Data plays an important role in any business, allowing them to improve targeting, optimize internal operations, and successfully drive innovation. However, as businesses look to adopt the latest technologies, the accuracy and quality of data has never been more important.
Poor data quality negatively impacts business creating both long and short-term issues which impact your return on investment. Poor data quality can have a ripple effect on an entire organization. The only way a positive business outcome results from poor data quality is when the poor quality data belongs to a competitor.
One of the biggest headaches poor data quality creates is having to go back and fix the errors. If an error is created early within the data collection process, it can easily snowball, taking more time to correct. Time is being spent accommodating and validating errors rather than utilizing data to create innovative business strategies.
Now that more business users understand the role of good data in business success, metadata is commonplace. Without metadata, an organization is at risk for making decisions based on the wrong data. What seem like minor mistakes are often caused by poorly managed metadata and can result in catastrophic outcomes.
Higher quality of data and metadata will enhance the business value in the end. Core goals of metadata strategy should be the development of an enterprise-wide understanding of the intrinsic value of metadata throughout the organization, recognition of the value of metadata to improving data quality, how the organization will use the metadata and what technologies will support their metadata activities.
The accuracy and quality of data is also a huge concern for analysts. Data analysts have found it a cumbersome task to fix erroneous data or changed processes to ensure accuracy prior to analysis. As a result, businesses have taken great efforts to have data warehouses with data quality requirements and they make intensive assessment an integral part of any data project.
If you are building a taxonomy to index your data against, it is very important that the data is of good quality. If your data is good, your taxonomy will be good. That will result in a substantial increase in the quality and consistency of indexing. This all results in making your content findable.
Bad data costs. And just leaving that bad quality data to sit in your system and continually give you degraded information to make decisions on, or to send out to customers, or present to your company, would cost you more than it would have cost to actually deal with that data at the point of entry, before it gets in. The cost gets greater the longer bad data sits in the system.
Melody K. Smith
Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.
