Establish Data Governance as your
Central Foundation

Every company gathers and stores an enormous amount of data every day. Quantity alone is not enough when it comes to using this data as a strategic resource within your company. You need to generate knowledge from this data so that your company can act based on data-driven decisions. The key to success is a central Data Governance you can use to define rules, processes and those responsible for your data management. You then need to make sure this data is available to your employees. Data democratization can help make your employees data literate.

Data Management | MID GmbH

Data Orientation for your Company

Successfully establishing Data Governance and data literacy leads to assurance of data quality so that you can make sense of your data. We recommend a structured meta data management and stable information architecture so that your company can react quickly and reliably when it comes to change. A well thought out strategic concept can make you the master of the following central challenges.

Common Understanding for Data

Clear guidelines form the foundations when it comes to interpreting homogeneous data so that it can be used and compared. We recommend following a Data Governance program to attain a common understanding and to define uniform data terms. This allows everyone within the company to understand a data field.

Define Company-Wide Valid KPIs

A large amount of data is collected in your company. We recommend harmonizing existing KPIs and focusing on company-wide valid global (and local) key figures to get the most out of your evaluation. You require standards for your KPIs to control and optimize achieving your goals. This enables you both a holistic view of your company data and a comprehensive evaluation of data from various sources. Efficient monitoring allows you to make valid decisions based on data and information.

Ensure a Lasting High Level of Data Quality

Data quality is a massive challenge. This normally depends on the accompanying data format in accordance with Data Governance. Your company data should follow the FAIR principle, i.e. it should be findable, accessible, interoperable and reusable. We also recommend that you ensure that data is mapped between various systems so that data exchange runs smoothly. This avoids unnecessary redundancies, sinks costs for data integrations and migrations and enables a high level of quality for your data.

Consistent Data

Common Understanding for Data

Clear guidelines form the foundations when it comes to interpreting homogeneous data so that it can be used and compared. We recommend following a Data Governance program to attain a common understanding and to define uniform data terms. This allows everyone within the company to understand a data field.

Monitoring

Define Company-Wide Valid KPIs

A large amount of data is collected in your company. We recommend harmonizing existing KPIs and focusing on company-wide valid global (and local) key figures to get the most out of your evaluation. You require standards for your KPIs to control and optimize achieving your goals. This enables you both a holistic view of your company data and a comprehensive evaluation of data from various sources. Efficient monitoring allows you to make valid decisions based on data and information.

Data Quality

Ensure a Lasting High Level of Data Quality

Data quality is a massive challenge. This normally depends on the accompanying data format in accordance with Data Governance. Your company data should follow the FAIR principle, i.e. it should be findable, accessible, interoperable and reusable. We also recommend that you ensure that data is mapped between various systems so that data exchange runs smoothly. This avoids unnecessary redundancies, sinks costs for data integrations and migrations and enables a high level of quality for your data.

Step-by-Step Towards a Data-Oriented Company

You can’t just simply collect data and expect this to make you a data-driven company. You need to systematically use the data to be able to derive strategic decisions. We guide you following one approach to provide sustainability. We will help you down your individual path to becoming a data-oriented company – from definition right through to establishing a cultural change.

How we support you

We offer an extensive portfolio of services to help your company become data-oriented. Our experienced data consultants will answer any data-based questions you may have and lead you from creation of a company-wide concept, right the way through to implementation, including technical implementation. Our powerful data modeling tool, Innovator, can also be employed for this.

Establishing Data Governance in your Company

Data Governance forms the basis of successful data orientation and enables data to be understood by everyone within your company. Profit from our many years of experience and our customer-specific approach when it comes to drafting your Data Governance. As data experts, we know all the obstacles to watch out for when it comes to establishing a successful Data Governance. We provide comprehensive support, from designing a concept right the way through to technical implementation and programming individual steps. We would be happy to help you to embed a common understanding for data within the mindset of your employees and increase their data literacy.

Building a Company-Wide Meta Data Management

We use existing systems to help you to build a sustainable Meta Data Management. Together we will create a tailor-made data catalog containing all meta data about reports, key figures and data provision to be employed throughout your company. We will take your individual requirements into consideration when helping you select a suitable data cataloging tool and implementing it successfully within your company.

Traceability of Data Stores

Data lineage starts with taking stock of existing operative systems, as well as including disparate systems (Data Warehouse and Data Lake). Your company's value chain and data structures will become transparent and traceable and can be easily documented. Data graveyards will be uncovered and eliminated. You can easily and clearly display dependencies by taking a 360° look at your data. This will help you to easily recognize ways to optimize and speed up your processes.

Data Warehouse Design

We base our data structure design on your enterprise data modeling. We link your business rules with technical data structures to achieve a technical implementation and documentation of the process chain. This enables a long-lasting process chain which is not dependent on individual employees (Data Lineage), which in turn leads to complex processes being able to be customized and fulfillment of compliance requirements.

Data Warehouse Automation with Data Vault and Innovator

Thanks to its stringent approach, Data Vault is the perfect choice for agile and automated processes. Data lake data can be easily integrated; technical and business interests are clearly separated from one another. This makes Data Vault modeling scalable, flexible, consistent and customizable to the needs of the respective company using it. We would be happy to help you model your Data Warehouse using Data Vault. Our power tool, Innovator, is the perfect tool for the job. A Data Vault model can be partially automatically created in Innovator; your modeling decisions are used to automatically create a part of the model.

Innovator for Information Architects

Do you want a comprehensive overview of your company data? Then use Innovator to visualize your data flows and model your Data Warehouse with Data Vault 2.0. Link your data with your data model and merge it with respective applications and processes. Make your data visible and also demonstrate its value. Innovator also has an interface to the SAP Solution Manager.

MID in Action

Do you want to find out more about Data Governance, data literacy, meta data management and tool-supported implementation of data management? Then check out our exciting blog entries, success stories and posters all to do with this topic.

Technical Article

Coexistence in BI Landscape: Data Warehouse & Big Data Solutions

Read the article to find out when you should employ Data Warehouse & Big Data and how targeted symbiosis allows for optimum use of data. In German only.

READ NOW
Blog Entry

3 ways to analyze & provide data
In German only.

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Webinar

The Path to a Data-Oriented Company
In German only.

SEE WEBINAR

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