Getting Big Data Where It Needs To Go

Getting Big Data Where It Needs To Go

Information is a critical, if not the, critical business asset in a fast-changing world. The more information an organization has, the better it can make decisions about which products and services to offer, how to price and distribute them, where it can reduce costs and where it can find new customers. Big Data is the process of creating insight from the increasing masses of raw data every organization generates.  Most Big Data is made up of loosely structured or unstructured data such as text, photos, genomic or other scientific data. But some of it also originates in structured relational databases. In addition, many of the results of a Big Data analysis are distributed in the form of a relational database. Whenever Big Data relies on relational data as either a source of information or a way to distribute Big Data insights, DataPortal can share those relational databases quickly, easily, cost-effectively and securely. “Point and Click” Database Sharing DataPortal is a patented tool for moving, storing, and sharing database data across platforms and over the Web. It was designed to be used by people at all technical levels. It requires no coding, entering command lines, opening ports or installation of software. Using DataPortal, each database is published to a DataPortal server. From there it is available over the internal LAN or the Internet to any authorized DataPortal client. This server-to-client communication avoids the security risks of exposing the database directly to a WAN or the Internet. Any user can transfer a full relational database or a subset of that database, in relational form, with the push of a button. All they need is a Web browser and authority to share the database. Using DataPortal, subject matter experts can stay focused on their critical, value-added analytic work without wasting time on the mechanics of sending and receiving data. DataPortal for Data Gathering DataPortal is an efficient way to gather structured data from various database sources at a central location for Big Data integration, analysis, conversion and storage. DataPortal complements Big Data frameworks such as Hadoop, which allow users to access massive quantities of data spread over hundreds or even thousands of processors. These frameworks allow queries to be performed using the familiar SQL used in relational databases.  The results of such queries can also take the form of structured data. Sharing the result set returned by Hadoop with end users can be...

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