Data Lake as a Service
The world’s first data lake as a service, the Bigstep Metal Data Lake is the easiest, most efficient way to store and access structured or unstructured exabyte-sized data. It integrates with your existing applications and systems, delivers unparalleled throughput, ensures enterprise grade security, and all for pennies on the gigabyte. It’s truly never been easier to work with big data.
You sat on the sidelines, anxiously awaiting the play caller’s decision. Is big data and data analytics the way to score a touchdown, or is the call still under review? After further review, the decision on the field stands … the Hadoop ecosystem features all the X’s and O’s you need for solid BI, marketing data, or any other purpose you have for big data and data analytics. What other insider tips and tricks do you need to score the extra points? We’re so glad you asked … Continue Reading
Whether your organization is just dipping your feet in the pond of big data or dunk all the way in for a swim there regularly, someone at some point has likely brought up the topic of building a data lake. They were likely met with a range of reactions, from the, “has he lost his mind,” look delivered over the rim of a coffee cup in mid-sip, to outright guffaws of laughter over the insanity of the idea. Don’t laugh. These are real reactions by real adults when presented with the possibility of a data lake. Continue Reading
For a very long time, the wide world of data storage was, well, a bit stagnant. Yes, storage costs came down over time, as capacity and supply increased, but that was about it. Then came the cloud, and now every year there are huge strides made in the field. So, what’s playing out in the data storage arena this year? Continue Reading
In the beginning was the database, and the database was good. It stored all of the transactional data and powered your users and applications quite nicely. Then the data grew, and the database expanded to the data warehouse. The data warehouse was good, too, and it allowed organizations with larger data sets to power even more users and applications. Then came big data, and the data warehouse just couldn’t keep up. Big data involved lots of sloppy unstructured data that didn’t get along well with relational databases. Businesses needed more. Hence, the data lake. Continue Reading
When a new concept comes along, the first thing it has to prove to the marketplace is why it is a valuable thing and what it has to offer that previous ideas can’t. Such is the case with both Hadoop and the data lake. Neither is easy to master, and both come with considerable investments of time and expense. What does your organization stand to gain for these investments? What can you actually get done with a data lake built on Hadoop? Continue Reading