Data Governance

Data-driven decisions without Data Governance? Unthinkable! With Data Governance, we ensure traceability, quality and protection of your data.
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What is Data Governance?

Data Governance describes all processes that aim to ensure the traceability, quality and protection of data. With the effort to use more and more data from different sources for decision making and through the technical possibilities of integration in Data Warehouses or Data Lake, the need for documentation and traceability increases exponentially. Questionable data provides questionable information that is used by automated (AI) processes and provides questionable decisions. Data Governance describes and unifies data, documents data quality and processes, and ultimately protects it from unauthorized use.

Reasons why companies should use Data Governance:

Data quality, traceability and protection are important aspects for the use of data in analytical processes. With the methods and technical tools of data governance, the process of data management is monitored and documented, data assets and sources are documented technically and functionally, and access is controlled as needed. This creates the basis for any decision-making, whether manual or automated by AI / ML.

Completeness

A new key value, a changed source column or simply an error in the system: the reasons for a hard termination of a job, or - even worse - unnoticed incomplete data management are manifold.

Correctness

Technically correct does not necessarily mean functionally correct! Even if data is complete, Data Governance establishes the context by cataloging the data so that users can check and evaluate the technical correctness for the use case.

Origins analysis

The origin of the data ("lineage") is an important criterion for deciding for or against a data asset in a use case. Likewise, the reverse case ("impact analysis") reveals important aspects when it comes to the assessment for properties to be changed.

Access protection

Based on business or technical metadata, manually or automatically, access to data must be managed and controlled, or data must be anonymized or pseudonymized.

Data Governance includes the following aspects:

What is the worth of insights from information if the respective data is dubious? The process of Data Governance therefore comprises several aspects: the responsibility for information is clearly defined by the designation of a "data owner or steward" for each data asset. He or she also determines the rights of access as well as the necessary protection of the data, which is then enforced by the technology. Another aspect concerns data quality: Here, too, the data steward determines the predefined threshold values which the technology tool uses for its measurements.

In order for the information to be usable for everyone, each asset must also be documented, on the one hand technically (see data lineage or impact analysis - often provided by data integration), but especially functionally: what exactly does this asset say, for which analyses has it already been used?


Our services regarding Data Governance

We see ourselves as experts for the combination of design, Data Integration, Data Warehouse / Data Lake, reporting, analysis to Data Science. By looking at the complete architecture, we can develop better processes, meet analytical requirements even more accurately and ultimately create agile systems that deliver valuable information to the business.

Strategy & Architecture

In addition to the pure technical integration, processes must be set, roles in the company defined and goals set. We support you in developing a strategy and approach.

Platform selection

With our expertise, we help you select the technical platform for Data Governance analogous to the defined architecture in the overall context of your Data Lake / Data Warehouse. The integration into existing technology and processes, as well as the goals of the implementation are decisive.

Support of the implementation

After determining the strategy and technology, we can accompany the implementation. This includes communication within the company, determination of the business framework (business terms, access rules, protection), as well as the concrete technical implementation in the tool.

Project Management

Data Governance is hardly like any other topic in the company, cross-functional and essentially characterized by professional cooperation. We take over the moderation and project management to ensure success.

The right vendor for every project:

Are you looking for technical support on Data Governance? We work with technologies and commercial solutions from the following vendors:

IBM

IBM began offering and integrating tools for Data Governance early on as part of its "Information Server" and "InfoSphere" products. QualityStage" was introduced for monitoring data quality, and the "Information Server Governance Catalog" (IGC) was offered for comprehensive cataloging. Together with the focus on the AI platform IBM Cloud Pak for Data, the solutions were integrated, technologically completely changed to new container platform and partly new functions were developed. The "Watson Knowledge Catalog" combines modern AI functions for the recognition of metadata, a data catalog including release and security processes, automatic data profiling and workflows including integration into the AI platform Cloud Pak for Data.

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Microsoft

Besides the possibilities contained in SQL Server in the context of the development of Data Integration, Microsoft offers a solution in the Cloud with the "Azure Data Catalog". Multiple sources are supported and data can be added to a catalog and queried with simple functions. In this way, an overview of data can be created relatively easily and inexpensively, and the tight integration into the Azure Cloud Platform goes without saying.

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Talend

Talend also benefits in the field of Data Governance from good connectivity to numerous source systems. The Talend Data Catalog is a comprehensive solution that is well integrated into the Talend Suite and offers comprehensive functionalities to ensure data quality and compliance. Based on intelligent mapping procedures and Machine Learning algorithms, a central data catalog can be implemented, access permissions can be centrally controlled and traceability of data processes can be ensured.

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Contact us now!

We would be happy to advise you in a non-binding meeting and show you the potential and possibilities of Data Governance. Simply leave your contact details and we will get back to you as soon as possible.

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Martin Clement
TIMETOACT Software & Consulting GmbHcontactpersonhelper.linkProfile.title