dcsimg

Flawed Integration Can Destroy Data Quality and Reliability

  • Flawed Integration Can Destroy Data Quality and Reliability-

    Maintaining High Quality Data

    Click through for five key factors organizations need to consider to ensure their data quality remains high and reliable, as identified by Paul Nashawaty, director of product marketing and strategy at Progress.

1 | 2 | 3 | 4 | 5 | 6 | 7

Flawed Integration Can Destroy Data Quality and Reliability

  • 1 | 2 | 3 | 4 | 5 | 6 | 7
  • Previous
    Flawed Integration Can Destroy Data Quality and Reliability-1

    Maintaining High Quality Data

    Click through for five key factors organizations need to consider to ensure their data quality remains high and reliable, as identified by Paul Nashawaty, director of product marketing and strategy at Progress.

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.