Data terms and concepts

Those of us who have been around for a while have seen a fair number of data-related terms and concepts come and go. If you are new to the world of data, this article can help you avoid confusion.

The terms

The analyst firms and vendors sell a vision through the terms that emerge. We can safely say that there is value in controlling the definition of terms. And there have been many over the years.

Here are the most important terms:

Business Intelligence

Back in the 1970s, we got Management Information Systems, or MIS, which later became Business Intelligence, or BI. Most people associate BI with reports and dashboards. But does the term not actually mean intelligent business operations, or business operations where we have complete oversight? The intention behind the term was that we should understand how the numbers drive change and learning, and not merely manage a tool (such as Power BI).

Business Analytics

Business Analytics, or BA, never achieved the same popularity as BI. Directly translated, this is of course business analysis, but as far as we are aware, it was used to mean the same thing as BI. In other words: Business Analytics as a term did not quite stick.

Big Data

Big data, Data lake and Hadoop were hot between roughly 2013 and 2017, and data modelling almost disappeared in the same period. All three are now dead terms. Today, large (and small) data is used everywhere. We all use data as a matter of course, and we have the technical capabilities to handle it all.

Data lakehouse

Data lakehouse as a term was introduced by Databricks, and was supposed to be the best of both the data warehouse and the data lake. And it is, in a way, until the next term comes along. Data modelling became hot again, by the way.

Data warehouse

The data warehouse has been around since the 1980s, but has now perhaps found its renaissance. However, it is often referred to instead as a data platform or data lakehouse. But it is more or less the same thing. Alright then – there is a bit more to it, but the modelled data in a data platform is more or less the same.

Data mesh

Weaving data – similar to the World Wide Web, but with data. It is called a sociotechnical concept, but that can feel a bit too abstract. We agree that much of what the data mesh term represents is established good practice, and that it has been elegantly articulated.

Data Fabric

Weaving data into a fabric. Or a technical integration architecture and data platform? Hard to say. Gartner fought hard, but lost, as far as we are aware. We do not know many people who spend much energy on this term.

Microsoft Fabric

This is not the same as Data Fabric. But it could certainly be a technology that helps to realise Data Fabric. Or Data Mesh.

Related content

Few people have an overview of everything that has happened in data over the past 30 years. If you are someone who would like to see a timeline of the development, this is the article for you.

Want to learn more?

Listen to the podcast “Datautforskerne”, episode 1 where Ole Olesen-Bagneux and Magne Bakkeli discuss data terms and concepts. The episode is available on Spotify, Apple and Acast.

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