In the age of digitalization and big data, much is about one thing: data. Terms such as Data Mart and Data Lineage regularly catch the eye. It is not always clear exactly what the technical words are, which is why this article should provide a small overview.

What is Data Mart?

Data Marts are a kind of collection point for custom data. It extracts data from large data strains and renuns it accessible in isolation to specific user groups. They thus form a partial segment of a data warehouse and can help to make certain data accessible to the user faster and with less effort. After all, this can save not only time, but also costs.

Data Mart vs Data Warehouse

Both Data Mart and Data Warehouses are used to store and manage records until they are used. Data warehouses specialize in organizing all of a company’s data, while Data Marts organize collection points for the data of individual departments. In this way, they are a tool that isolates certain records and makes them available separately to the respective function field.

Types

Basically, Data Marts distinguishes between 3 different categories.

Depending on

Dependent data marts are always directly related to an enterprise data warehouse by being developed according to the top-down principle. To do this, data is first summarized at a collection point and then extracted certain data sets, which are then distributed in their intended data mart.

Independent

An independent data mart, on the other hand, is not linked to any data warehouse and thus forms an autonomous system. Data is extracted from an organization’s internal and external data sources instead of from the data warehouse collection point and then distributed specifically to the individual data marts. This makes this type of data marts much easier to implement and is especially helpful in tracking short-term business goals.

Hybrid

Hybrid data marts describe connecting dependent and independent data marts in a system by extracting data from a data warehouse, as well as from an organization’s internal and external sources. This allows you to combine the advantages of both methods and create a complex but clear system.

Benefits

Data Mart offers many benefits due to its function as an accelerator when accessing specific data sets.

  • Minimize the time it takes to obtain specific data
  • Significantly faster than an enterprise data warehouse
  • Data Mart requires comparatively little expertise in implementation
  • Affordable alternative to an enterprise data warehouse
  • Data Mart helps improve the performance of a data warehouse by allowing them to obtain data with less effort
  • KPIs are easier to monitor thanks to Data Mart
  • Data Mart supports data maintenance by assigning records to specific departments, which in turn can monitor them independently

What is Data Lineage?

Data lineage plays a role in the origin of data, which is why the term is often used as a synonym. Data Lineage has the task of recording changes as well as optimizations of data as well as the development of their elements in a history. In doing so, it tracks a data set on its journey from creation to adaptations to the final destination and at the same time documents the corresponding properties. In simple terms, data lineage can therefore be imagined as a kind of biography of a data set.

Benefits

With its function, Data Lineage offers many advantages for the user.

  • Data can be monitored at any time and completely
  • Increased visibility into the development and history of data sets
  • Quality of data is maintained
  • Helpful when it comes to sensitive data that needs to be protected
  • Businesses can more easily adhere to data-based standards and regulations using data lineage

Beyond Data Mart and Data Lineage

The following articles also provide information on data and big data:

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I blog about the impact of digitalization on our working environment. For this purpose, I present content from science in a practical way and show helpful tips from my everyday work. I am a manager in an SME myself and I wrote my doctoral thesis at the University of Erlangen-Nuremberg at the chair of IT Management.

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