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.
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.
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. Our results were published in our business-user friendly Data Quality Dashboard (DQD) application, as well as Excel files for more technical users.
After seeing the successful results of our initial cooperation, the company decided to pursue another data quality project with Ataccama ONE software tools. 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 leverages Ataccama ONE’s complete suite for data quality and governance:
Data Quality Center (DQC) – a powerful, business rule driven engine 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.
Running on top of the DQC engine, there are two user-friendly applications for data stewards and business users:
Data Quality Issue Tracker (DQIT) – allows data stewards to resolve various data quality issues that cannot be managed [or fixed/settled] automatically and require their approval or other manual intervention.
Data Quality Dashboard (DQD) – an application providing a quick, accurate snapshot of the current state of your data, and an excellent tool for tracking data quality trends.
The biotechnology company most appreciated the user-friendly nature of our Data Quality Dashboard, which can be easily used by business rather than technical users.
Find out what’s in your data, from incorrect or missing values to duplicates and more, with our sleek, collaborative cloud application for data profiling—Ataccama ONE Profiler. Join the 20,000+ users who profile their data with Ataccama ONE.
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