Flawed Integration Can Destroy Data Quality and Reliability

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Performance and Scalability

There is an enormous amount of data in our digital world, and companies continue to struggle with what to do with it. One thing we do know is that the amount of data generation shows no signs of slowing. As the quantity continues to grow, performance becomes a bigger and bigger problem.  Algorithms and software systems must retrieve and process data at exceptional speed: Every millisecond counts.

Performance of these systems determines how fast we can mine the data, how fast we can make use of it, translate it, transform it, analyze it, and use it to make decisions. The cloud offers a convenient solution for addressing these concerns and also offering pay-as-you-go models, so businesses only pay for what they use, providing enormous flexibility and scale.

Analyzing large amounts of data across a multitude of business systems enables companies to optimize the performance of the sales team, identify patterns in the industry, or determine the efficacy of marketing. A variety of tools enable organizations to prepare the data, but if the quality is insufficient, it will provide unreliable insights.

Data connectivity and integration can be affected by a variety of factors including how it is entered, stored and managed. Maintaining high-quality data is reliant on regular updating, standardization and de-duplication. However, if these processes are flawed, the data can negatively sway organizational spend and productivity. When evaluating the quality of your organization’s data, a variety of characteristics need to be assessed.

In this slideshow, Paul Nashawaty, director of product marketing and strategy at Progress, looks at key factors organizations must consider to ensure their data remains of high quality.


Related Topics : Vulnerabilities and Patches, Resellers, Broadcom, Broadband Services, Supercomputing

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