analysis on your portfolio and their returns over a certain period. In business, if you happen to use Mailchimp to send out newsletters, you often see analytics on opens, click-throughs and more.
At this year’s O’Reilly Strata event we will showcase our support of the newest genesis of the Hortonworks Data Platform (2.0), a release that we believe represents a paradigm shift in the perception of what you can use Hadoop to accomplish.
A few weeks ago we told you about our two Data Services for Hadoop-based applications, the Managed Big Data Platform service (in Unlimited Availability) and the Cloud Big Data Platform (in Early Access). Working hand in hand with Hortonworks, we are giving you a choice of architectures for your Hadoop applications, whether you need a custom-built Hadoop architecture based on specific dedicated hardware, or a dynamic, API-driven programmable Hadoop cluster in our public cloud.