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Duplicated. Corrupted. Incomplete. Absent. Late. If any of these adjectives apply to your most important information, you might just have a data quality problem.

While the business impact of poor data quality can be frightening, the benefits of high data quality are just as enticing. From decision efficiency to business execution, Aberdeen Group’s recent data quality report demonstrated some of the tangible benefits that quality data can bring to an organization. The research also suggests that in order to get to a higher level of data quality, organizations should focus on three key activities.

Data preparation

As much of a philosophy as a technology platform, data preparation activities are designed to be more approachable for a less technical audience. From integration to data profiling and deduplication, most of these activities are purpose-built to improve data quality and streamline the process of analysis.

Diversity of data usage

Duplicated, incorrect, or corrupted data are all significant issues for organizations, but so is data absence. A major factor in user satisfaction is the ability to access the data needed to perform the analysis wanted. Sometimes traditional internal structured data is sufficient for these purposes, but other times, they may need to pull unstructured data from social channels, sensor-generated machine data, or a variety of other data types. Best-in-Class companies are much more likely to empower their users with a wide assortment of data.

Data sharing and collaboration

Building on the previous point, a major factor in data quality is the completeness and richness of the data available. It’s one thing to have access to systems and data sources in different functional areas of the business; it’s another to share insight and knowledge born out of analyses performed elsewhere in the company.

According to the research, organizations having high data quality also reported strong performance in these three areas:

Key Factors Contributing to Data Quality
1

Real and repeatable business results 

Poor data quality may lead to impediments in the decision process, misguided conclusions, and missed business opportunities, but high data quality leads to equal and opposite results. Companies reporting strong data quality experienced an accelerated decision process, more accurate analyses, and tangible business performance. As nice as it would be to blink and see improvement in data quality, top-performing companies recognize its vital importance and are willing to sink time and resources into its improvement.

Best-in-Class companies blend a variety of internal capabilities, processes, and technology deployment to help improve the quality and usability of their data. Between data preparation activities like profiling and cleansing, and strong data governance policies, these top performers enjoy a more frictionless transition from raw data to usable insight, and are able to deliver real and repeatable business results.

For more information, explore the related research report: The Three Levels of ROI from Data Quality Initiatives.

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