What is master data management?

Master Data Management is a process that involves the management of critical data assets to ensure uniformity, accuracy, stewardship, semantic consistency, and accountability across an organization. MDM aims to create a “single source of truth” for important data, such as customer information, product data, and financial data. This definition shifts away from the outdated notion that MDM is a technology, to reflect the reality that master data management is a business capability.

Master data are the objects in a business that provide context for transactions. For example, for a procurement transaction a supplier (person) may provide a service (thing) under the terms of a contract (concept). For a purchase, a customer (person) may buy a product (thing) from a store (place).

Why is data integrity the foundation of master data management?

Data integrity is crucial to the success of MDM because it ensures that the data being managed is of high quality and trustworthy across all systems and departments. If data is inaccurate, inconsistent, or unreliable, it can lead to errors in decision-making, wasted time and resources, and ultimately damage the reputation of the organization.

How does Master Data Management work?

MDM involves a series of processes, enabled by technology, that work together to create a single source of truth for critical data. The process typically involves identifying key data assets, cleansing and standardizing data, and creating a master record that can be used across the organization.

How can we align business and data management?

The alignment of business and data management is critical for an organisation's success. To achieve this alignment, four pillars need to be in place: data strategy, data culture, data monetisation, and data literacy. Data Strategy: A clear data strategy is essential for aligning business and data management. It should outline how data will be collected, stored, managed, and analysed to support business goals. A well-defined data strategy can help identify data gaps, define data standards, and establish a roadmap for data management initiatives. Data Culture: Data culture refers to an organisation's values, beliefs, and behaviours around data. It is essential to foster a data-driven culture that values data as a strategic asset and encourages data-driven decision-making. A data culture can help to promote collaboration, transparency, and accountability around data management. Data Monetisation: Data monetisation is the process of leveraging data to create business value. It involves identifying opportunities to monetise data assets, such as through new revenue streams or cost savings. Data monetisation requires a clear understanding of data value and the ability to extract insights from data to inform business decisions. Data Literacy: Data literacy refers to the ability of individuals to read, understand, and effectively use data. It is essential to build data literacy across an organisation to ensure that employees have the skills and knowledge to leverage data for business purposes. This includes data analysis, visualisation, and interpretation.

Data Integrity Specialists. Getting African data right

Business-First Master Data Management, Data Governance and Data Integrity solutions for Africa

We are data integrity Specialists!

Over more than fifteen years, we have enabled leading African organisations to get data right!

Our business-first approach prioritises the needs of the business over any other considerations using data.

We apply our fifteen years of data integrity expertise to solve the immediate data problems that are blocking your business while building a scalable and sustainable enterprise capability to enable the digital, data-driven enterprise.

Overall, our business-first approach to data management is focused on using data to drive business value and support the organisation's success.

At Masterdata, we understand that master data management (MDM) is more than a technology problem.

Monetising Data, Without Data Integrity

... is like racing through the streets of Jo'burg ...

...without fixing the potholes!

Slow, frustrating and expensive

Stop hitting data potholes

The surest way to monetisation is through data integrity!

IDC Research shows that higher levels of data integrity drive positive improvements across key business metrics.

From improving customer satisfaction to increasing business agility to reducing risk and increasing revenue - recent IDC research shows that investments in data integrity drive improvements across the business!

Conversely, a lack of investment in data integrity has a direct negative impact on costs and revenue.

Delivering Master Data with Integrity

We blend consulting, education and technology to provide a complete business solution to master your data

Our business-first approach to Master Data Management

At Masterdata, we understand that master data management (MDM) is more than a technology problem.

Our more than twenty years of experience have taught us to take a business-first approach to deliver master data management, prioritising data integrity to provide the best results.

Our MDM approach enables key business outcomes by ensuring that critical data is accurate, consistent and complete. By aligning the MDM strategy with our client's overall business strategy, we help them manage their data assets more effectively, improving operational efficiency, reducing costs, and driving better decisions.

Working for Our Customer's Success

Absa Capital Case Study

When Absa Capital needed to improve client static data quality they turned to Master Data Management and Precisely Trillium

"We wanted partners with both strong technology and solid local expertise, and MDM and Trillium Software met our requirements"

Ian Kriegler, CIO, AbCap

Capitec Case Study

"We needed a data governance solution to help us manage the risk around this and effectively organize our data to enable it to be used for business insight"

Manrich Kotze, Data Governance Lead, Capitec Bank

Within three months, Master Data Management implemented a data catalogue and automated data lineage capability that allows Capitec to visualize its entire data landscape as never before. This ability to rapidly assess the impact of planned changes in their data environment has helped Capitec boost business agility and optimize data processing.

Data lineage case study: Capitec reduces data risks…

Learn how we helped Capitec Bank to deliver a data catalogue and integrated data lineage End-to-end…

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Master Data Management Case Study

This case study showcases the importance of strong technology and local expertise in achieving Absa Capital's…

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Business First Data Management

BARC Research shows that executives openly articulate the need for their organizations to be more data-driven but practitioners struggle to deliver trusted data.

Our approach involves understanding the business objectives and using data management practices to support those objectives. It requires an understanding of the business processes and a willingness to collaborate with different stakeholders to ensure that data is managed in a way that meets the needs of the business.

For example, a business-first approach to data management might involve developing data governance policies and procedures that support the organization's goals, implementing data quality controls to ensure that data is accurate and reliable, and using data analytics to provide insights that can help the business make more informed decisions. We help organisations to prioritise their data investments for sustainable business improvement

Unlocking the value in your data

"Trust comes through transparency provided by intelligence about data backed by enrichment to provide context and deliver integrity." - IDC

Data Management frameworks and accelerators

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07 Dec 2023;
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Enabling Real-Time Data and Analytics: Key Considerations and Best Practices

12 Dec 2023;
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Data Management Best Practices

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Data Quality Matters

Data integrity - Unlock the value in your enterprise information asset

What is the importance of data lineage in certifying a report?
Report certification is a meticulous process that ensures the reliability and credibility of data used in decision-making. This process encompasses verification, validation, and authentication of data, fostering transparency, enhancing accountability, and providing a basis for benchmarking. Data lineage plays a pivotal role in report certification by maintaining data quality, demonstrating regulatory compliance, aiding issue resolution, facilitating impact analysis, and supporting risk mitigation.
Time to Reinvent Data Governance
Data governance, the process of establishing processes, roles, policies, and standards to manage data, is experiencing a significant shift in response to an ever-exanding data landscape. Traditional methods are proving inadequate due to data explosion, big data impact, and the rise of unstructured data. Consequently, a reinvention of data governance, focused on agility, automation, and adaptability, is being hailed as paramount for organizations. Newer methods include the Agile Data Governance model, Data Governance as a Service, and Data Governance 2.0 that aim to enhance data accessibility, reduce costs, and streamline decision-making.