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{oA.Lineage}

Mapping an Information System

Information systems are so complex that teams are no longer able to effectively navigate the flows to carry out the desired investigations. In recent times, domain-oriented Data Mesh architectures have accelerated this state of affairs.

Our multi-technology data lineage, coupled with the analysis of data usage, makes it possible to map systems precisely and continuously.



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Do Data Lineage in DataFlows

Starting from any “data point” of the Information System (a field of a table, a table, a file, a diagram, etc.), {openAudit} allows us to understand its origin, its future and its uses thanks to technical, multi-technological data lineage. The process is dynamic, operated in delta mode, and without breaks: {openAudit} processes views, dynamic procedures, etc.

End-to-end impact analysis

{openAudit} offers a view that allows to instantly know all the uses of a data point in the data visualization layer, ignoring all transformations.

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Complete and instantaneous mapping

{openAudit} allows you, from any data point, to display a complete map of the upstream and downstream flow, from operational sources to data exposure (DataViz, queries), i.e. its uses.

Granular data lineage

{openAudit} allows you to progressively monitor the deployment of data in complex Information Systems, on premise, Cloud, without disruption. Each transformation can be analyzed with “drill through”.

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Use cases

Data Observability, Buzzword or necessity?

BCBS 239: The issue of frequency and accuracy of risk reporting

Cybersecurity: data lineage at the service of data loss prevention (DLP)?

Do Data Lineage in the Data Visualization layer

{openAudit} allows you to understand all of the company's data visualization technologies on a single impact analysis interface. Data lineage in the dashboard can be triggered to highlight the numerous management rules defined there.

Highlighting management rules

{openAudit} performs data lineage in expressions, variables, etc., to precisely explain the management rules underlying the calculation of a dashboard indicator.

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Automatic sourcing of dashboard indicators

{openAudit} analyzes the content of views to identify the physical fields that are the source of a dashboard's data, even if the views are stacked.

A combined impact analysis grid

{openAudit} combines the analyzes of the company's different DataViz technologies in the same grid, which allows the business and IT to carry out exhaustive impact analyses.

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Use cases

Source the data in a dataviz solution