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We’ve reached an age in which technological capabilities can analyze virtually anything, including Big Data. While this should be viewed as a major technological accomplishment, many enterprises are now being faced with the challenge of storing and analyzing volumes of structured, unstructured and semi-structured data sources which have simply outgrown data warehouses. Data driven businesses are now being forced to seek a smarter Big Data management solution.
Offloading is described by IBM as, “moving infrequently accessed data from data warehouses into enterprise-grade Hadoop.” Simply put, in order to deal with volumes of data coming from a variety of complex sources, enterprises are now transferring large data sets from data warehouses onto another analytic platform. An offloading solution provides companies with a long-term storage and ETL tool, enabling enterprises to combine their current data warehouse with a new technology.
Data warehouses are capable of storing volumes of past or archived data without much updating required. An offloading solution should be applied when an enterprise is confronted with what I refer to as a, “Big Data overflow.” A Big Data overflow occurs when a companys’ data warehouse can no longer accommodate the volumes of data flowing in from social networks, online sources, customer records, machine-generated log files, etc. (unstructured/semi-structured sources).
Offloading serves as a solution to unconstrained analytics and helps companies capture information which was once considered unobtainable due to data warehouse restrictions. When utilized correctly, offloading can provide companies with 3 main benefits:
Transferring data from one source to another is easier said than done. Moving information from a Data warehouse to another platform can be extremely expensive and time consuming, depending on the technology. Apache Hadoop, Amazon Redshift and SQream Technologies all offer offloading solutions which are compared below:
Data only continues to get bigger as we approach 2014. The bottom line remains – enterprises that want to get the most from their Big Data must be equipped with a hassle-free and cost-effective data storage solution. Apache Hadoop, Amazon Redshift and SQream Technologies all offer great options, the next step is finding the best fit for your company.
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