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Sap Master Data Governance
Business data governance is a very important subject that is often neglected, even though it is paramount for efficient data integration. Taking care of data governance means carefully defining data usage and management, agreeing to processes for handling data issues and boosting the quality of your data so your business decisions are based on real, correct and up-to-date assets. Having the right technologies, smart tools and the right people with you during this data governance process is the key to success.
Road Map Webinar: Sap Master Data Governance
Understand the vision and road map that define how SAP Master Data Governance provides essential support for business process efficiency, trusted business analytics, and emerging needs stemming from business networks, cloud deployments, and digital transformation. Understand how SAP Master Data Governance supports your SAP S/4HANA road map, and get a preview of planned innovations.
Note: This webinar is hosted by SAP. For questions, contact .
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What Is Sap Master Data Governance All About
The following videos provide quick insight into the concept and benefits of SAP Master Data Governance.Watch the videos introducing SAP Master Data Governance from a business perspective, it takes no more than 3 minutes .
Video 1: Introducing SAP Master Data Governance
The first video describes the impact of poor master data across the enterprise and outlines how SAP Master Data Governance can help to get and keep your customer, supplier, material, financial and technical asset data ready-to-use for excellent business operation and analytics. And this is valid also in hybrid landscapes consisting of on-premise and cloud systems. Check the SAP Master Data Governance introduction video out on SAP.com:
Video 2: Introducing Consolidation with SAP Master Data Governance
The second video focuses on the consolidation capability of SAP Master Data Governance which has first come with SAP MDG release 8.0, and substantially enhanced with the current release MDG 9.0. With this capability, SAP MDG tackles the challenge of consolidating master data that is spread across heterogeneous system landscapes. As of release SAP MDG 9.0, consolidation is available for business partner , material data and custom objects. More details can be found in this presentation.
Video 3: Master Data Governance for Technical Assets
Video 4: Master Data Governance for Retail and Fashion Management
What Is Master Data Governance In Sap
What is SAP Master Data Governance?
SAP Master Data Governance is an established master data management solution that provides domain-specific master data governance. It centrally creates, distributes, changes, or consolidates master data across your complete operation system structure.
SAP MDG ensures data integrity across both SAP and non-SAP systems. It is an integrated foundation for optimized business processes resulting in higher productivity with trusted data. One of the results is that it ensures consistency, saves time and money.
Why Master Data Management?
Poor master data can cost companies a fortune, the users are frustrated, their systems get blocked and, reports are incorrect. More than half of the CFOs want access to clean data to sustain their decision-making better. Yet, less than 30% of most companies can evaluate the value of this data. Almost 70% of data users at the management level suffer inaccuracies or disparities in the data they use. The numbers represent themselves although, there is still a long way to go. Data quality is a worry for all units of a company. Robust master data is a competitive benefit.
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Keeping The S/4hana Project Within Budget And On Schedule:
- Utilize independent risk assessment for checks & balances
- Include key stakeholders early in the project
- Involve superusers early in the project
- Adopt a change management strategy that builds momentum and leverages ability to bridge the gap between the as-is and to-be organizational/operational states
Regardless of where you are at in your SAP and enterprise systems journey, we want you to know that BCTG is here to help. Whether that be through leveraging our network of technical and functional consultants, or through simply having a human conversation, we welcome the opportunity to become an extension of your team. Situation:Objective:Approach:Outcomes:industry insight. Five phases of Activate Methodology:
The SAP Activate MethodologyRegardless of where you are at in your SAP and enterprise systems journey, we want you to know that BCTG is here to help. Whether that be through leveraging our network of technical and functional consultants, or through simply having a human conversation, we welcome the opportunity to become an extension of your team. Please call us to help you 1. BI/BW/Embedded Analytics2. SAP Fiori4. SAP IBP
Questions Related To Sap Master Data Governance Cloud Edition An Its Role In The Overall Sap Master Data Governance Solution Portfolio
Does SAP Master Data Governance, cloud edition replace SAP Master Data Governance on S/4HANA?
No. SAP Master Data Governance, cloud edition extends the solution portfolio. On the one hand, it enables companies to kick-start master data management initiatives at low entry barriers, and, on the other hand, it provides a non-disruptive additional deployment option for companies that run SAP MDG on S/4HANA implementations but see a need for a federation of governance. Companies that do not opt for a federation of governance, that is, aim at or continue with managing core and application master data in a central hub simply go with SAP MDG on S/4HANA.
Is the concept of data ownership planned to be introduced in SAP Master Data Governance on S/4HANA on-premise?
he data ownership concept is incorporated in the Master Data Orchestration layer, which is part of SAP Master Data Integration. Therefore, all participating applications including SAP MDG on SAP S/4HANA on-premise will benefit from the concept of ownership.
Why has SAP Master Data Governance on S/4HANA, essentials edition not been chosen as the cloud solution going forward for enterprise MDM?
Is there any roadmap information about SAP Master Data Governance, cloud edition?
Roadmap information for all MDG deployment options is available on the SAP Roadmap Explorer.
Do SAP Master Data Governance, cloud edition and SAP Master Data Governance on S/4HANA target the same master data objects?
SAP Master Data Governance on S/4HANA
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Transformational Effects After Receiving The Roadmap
The client now had a clear roadmap to implement its Master Data Governance framework, alongside a roadmap to implement new analytics infrastructure and services.
Estimates contained within both roadmaps could feed into the clients planning and budgeting exercises, managing capital expense and monetary risk.
Clear business values were established across both roadmaps in specific areas, giving the green light to stakeholders with a proof of value statement.
A clear methodology towards harmonizing both SAP instances was provided, offering guidance on resources, budgets, and roadmap constraints.
Why Bother With Managing Master Data
Because master data is used by multiple applications, an error in the data in one place can cause errors in all the applications that use it.
An incorrect address in the customer master might mean orders, bills and marketing literature are all sent to the wrong address. Similarly, an incorrect price on an item master can be a marketing disaster and an incorrect account number in an account master can lead to huge fines or even jail time for the CEOa career-limiting move for the person who made the mistake.
Real Life Master Data Example: Why You Need Master Data
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Lack Of Centralized Maintenance
Low master data quality may translate into incorrect payments, wrong delivery times, missed orders and other issues. With data volumes growing consistently, maintaining high quality master data becomes cumbersome. SAP employs decentralized data model where various line of businesses can maintain the same master data, creating their own specific view. A central master data team can maintain and ensure up-to-date master data but that introduces delay in the process and any deviation can cause inconsistent data as well.
Reduced Effort In Generating Insights
Maintaining accurate master data ensures that you spend a lot less effort on transactional data maintenance. For every order the buyer raises, he already knows what the price is, who the supplier is and what the lead times are etc. The objective is to reduce non value adding activities in form of acquiring and cleaning the data stemming from a poorly maintained master data plagues with inaccuracy, duplicate records and inconsistencies. Executives can generate insights faster and put their effort elsewhere e.g negotiations.
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Our Offer At A Glance
Incorrect handling of master data can cause considerable problems. The correct creation, maintenance, administration and distribution of master data are therefore essential. We will be happy to tell you what you can do.
Higher data quality and clear assignment to a central location, faster processes, simpler management, low costs – the advantages of SAP MDG are convincing. When do you benefit from it?
SAP MDG is easy to integrate into existing systems. The platform can also be implemented in non-SAP systems. And even customer-specific extensions are possible. Would you like to know more?
Are you interested in SAP MDG? GAMBIT develops and implements SAP-MDG solutions, so that you can use the advantages of harmonized master data as fast as possible. One call is enough – and we get to work.
Jochen Knösels, Senior Project Manager
+49 2241 8845-616
Data Management Guidelines Policies And Standards
Guidelines, policies and standards define how quality is measured, how data is documented and how the data life cycle managed. But most importantly, they comprise documents that define, how to create and maintain data correctly. For each data domain, they describe the key data objects with permitted values for the data attributes. For example, if we have a German postal address, is it permitted to shorten the word street to Str. or is it mandatory to write Strasse? Similarly, should the legal form of the company be part of the name or not? These guidelines are relevant for the entire data life cycle and for all systems in which the data is stored or used. Good guidelines, policies or standards are the foundation for high-quality data that is also harmonized across the company. The key to success is to train the organization and to monitor whether users adhere to the rules. Some rules defined in the guidelines can probably also be coded as validation rules into the IT systems.
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Master Data Management Steering Committee
Its recommended that management-level representation from the MDM stakeholders form a Steering Committee to facilitate cross-functional decision-making. Here are a few characteristics of an effective Steering Committee:
- Be sized appropriately Big enough to represent the priority stakeholders, but small enough to quickly analyze key information and make decisions.
- Focused on fast decision-making
- Become a vehicle for removing organizational barriers and not simply a regular meeting for listening to reporting from the Project Team members
- Not be a substitute for hands-on Sponsorship
Once the stakeholders are identified, the MDM Project Charter should include formation of a Steering Committee. Based on running hundreds or MDM projects, Profisee recommends the following roles participate in the Steering Committee. Note that there may be more than one team member per role, or some roles may not be applicable or a companys organizational structure.
Cleaning And Standardizing Master Data
Before you can start cleaning and normalizing your data, you must understand the data model for the master data. As part of the modeling process, you should have defined the contents of each attribute and defined a mapping from each source system to the master data model. Now, you can use this information to define the transformations necessary to clean your source data.
Cleaning the data and transforming it into the master data model is very similar to the Extract, Transform and Load processes used to populate a data warehouse. If you already have ETL tools and transformation defined, it might be easier just to modify these as required for the master data instead of learning a new tool. Here are some typical data cleansing functions:
- Normalize data formats: Make all the phone numbers look the same, transform addresses and so on to a common format.
- Replace missing values: Insert defaults, look up ZIP codes from the address, look up the Dun & Bradstreet Number.
- Standardize values: Convert all measurements to metric, convert prices to a common currency, change part numbers to an industry standard.
- Map attributes: Parse the first name and last name out of a contact name field, move Part# and partno to the PartNumber field.
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How Should You Merge Your Data
Most merge tools merge one set of input into the master list, so the best procedure is to start the list with the data in which you have the most confidence and then merge the other sources in one at a time. If you have a lot of data and a lot of problems with it, this process can take a long time.
PRO TIP: You might want to start with the data from which you expect to get the most benefit once its consolidated and then run a pilot project with that data to ensure your processes work and that you are seeing the business benefits you expect.
From there, you can start adding other sources as time and resources permit. This approach means your project will take longer and possibly cost more, but the risk is lower. This approach also lets you start with a few organizations and add more as the project demonstrates success instead of trying to get everybody on board from the start.
Because of implications around privacy, you might want to add a lawyer to your MDM planning team.
The next section provides some options on how to do just that.
A Varied Agenda At Sap Mdg Summit 2021
The agenda of the SAP MDG Summit 2021 holds exciting discussions, presentations and field reports from the master data environment. Speakers include experts from SAP and IBsolution as well as master data specialists from well-known companies who will report on how the implementation of SAP MDG can be achieved in a short time with the help of predefined processes, how data migration projects can be successfully implemented, and why the future of SAP master data management lies in the cloud.
The SAP MDG Summit 2021 will start with the keynote Data quality management in the cloud with SAP by Alexander Röckle. The Head of Platform & Technologies at SAP Germany will give an insight into SAPs future master data strategy and present the current roadmap. Afterwards, the three companies Hirschmann Automotive, ZF Friedrichshafen and EagleBurgmann report on how they have successfully mastered the challenges in the area of master data management in joint projects with IBsolution.
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What Is Sap Master Data Governance Cloud Edition
SAP Master Data Governance, cloud edition is a complementary deployment option.
Find questions and answers about SAP Master Data Governance, cloud edition, including information on how it is embedded in the overall MDG solution portfolio , how it can enable greenfield master data management projects to kick-start their initiative at a low entry barrier and, if needed, allow existing MDG on S/4HANA customers to increment to a more modular set-up in a non-disruptive way.The questions are clustered according to the topics of Integration, Portfolio and Roadmap, Concept of Federated Governance, and Implementation and Use Cases.
SAP Master Data Governance, cloud edition has been available as a public trial version since February 2021. It is generally available as of May 22, 2021.
Business Challenges For The Client With Sap
The client had implemented SAP around twelve years prior to engaging with Trianz. This system supported all aspects of the enterprise resource planning process, alongside an acquired business arm from six years prior.
After the acquisition, the acquired businesses SAP instance was not harmonized with the main SAP implementation, creating redundancies and siloed datasets that prevented holistic reporting.
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