| |July 20179CIOReviewWith the exposure to cloud based technologies, businesses are uniquely positioned to be more informed than ever before sources that enterprises want to lev-erage via analytics, and it does so at a low cost and with good interopera-bility with other platforms in the da-tawarehousing world. In this sense, Hadoop and datalakes add value to the DataWarehouse and its environ-ment without ripping and replacing mature investments. The data lake and the enterprise data warehouse must both do what they do best and work together as components of a logical data ware-house. The logical data warehouse, made up of an enterprise data ware-house, a datalake, and a discovery platform to facilitate analytics across the architecture, will determine what data and what analytics to use to an-swer business needs. DataLake also comes with features like SQOOP where loading data from Relational Data bases onto HIVE is easy and faster. Data modeling skill is not re-quired and data can be queried lever-aging its query features without the knowledge of SQL. The ability to capture and process this ever growing business data is now possible because of the growth of inexpensive storage and limitless compute, along with the invention of new technologies that enable real-time analysis and a direct connection to action through new applications and products. EMC Isilon is one such example; it has multi-protocol scale-out file storage for DataLake kind of applications. The new datalake2.0 strategy ex-pands the datalake to extend from the datacenter to the enterprise edge locations and to your choice of public or private cloud options. With Isilon CloudPools software, the datalake can be extended to provide virtually limitless capacity without adding any complexity to store or manage the data.The Hadoop datalake isn't with-out its challenges. Even experienced Hadoop datalake users say that a successful implementation requires a strong architecture, security gates and disciplined data governance policies- without those things, they warn, datalake systems can be come out-of-control dumping grounds of exploding data.In conclusion, in the era of Data-Driven Innovation the emergence of the data lake comes from the need to manage and exploit new forms of data. Many companies feel like they are on the cutting edge of BigData analytics in the enterprise by leveraging this. More impor-tantly, it helps with the foundation and tools to use data and analyt-ics to create sustainable, long-term competitive differentiation. The shape of your datalake is de-termined by what you need to do but cannot with your current data processing architecture. The right datalake can only be created through experimentation. Together, the data lake and the enterprise data ware-house provide a synergy of capabili-ties that delivers accelerating returns, allowing people to do more with data faster and driving business results. It is a game-changer not because it saves IT a whole bunch of money, but because it can help the business make huge money.
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