Partnering for data quality

Author Vlad Rișcuția is joined for this article by co-authors Wayne Yim and Ayyappan Balasubramanian.

Why data quality?

Data quality is a critical aspect of ensuring high quality business decisions. An estimate of the yearly cost of poor data quality is $3.1 trillion per year for the United States alone, equating to approximately 16.5 percent of GDP.¹ For a business such as Microsoft, where data-driven decisions are ingrained within the fabric of the company, ensuring high data quality is paramount. Not only is data used to drive, steer, and grow the Microsoft business from a tactical and strategic perspective, but there are also regulatory obligations to produce accurate data for quarterly financial reporting.

History of DataCop

In the Experiences and Devices (E+D) division at Microsoft, a central data team called IDEAs (Insights Data Engineering and Analytics) generates key business metrics that are used to grow and steer the business. As one of its first undertakings, the team created the Office 365 Commercial Monthly Active User (MAU) measure to track the usage and growth of Office 365. This was a complicated endeavor due to the sheer scale of data, the number of Office products and services involved, and the heterogenous nature of the data pipelines across different products and services. In addition, many other business metrics, tracking the growth and usage of all Office products and services, also needed to be created.