How to Become a Data Quality Analyst

摘要： Data quality refers to the planning and implementation of quality management measures for the data that companies generate.

Data quality refers to the planning and implementation of quality management measures for the data that companies generate. The idea is that the data should fit the end goal of the data consumer’s needs – and must follow specific quality dimensions to be deemed fit for use. The role of a data quality analyst (DQA) is to ensure that the data being stored and passed on is in line with what the organization needs. A prerequisite to being a data quality analyst is being adept at using quality management techniques.

Data quality analysts have been common in the information technology (IT) sector for a long time, but they’re becoming more prevalent in the data space now. The need for such a role arose when businesses started to notice that despite having all the necessary measures in place, they still had poor-quality data seep into their systems, resulting in a tremendous waste of time and resources. The role of a data quality analyst was introduced to avoid this.

The most important part of a data quality analyst’s job is ensuring that the incoming data aligns with the business’s objectives. Since most companies have vast amounts of incoming data from different sources, it can be difficult to understand which ones can be used for the larger organizational goal and which can’t.

Let’s look at the responsibilities of data quality analysts and the skills they need to thrive in the role.

轉貼自： dataversity.net

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