Data quality monitoring is a job that's increasingly important in numerous organizations. Every company needs to have a strategy that employs data monitoring to prevent the garbage-in-garbage-out problem.

How do you build a strategy, though? An organization ought to do these four things as it develops a strategy for data quality monitoring.

Identify Organizational Goals

You must clearly identify and state where data fits within your organization's goals. Data monitoring will be a natural extension of the company's vision and purpose. This matters from a strategic viewpoint because it'll affect how quality monitoring fits into your processes. A company that delivers data as a licensed product to third parties is going to have different concerns than a firm that uses data insights in-house for decision-making.

Map Processes

Every company will have different processes for ingesting, analyzing, storing, and deploying data. This will affect where you position data monitoring software in the process. A company that has notable quality issues during the ingestion stage, for example, will want to have data quality monitoring software deployed upfront.

Your strategy should follow the map closely to ensure there won't be any gaps, too. A company might feel comfortable with its data quality monitoring efforts at the start of the process only to overlook issues after producing analysis and reports. You need a strategy that values monitoring at each stage so you can ensure that any poor quality coming in hasn't funneled garbage out.

Resources

An organization's strategy should also make sense relative to its resources. Data quality monitoring software either has to run on the same servers handling the work or adjacent systems on the network. There will be a trade-off in performance unless the organization can commit more resources to speed things up with hardware. Even if your resources are more than up to the job, you need to plan for how data quality monitoring software will go on systems and affect timing.

Criteria, Communication, and Accountability

Finally, a data monitoring strategy has to fit into the organizational culture. You will need to establish criteria so team members understand how the software fits into their jobs. Similarly, you must communicate with your teams about the criteria and the way the software will work. Also, there must be accountability for how different departments implement the strategy. You want to see your strategy make each job easier while also improving outcomes in terms of accuracy, analysis, retrieval, reporting, and decision-making.