Meet master data experts from Camelot Consulting Group at one of the finest Enterprise Information Management event of the year, presented by ASUG. ASUG Experience for Enterprise Information Management in Chicago is an event that allows professionals in the EIM space to connect with their community, learn about the latest technologies, and discover new opportunities for leading their business to success.

Camelot is one of the leading MDM consulting companies. Our specialists will be providing a variety of demos and presentations throughout the event. Meet us at our booth and be sure to attend our presentation “The Future (and Present) of ML and AI in Master Data Management” (EIM28), from 12:45 – 1:15pm on Wednesday afternoon .

Learn more about the hot topics and key themes in our series “10 reasons to meet Camelot @ ASUG EIM”. We’ll be sharing a new reason every week leading up to the event, including the many benefits, best practices, innovations, concepts and approaches offered by Camelot.


Marc Hoffmann
Marc Hoffmann
Head of Enterprise and Information Management

Want to hear more? Schedule a meeting with a Camelot consultant on-site at ASUG EIM. We look forward to meeting you!

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#1 Exchange with peers, experts and researchers in the Global AI in MDM Community

Camelot founded and facilitates the Global Community for Artificial Intelligence (AI) in Master Data Management (MDM). The community is designed to foster systematic knowledge transfer and exchange with other companies, researchers and experts.

Community members are provided with continuously updated content, comprising interesting lectures, latest research information, innovative use cases, lessons learned and how-to guidance.

Furthermore, design thinking workshops will be conducted in Europe and the United States of America to ensure continuous inflow of new ideas. The workshops also offer the chance to share thoughts and ideas as well as challenges that will be discussed within the community. Benefit from this great opportunity to find partners for co-innovation joining forces in the endeavor to bring first AI & MDM light house uses cases to life.

Get more information and join the community now at

#2 Learn about Next Level DQM - Value Driven Data Quality Management

Data Quality is not determined by the quality of data itself or data objects but by the reliability of processes that are utilizing this data.

Camelot developed a process centric approach that analyzes core business processes consuming master data and set them in relation to transactional information of this processes.

The approach is an evolution of the classic DQM approaches and provides a more accurate measurement of data quality and allows to prioritize data quality remediation activities based on assessment of financial risk resulting from bad data quality.

#3 Decode the DNA of your master data- Reference Data Management with SAP MDG

While Master Data Management has become an important discipline in most companies, the management of reference data is often neglected. Reference data builds the basis for all other data types and objects by defining permissible values and standards for master data as well as transactional data. Nevertheless processes, technology, and standards to manage reference data are rarely on the same maturity level as other data.

Camelot developed a generic solution utilizing SAP MDG custom objects that enables not only the management of reference data but also allows the management and distribution of reference data in all other systems utilizing them.

The how and why of governing reference data – and what it brings to the business

#4 Transform Document Management into an integral part of your overall EIM

With growing digitalization, organizations are challenged by enormous amounts of unstructured information residing in numerous platforms.  Yet document management is often overlooked and not considered a high value activity/function.  In reality, a well-run DM strategy can address numerous challenges including furthering your organization’s digital journey

Stemming from our previous experience with DM projects with fortune 500 companies across industries, we have developed a holistic framework to manage documents efficiently.  The approach is broken down into four areas:

  • External Requirements – focuses on regularity, integrity and authentication by adhering to any legal requirements established by external entities
  • Document Organization – encompasses all administrative & organizational aspects including documents in scope, document classification and structure
  • Process Organization – harmonizes the organizational technical aspects by defining the processes that need to be supported and how they work
  • DM System – the interface between external requirements, document organization and process organization by depicting their underlying structure and definitions

#5 Simplify your data maintenance with Camelot’s chatbot for SAP MDG

The chatbot application is based on machine learning (ML) and is integrated in SAP MDG, SAP’s standard software solution for managing master data. One of the chatbot’s benefits is its intuitive design, based on IBM’s Watson Conversation Services and SAP Fiori applications. The personal assistant saves users a great many clicks, and guarantees a completely new user experience, for instance when creating new materials.

The chatbot resulted from the first cycle of innovation from the “Global Community for Artificial Intelligence in Master Data Management”, an initiative founded by the CAMELOT group. It is an open community that connects leading MDM and AI thought leaders from research and practice, thereby promoting discussion and the targeted transfer of knowledge. Requests to participate are fielded at

#6 Enhance Data Security with Data-Driven Fraud Protection

According to the Association of Certified Fraud Examiners (ACFE), losses to internal fraud constitutes 7% of profit on average.  With the growing amount of connected devices and more data being generated, industry experts agree that cyberattacks are on the rise.  Fraud, in its basic form, can be defined as deliberate deception intended to result in personal or financial gain.  With regards to data, examples of fraud could be:

  • Redirect funds to a private, fraudulent account
  • Modify master data such as pricing or altering salary information
  • Complete false transactions
  • Misappropriation of company capital

Due to the increasing number of companies facing data security risks, particularly with regards to the redirected payment scenario, Camelot has developed a 3-step approach to develop your fraud protection solution. Our holistic approach focuses on efficient process design, organizational structure, and the latest technologies (i.e. SAP Enterprise Threat Detection) to secure your data from fraudulent activity.

#7 Tackle your MDM Transformation with a dedicated Change Management Approach.

Implementing a new master data strategy within your organization can be a daunting task. With obvious changes to processes, tools an organizational structure come also changes in communication and collaboration pattern and employee capabilities. These are challenges that require a lot of attention early on and will set the pace for a successful transformation.

Our Business Transformation experts have supported countless global initiatives in the field of MDM. They combine strong functional know how and industry experience with extensive Change Management expertise and relevant certifications e.g. PROSCI.

With our holistic Change Management approach we are able to strategically address main pain points in a MDM initiative, throughout all dimensions of change. Our extensive toolkit enables the execution of this approach in accordance with project phases. Our Business Transformation experts work closely with functional experts and project management to deliver change management activities in accordance to the implementation methodology and project management approach.

#8 “Get Clean” with Camelot’s approach for data Migrations, data cleansing and continuous data quality management

Initial migration activities for master data are still one of the major obstacles for successful implementations of either dedicated MDM tools or ERP introductions. With the necessity of S/4HANA implementations and the necessary shift to e.g. the Business Partner concept the relevance of successful migration activities is even higher than before.

With the Camelot Get Clean platform we support end-to-end migration process with a fully integrated approach:

  • Flexible scoping of migration relevant master data due to easy adjustable rule-sets
  • Standardization and harmonization of data through easy adaptable transformation and matching rules
  • Centralized workspace for consolidated migration activities supported by workflows and simple stakeholder involvement
  • Consistent validation checks via full integration of SAP standard and MDG custom rulesets

Additionally, the platform enables continuous data quality management to not just get your data clean, but keep it clean in the future. A key aspect in times of digitalization and automation to reduce efforts and cost related to master data management.

#9 Analyze your Data Quality without a DQ Tool - Data Quality Health Check

Keeping your master data clean and accurate is key to enable process automation and fully leverage your company’s data to create benefits. Identifying data inconsistencies and using the right checks and KPIS is often a challenging task especially in commonly used heterogenous system landscapes.

The first step on your journey to high data quality is the Camelot Data Quality Health Check. By using Camelot’s industry leading knowledge and best practices you receive a comprehensive review of your current data quality with only a small investment of time and resources. Camelot using our own DQ Tool Set with hundreds of predefined industry specific rules and KPIs.

Based on the findings a Data quality roadmap will be defined tackling the major pain points in data governance, processes, organization and IT capabilities.

#10 Trusted Master Data Quality - based on Blockchain (Trusted MDQ)

When speaking about Blockchain, usually big industry use-cases as “Track and Trace” or financial transactions come to mind. But relevant use cases exist in the area of Master Data Management as well, especially when exploring measures to achieve Data Quality.

Usually companies spend large amounts of money to receive data from dedicated providers for address validations or blacklisting information. Additionally, data collaboration initiatives are joined. But in both cases the data is governed by a central instance which takes over the authority.

By using Blockchain in combination with encryption and secure storage of local data, the next generation of data collaboration can be introduced. A powerful network is created that allows participants the full control over their owned data. By connecting to relevant industry peers the knowledge off a whole industry can be leveraged for joint creation of trusted master data quality.