A biotech company centralized product and customer data from hundreds of sources to build a robust and business-user friendly data governance solution.
Business objective & project requirements
The biotech company aimed to implement a data governance solution with high quality data at its core. Since the early 2000’s, the organization had been using one primary customer relationship management (CRM) system, together with a number of additional systems to store product data, customer information, and more. They sought to overcome this data storage complexity and achieve data excellence.
- Develop a data solution focused on governance, processes, data content, and systems & technology.
- Implement a data quality tool supporting both rule definition and the execution of quality controls, two critical elements of data governance.
Initial data challenges
- While the amount of data handled by company systems was not an acute issue, certain early data design and definition choices in the company made their data structures more complex than necessary.
- Moreover, input data existed as a variety of types, including bank information, emails, addresses, purchase orders, invoices, company codes, and more. The company estimated that prior to cooperation with Ataccama, 66% of data issues were related to lack of governance, the absence of formalized definitions, and communication difficulties.
Solution & benefits
Ataccama cooperated with the biotech company on the implementation of two data quality projects.
The first project entailed checking the quality of customer and vendor data stored in their systems, as well as data mapping, joining, and the application of data quality rules.
After seeing the successful results of our initial cooperation, the company decided to pursue another data quality project with Ataccama. Given the nature of their biotechnology business, which includes factories for industrial-grade ethanol and a significant number of factory machines producing vast amounts of data, the company sought to take data from 100+ factories and compile it into a single database. Centralizing this data and ensuring that it was of high quality allowed analysts to learn which of their factories were running most efficiently, which were using optimal metrics, and more.
Ataccama successfully implemented a data quality solution which enabled the monitoring and safeguarding of data quality through a series of rules and definitions. Additionally, we generated a key set of documents, models and tools to support ongoing work to improve data quality and to optimize the associated data curation processes—all handed over to the company’s Data Excellence team.
