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Organization of Data Environments

In the corporate world, processes are increasingly based on large amounts of information that flows and accumulates through the many repositories of data, collected in a variety of ways, with a wide variety of formats, structured or not, and multiplicity of origins – many of which are not controlled by the companies.

For an organization, it is imperative to clearly define how to make the most of the information available. This necessarily begins with understanding the strategy, goals and needs of the business of the company. This alignment should guide the purpose and actions of the enterprise data environment.

Large data environments, whether for Big Data or traditional structures, must be built on solid foundations because the information contained therein will be the basis for planning and executing important actions and studies, such as Business Intelligence (BI), Analytics, CRM and operational processes. However, many companies continue to operate and make decisions without prior knowledge of the actual quality of the data involved, allowing the production of incorrect results that can lead to significant financial losses, as well as disbelief in the systems in use.

The use of large data structures, such as Data Lake, Operational Data Store (ODS) or Data Warehouse, for analytical studies, operational support and strategic and critical decision making for the company’s business, increases the need for these environments rely on valid, trusty, quality and timely information.

Data ingestion, preparation and consolidation are complex tasks, which involve the analysis of information from various sources, captured at different times and by different processes. The Data Quality process in these environments aims to monitor and guarantee the information quality, from its origin through its transformation and consolidation – the so-called Data Preparation. In most cases, data is not ready for use, and needs to be adapted to the different needs of their consumers in the organization.

The growing complexity of enterprise data environments is also represented by the multiplicity of storage technologies and standards available on the market. The choice of data storage technology and standards directly influence the level of suitability for consumption by the different areas in the companies. Data availability for consumption should consider the diverse needs of the consumers, regarding integration, granularity, orientation, format and representation of the information. These factors will contribute decisively to facilitating the use of information and the perception of its quality by consumers.

In addition, such projects must also support the registration of the most diverse metadata, which explains both the meaning of each piece of information and its production flow – the so-called Data Lineage.

Assesso has extensive experience in mapping and designing the data flow in complex environments, in order to stimulate the use of information by the departments of the companies, meeting the quality requirements and allowing the full use of the information in the operational, analytical and strategic areas.