Data Quality Fundamentals

Data Quality Fundamentals

Data quality is not necessarily data that is devoid of errors. Incorrect data is only one part of the data quality equation. Managing data quality is a never ending process. Even if a company gets all the pieces in place to handle today’s data quality problems, there will be new and different challenges tomorrow. That’s because business processes, customer expectations, source systems, and business rules all change continuously. To ensure high quality data, companies need to gain broad commitment to data quality management principles and develop processes and programs that reduce data defects over time.

Much like any other important endeavor, success in data quality depends on having the right people in the right jobs. This course helps you understand key concepts, principles and terminology related to data quality and other areas in data management. 

Understand key concepts, principles and terminology related to Data Quality.

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What you will learn

• Determine data quality requirements by studying business functions, gathering information, evaluating output requirements and formats.
• Profile select data sets to ensure quality and develop the data visualizations necessary to both manage and communicate data quality.
• Coordinate business efforts to deliver data that is fit for use for use in critical processes, analysis and reports.

Rating: 4.07143

Level: Beginner Level

Duration: 3 hours

Instructor: Sid Inf