Big data analysis, that extracting value from Big Data today has become a business imperative if we aspire to make better decisions, predict consumption habits and, in summary, when we seek to obtain a competitive advantage that differentiates us from our competitors.
The irruption of new technologies Big Data has forced the reformulation of data center strategies to achieve efficiency and gain awareness of these collective preferences from huge volumes of data from hundreds of millions of devices. Y, undoubtedly, in that reformulation Hadoop is a key element thanks to the huge utility Yellow Elephant Open Source to Save and Process Big Data at Low Cost.
But even though the Hadoop-powered revolution, architect of the democratization of Big Data, makes it possible to scale at low cost, the truth is that it also implies deficiencies that need to be fixed. Even though today Hadoop is almost synonymous with Big Data, not only more robust platforms are required, agile and scalable, but also real-time analysis tools for a great improvement of decision-making processes at political and commercial level.
Real-time analysis with non-disruptive technologies
Its potential and popularity allow us to affirm that, as a big data processing engine, Hadoop will continue to be part of the future of Big Data in the near future, and even in the medium and long term, but with items that complement it to boost these weaknesses. Therefore, there will be share the spotlight with new technologies that help make the most of Big Data.
Specifically, solutions capable of responding to the real-time analysis needs Y, as an example, engines In Memory (Spark, Storm, etc.) to allow real-time queries are the strongest candidates. A joint implementation that take advantage of the different resources in architectures to this, even though in the future they may become disruptive technologies.
This emerging need to analyze big data for immediate business decisions will force Big Data technologies to mature. until its total unification, as happened at the time with relational databases.
Therefore, versus current trends, a future beyond Hadoop means not so much its exclusion, but a improvement using other complementary solutions that also satisfy this requirement for real-time analysis or that help guarantee its performance, without giving up the advantages of infinite scalability and a large data repository.
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