The definition of Business Intelligence is born from the knowledge of what is Data Management. According to Barbieri (1994, apud SERRA, 2002), data management can be defined as a function of the organization responsible for centrally developing and managing strategies, procedures, practices and plans capable of providing the necessary corporate data, when necessary, covered with integrity, privacy, documentation and sharing.
Data Management has a very broad operation and participates in organizational strategic planning, detects future information needs, plans the databases to meet the organization’s business and manages all of the organization’s data (even those non-computerized). However, for Serra (2002), Data Management has changed its name and is now labeled “Business Intelligence”, however, the purpose and characteristics remain the same. The truth is that the term BI encompasses a variety of software and practices that facilitate decision-making (operational, tactical or strategic) by analyzing information of responsible quality.
Business Intelligence represents a great potential for organizational change and, for this reason, has inherent challenges in its implementation due to human resistance to change. Thus, cultural and technical challenges can pose threats and opportunities. One of the key challenges for the BI project is the issue of data quality, which must be clean and consistent to substantiate the information that will be generated. In this way, it is necessary to be certified that the data that feed BI have these attributes (cleanness and consistency) so that the information generated is reliable. The need for data cleansing and consistency used in BI is addressed in the data staging phase of the Data Warehouse, of which the BI tools are part.
We educe from Serra (2002) that there are some important factors to be considered in Business Intelligence. Among them are the relationship between data, information and knowledge, the data quality, the information quality, the relationship between operational information and managerial information, and the adequacy of information to business needs.
Text: Pedro Carneiro Jr.
Revision: Luis Cláudio R. da Silveira
These are the posts on the same “Enum and Quality in BI” monograph:
- When to use Enums?
- About The Software Design Science – Part 1 of 2
- About The Software Design Science – Part 2 of 2
- About Business Intelligence (BI)
- About Business Intelligence: The Relationship Between Data, Information and Knowledge
- About Business Intelligence: The Quality of Data
- About Business Intelligence: The Quality of Information
- About Business Intelligence: The Relationship Between Operational Information and Managerial Information
- About Business Intelligence: The Adequacy of the Information to the Business Needs
Our future posts that complete the current “About Business Intelligence” theme will be:
- About Business Intelligence: Data Warehouse
This short text is a mere Portuguese to English translation from part of my monograph “THE PERSISTENCE OF ENUMERATIONS IN POSTGRESQL DATABASES AND QUALITY IN BUSINESS INTELLIGENCE” (free translation of the title), also aliased as “Enum and Quality in BI”, which corresponds to a minor part of the document structure.
- SERRA, Laércio. A Essência do Business Intelligence. 1ª ed. São Paulo:
Berkeley, 2002 – https://www.skoob.com.br/a-essencia-do-business-intelligence-154218ed172085.html, ISBN-10: 8572516301.
- “The Commons”, Flickr.com / Internet Archive Book Images – https://www.flickr.com/photos/internetarchivebookimages/14583229327/sizes/l/