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.
As we close out another big year for data driven application adopters, the emphasis on delivering right business insights has never been greater. The companies that have embraced data analytics have quickly tapped into new revenue streams and innovated faster than their competitors. The conversation is no longer about when and why an organization should implement a robust data strategy, but which one they should focus on and how they will get valuable insights quicker. This may be best represented by the overwhelming attendance at this year’s fall Strata Conference focusing on the world of Apache HadoopTM, October 28 through October 30 in New York.
Not all data is created equal. Each company’s data strategy needs to be laid out with consideration and thought as to what the future demands of the system might be. Although HadoopTM has its roots firmly planted in the JBOD and bare metal camps, users are increasingly trying to find ways to split up data processing based on workload requirements and on the nature of the type of query they are running.
Most companies today still make business decisions based on guesses, hunches and intuition rather than leverage data-driven analytics platforms. Many don’t understand how to capture the insights or they don’t have the mathematical expertise to make their data meaningful in a manner that helps describe what they should look for. As companies transition away from traditional ways of doing business and start capturing the relevant data that allows senior management to make informed decisions, they encounter an explosion of data growth that legacy database systems and information management processes can no longer manage.
The world of big data is vast. And organizations trying to prepare for success by harnessing the power of data analytics can sometimes fall victim to confusion and tricky marketing. But one thing that is often left out of the conversation is the awareness of the big data problem. With the heightened expectations that big data promises, it’s important to put your data considerations in the context of a realistic discussion around your organization’s needs, use cases and tools.