Data monitoring represents a notable commitment for any organization. Fortunately, data quality monitoring software often provides a cost-effective way to automate much of the process. If you're not sure whether your organization is the kind that needs data monitoring software, consider whether it fits one of these four types.
Marketing and Customer Service
Today's marketing and customer service operations tend to lean heavily on databases. If a company sends direct mail products to potential customers, for example, they don't want to waste money mailing items to the wrong people or locations. Consequently, they should have data monitoring software running to prevent simple errors on their lists.
On the customer service side of the ledger, many businesses need to know a lot about the people they're helping. If a company is tracking warranties on equipment, for example, they don't want to irritate customers by losing track of them. If someone calls your company to complain about a product, the person fielding the call needs to identify them in the database as quickly as possible. Otherwise, you'll risk losing the customer due to frustration when the customer service rep is trying to work with flawed data.
Organizations often use business intelligence systems to analyze data and produce insights and reports. Your analysis, though, will never be better than the quality of the data.
Suppose you've downloaded a large spreadsheet from a government statistics website. However, the data isn't formatted to the way your analysis tools handle things. Data quality monitoring software can recognize missing or flawed information. The software can then use established patterns to repair the data so you can analyze it.
Increasingly, data is a product in its own right. Companies often ingest data and present it to the general public or specific customers.
For example, an environmental group might have a website that presents geospatial data about the local impacts of industrial operations. That group stakes its reputation on presenting advocacy data faithfully and accurately. Consequently, it needs good data monitoring practices to avoid delivering low-quality work products.
Many businesses also ingest data for tracking purposes. A trucking company might have a database to monitor its fleet for issues with fuel economy and maintenance, for example. Buggy data could send up unnecessary red flags and ultimately defeat these cost-saving efforts. Data quality monitoring tools, though, can identify and address issues before they go into the tracking system's dashboard.
If your business could benefit from data monitoring software, be sure to reach out to a professional.