Data quality analysts look at complex data and turn it into information and insights to guide business decisions. They also monitor quality and performance control plans to identify problems or ways to improve system and database design. This role requires collaboration with database developers to implement effective automation processes by developing access queries on the SQL platform so that data can be extracted for quality control and accuracy. Data quality analysts typically work full-time in an office environment, often as part of a larger development team. This role is suitable for people who enjoy working with numbers and datasets, have an aptitude for computer systems and software, and have strong analytical skills
Duties and Responsibilities of the Data Quality Analyst
The type of organization a data quality analyst works for will determine the exact roles and responsibilities they will assume. Based on the open positions we have analyzed, the duties of a data quality analyst generally include:
Interpret the data
Data quality analysts interpret the data and analyze the results using statistical techniques. They provide ongoing reports on the effects of different strategies and observe any trends or problems that arise with top management.
Develop and implement databases
This role involves working with database developers to implement databases for more effective data collection and storage, as well as performing data analysis and other strategies to optimize the efficiency and quality of the collected data.
Identify trends
Data quality analysts acquire data from primary or secondary data sources to maintain database systems. They also identify and interpret trends or patterns in complex data sets.
Review the computer reports
This role involves filtering and "cleaning" data by examining computer reports and performance indicators to correct any code problems and verify the efficiency of the data collection processes in place.
Prioritize business needs
Data quality analysts collaborate with management to prioritize business and information needs and identify new processes that will improve implemented systems and define new opportunities.
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