Predictions for Big Data Tech in 2015
In a short span of time, the technology of big data has grown from nothing into one of the most important factors of the current digital age. Last year, we saw a large number of big data projects move from their beta stage into production. This trend will develop & continue in 2015, with big data tech being used for even more applications—including uses in real time.
Experts are claiming that throughout 2015 organizations will develop their big data applications beyond initial batch deployments, using the technology to gain insights in real time. The motivation for this is the potential benefits, which have been highlighted by how far big data has moved businesses forward previously. Industry leaders have been at the forefront of this and are incorporating big data applications as part of their analytics programs, and are gaining real time data to help steer their business as they work. Here are 3 key predictions for these developments:
The Agility of Data is a Key Focus
Experts say that data agility will become a central concern for business organizations as they develop their programs from the capture and management of data to the use of it. It has been claimed that date warehouses and legacy databases have become too expensive, and DBA resources are required to compress and structure the data, as a result, the legacy databases are not fit for purpose in terms of agility for most businesses.
Companies Shift From Data Lakes to Data Processing Platforms
2014 was the year when the “data lake” became prominent as servers were used to store data until it could be used. They present an enticing value proposition because they are representative of the type of infrastructure, which is economically appealing and agile. Experts claim these will still be evolving in 2015, gaining capabilities that will make them more efficient and more secure.
Big Data Self Service Hits the Mainstream
Progress in big data technology means that this year will be the time when IT access moves closer to data scientists and business users, by leveraging the advances in making businesses feel comfortable while accessing their data. Where businesses would have previously had to work through centralized data structures, they can now move away from this model, increasing their ability to speed up processes and gain access to new sources of data.