Many enterprises are rapidly deploying big data technologies to better process large stores of information for more actionable analytics. Leveraging these tools for the most insight demands remote database support, however, in order to ensure that analytics are both timely and accurate.
Mark Smith, Information Management contributor, explained that migrating and integrating data from separate, existing sources can be time-consuming, expensive and stressful for organizations that have data spread across disparate systems. Without the use of database administration services, these obstacles can become even further challenging, as Smith explained that conventional systems are incapable of allowing a seamless flow of data between relational and non-relational structures. Integration processes must be flexible and able to adapt to different events and streams, while ensuring that high quality of data is maintained.
Smith reported that organizations often struggle to choose the best approach to big data due to a lack of knowledge regarding the specific practices and requirements necessary to the business and IT. Inadequate software and data environments already in place can cause further issues in deploying big data solutions. Smith asserted that having optimal data integration and management processes can empower IT to be more productive and collaborate more effectively with other business departments. However, firms must first identify and evaluate processing capabilities and techniques that will be important to reaching big data objectives. Smith further revealed that according to a survey by Information Management, the most important benefits of big data tools include retaining and analyzing more data (74 percent) and increasing the speed of analysis (70 percent).
The analytics solution to volume
Gartner recently named Oracle as a leader in database management systems (DBMS), based on its ability to support fast analytics in warehouses of all sizes, with large numbers of users and mixed workloads. Data volume management, a capability which Gartner commended Oracle for achieving, is a key function to big data strategies. As a leader in the DBMS market, Gartner revealed that Oracle represents the lowest risk in data warehouse implementations. Oracle has been able to support emerging processes for metadata management, data virtualization and distributed processing, all of which are essential to big data. Gartner concluded that Oracle's data warehouse offerings provide the most thorough, fast, cost-effective and reliable platforms for big data and business analytics.
By using robust database management systems such as those offered by Oracle, firms can better work to reach big data objectives by gaining faster and deeper insight into analytics.
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