|Scalability, uninterrupted performance, availabilitty, adaptibility, and flexibility are the conditions when looking a right data solution to protect big data / Photo by: everythingpossible via 123rf|
Quite possibly the only thing that might stand in the way of managing big data is the fact that not only does it have to be efficient, it also has to be flexible. But if it’s a long-time kind of big data management, it’s important to keep in mind these characteristics when choosing big data strategy.
Scalability. Big data is big for a reason: there’s a steady stream of data anywhere you go. Now that the world is only ever pushing forward in a bid for better connectivity, the scale of a big data environment must be discussed.
Uninterrupted performance. Big data also needs to not only be functional and have enough space to move about, but it also has to be accommodated by big data solutions that are fast enough to keep up. As mentioned by Tech Radar, “speed is key” in the big data game. A big data solution should, therefore, be a “data-centric security solution that delivers on its intelligence features for both streaming and load distribution.”
Availability and adaptability. The data-centric solution should be able to have access to every possible data there could ever be, especially since making these available will help big data solutions “achieve maximum value and protection” that is not at the cost of locking data away forever.
When specific data do start to cause an issue, the system should be able to adapt quick to the changes and resolve to continue operations like it had not been interrupted in the first place.
Flexibility. New tech always cropping up also means that big data frameworks have to be able to follow trends efficiently, this means that they have to be flexible enough in order to ensure that it “does not become outdated.”
Spark, MapReduce, and Hadoop have already plunged ahead on a good start, but more will be needed to be done a few years down the line.