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The Business Glossary: the key repository for keeping the promises of Artificial Intelligence

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On the other hand, regulatory pressure forces companies to standardize and secure the storage, access, and use of data. It is therefore a real business opportunity for companies to use the data they collect as a strategic asset to make impactful business decisions and drive business growth.

The business glossary: an innovative tool for companies

In this context, the business glossary is the basis for setting up a data-driven corporate approach. It is a dictionary of business concepts, which contains both the definitions of business terms and the mapping of the distribution of these terms in the IS.

Although it is seen as a dictionary, the business glossary is much more than a simple primer of keywords, because it contains all the critical data for the company. By defining terms from different sources, this tool allows businesses to have a unified view on a given subject, and on all related concepts that could provide additional value.

For example, a "customer" is defined differently in different departments of a company. And the information relating to this customer is generally dispersed in several systems like the CRM, invoicing, data lake, etc. The business glossary makes it possible to unify this information, which is synthesized in an easily accessible and readable format. Using one single source is how inconsistencies are avoided and collaboration is facilitated.

The business glossary also provides simplified access to new sources of data resulting from digital transformation: customer journey, customer opinion, and customer sentiment. These innovative data combined with the usual data are the lever of creativity of the Data. Thus, the glossary promotes innovation and business performance by providing businesses with unified, clear, connected, and up-to-date information. This powerful tool also makes it possible to break down information silos.

A common automated data repository that drives performance

However, the mapping function should not be confused with a Data Catalog, which is the inventory of all technical data within the systems. The business glossary is the inventory of all business data. However, the Data Catalog remains intrinsically linked to the process of creating a business glossary.

During an innovation process, the business will identify the most relevant data (Data Shopping) at the business level first, via the business glossary. The link to the technical data will then be relevant and indicate to Data Scientists which target systems will collect the necessary data.

The business glossary is the repository of information that characterizes a company in its sector at a given time, but its content must evolve at the same time as the business context and as the company transforms and changes. Therein lies the real difficulty in keeping it up to date.

Being one of the foundations of data governance, the business glossary must be the subject of the greatest care during its creation and evolution, because it directly impacts the work of Data Scientists and their outcomes and results. This is why quality information and accurate data is essential to the performance, success, resilience, and innovation of organizations.

 

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On the other hand, regulatory pressure forces companies to standardize and secure the storage, access, and use of data. It is therefore a real business opportunity for companies to use the data they collect as a strategic asset to make impactful business decisions and drive business growth.

The business glossary: an innovative tool for companies

In this context, the business glossary is the basis for setting up a data-driven corporate approach. It is a dictionary of business concepts, which contains both the definitions of business terms and the mapping of the distribution of these terms in the IS.

Although it is seen as a dictionary, the business glossary is much more than a simple primer of keywords, because it contains all the critical data for the company. By defining terms from different sources, this tool allows businesses to have a unified view on a given subject, and on all related concepts that could provide additional value.

For example, a "customer" is defined differently in different departments of a company. And the information relating to this customer is generally dispersed in several systems like the CRM, invoicing, data lake, etc. The business glossary makes it possible to unify this information, which is synthesized in an easily accessible and readable format. Using one single source is how inconsistencies are avoided and collaboration is facilitated.

The business glossary also provides simplified access to new sources of data resulting from digital transformation: customer journey, customer opinion, and customer sentiment. These innovative data combined with the usual data are the lever of creativity of the Data. Thus, the glossary promotes innovation and business performance by providing businesses with unified, clear, connected, and up-to-date information. This powerful tool also makes it possible to break down information silos.

A common automated data repository that drives performance

However, the mapping function should not be confused with a Data Catalog, which is the inventory of all technical data within the systems. The business glossary is the inventory of all business data. However, the Data Catalog remains intrinsically linked to the process of creating a business glossary.

During an innovation process, the business will identify the most relevant data (Data Shopping) at the business level first, via the business glossary. The link to the technical data will then be relevant and indicate to Data Scientists which target systems will collect the necessary data.

The business glossary is the repository of information that characterizes a company in its sector at a given time, but its content must evolve at the same time as the business context and as the company transforms and changes. Therein lies the real difficulty in keeping it up to date.

Being one of the foundations of data governance, the business glossary must be the subject of the greatest care during its creation and evolution, because it directly impacts the work of Data Scientists and their outcomes and results. This is why quality information and accurate data is essential to the performance, success, resilience, and innovation of organizations.

 

Key steps to implement an effective data governance program banner.png