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.
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.
The organization utilized the Ataccama ONE platform module for Data Quality Management. Ataccama ONE DQM is a powerful, business rule-driven platform module for complex data curation that enables you to transform, standardize, cleanse, validate, correct, and enrich your data, and prevent incorrect data from entering your systems.
A biotech company centralized product and customer data from hundreds of sources to build a robust and business-user friendly data governance solution.
Крупная фармацевтическая компания согласовала данные в исходных системах с их существующим центром данных, очистила основные данные и улучшила качество всей информации в организации.