Take care of the data quality before it becomes a problem

The more data you have, the more accurate your predictions and decisions will be. But it’s not just the quantity that matters, it’s also the quality of the data, right? What data parameters are of priority if we are talking about business intelligence (BI)? The main ones include the following:

• Credibility. The data you use must have the correct value, dimension, source.
• Completeness of coverage. For each element, all fields of the corresponding form must be completed.
• Exact lineage. Some datasets flow from others and flow into others through various pipelines. As they move, derived tables must accurately inherit the reference data in their parent tables in both structure and value.
• No duplicates. Duplicate data greatly increases the cost of storing it, and also becomes a source of errors.
• Relevance. Your data also has validity. In some areas it is measured in years, while in others it is measured in hours.

If you own really huge stacks, you won’t be able to control data quality manually. The process needs to be automated.

1. The observability platform by Masthead is a professional real-time data quality monitoring solution

An out-of-the-box ML algorithm allows controlling over all of the above data quality parameters. You get a flexible tool:

• You set up thresholds.
• You set the priority for tables, thereby reducing the number of alarms.
• You choose a convenient communication channel.

Data security is as important as its quality. This algorithm uses logs in its work without affecting the data itself. This is a HIPAA-compliant tool.

No installation is required as you get a zero-code integration tool. Setup takes no more than 20 minutes. 

You might want to know more about automatic data quality monitoring by Masthead. This is easy to do by clicking on the link to their website.