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Published: March 25, 2021 • 126 Views • Subtitles: EN
In a world where we are increasingly hearing that we are all data-driven, that data is the new oil, and that the future of companies depends on their ability to use correctly the data they have, there is need that is even more important: Data Quality. In order to achieve medium-long term goals of becoming a data-driven company, Unitel SA began to mark the first steps, creating initiatives related to data governance, which includes enhancing its entire architecture of data, technology and application. With all this architecture, it will be possible to maintain the strategy of knowing its customers in detail and, naturally, it will allow C-level to make decisions based on reliable data.
Currently, Unitel.SA uses data from the most diverse sources (internal and external) to enhance a deeper knowledge of the customer and to adapt its offer of products and services to the customer in the best way. Given the growing importance of data in the company, there is a great need for data to be credible, not just available, in order to allow it to add value to the business.
In this sense, we have developed dashboards that support the analytical component of data quality processes, which run over the models of Data Warehouse, which has more than 120TB of data. The data quality dashboards were built based on the KPIs for each data model, defined through the input of the main users and the experience of the support team, allowing to identify the main inconsistencies and the existing information silos. Based on the same dashboards, it is possible to solve the use and origin of inconsistent data (for example, when the reports obtains data different from those present in the source systems or have inconsistent reference data).
For this reason, this document is a proposal on how dashboards can be used as the main data quality- monitoring tool, promoting greater security and reliability in the use of data and bringing to Angola the new reality of the importance of companies becoming increasingly data-driven.