Strategies and best practices for effective Master Data Management
Master Data Management (MDM) involves several components including data collection, cleansing, and standardisation to achieve a single view of assets.
As digital transactions and data grow, more organisations are recognising that MDM needs to be a critical component of their data management strategy and digital transformation efforts.
To achieve effective MDM, organisations need to have a well-defined data management strategy and data governance structure in place to enforce it.
Our consultants share features and highlights of each new Profisee release, including the most useful and our favourite features of this MDM solution.
Learn how this government education organisation gained a full lifecycle view students, staff and schools. This was enabled by an upgraded MDM platform, which also provided a solid foundation for modernising their technology stack.
Discover insights from Harvard Business Review’s report on AI adoption, challenges, and strategies. Learn how businesses can build a solid data foundation to leverage AI effectively.
Data management refers to the way data is collected, organised, and made secure and accessible. The goal of effective data management is to optimise data to support an organisation to be more efficient and effective at delivering on its goals.
There are many systems that aid data management, including customer relationship, marketing, data warehouse, and analytics systems.
What are the benefits of data management? Strong data management practices can help your organisation in these areas:
Discover insights from Harvard Business Review’s report on AI adoption, challenges, and strategies. Learn how businesses can build a solid data foundation to leverage AI effectively.
[Report] Harvard Business Review surveyed executives around the world on effective strategies to bolster enterprise data management. Learn how organisations are investing in their data strategy and which are most effective.
What is MDM, why is it important, how do you manage it, and who should be involved? This article covers key MDM questions and best practices.
Data quality refers to the standard and condition of data. Data that is of good quality is accurate, complete, consistent and up-to-date, and serves those who need it.
Managing data quality can include data cleansing to fix errors, and enhancing data sets to complete or update records. It involves a continuous process of reviewing and managing the data to ensure data rules or standards are kept.
Having good quality data results in:
[Report] Harvard Business Review surveyed executives around the world on effective strategies to bolster enterprise data management. Learn how organisations are investing in their data strategy and which are most effective.
What is MDM, why is it important, how do you manage it, and who should be involved? This article covers key MDM questions and best practices.
Golden Record Management is the process of matching, surviving and merging to create a single complete record about an asset such as customer or product.
“Golden record” refers to the accurate and complete record. This record can be fed into other data sources to ensure they have the same up-to-date information.
Golden Record Management typically involves a combination of data governance, data quality, and data integration technologies and processes. It is important for organisations who want to ensure they have a consistent and accurate view of their data.
What are the benefits of Golden Record Management?
This in turn leads to better understanding of the business, operational efficiency, time and cost savings, and better decision making.
After experiencing disparate data and discrepancies between systems, learn how this energy company turned things around by applying MDM to deliver value.
There are different ways to implement a software. Deciding on an implementation approach can depend on the development method, tools and technology, and processes used to manage the project.
Master Data Management implementation styles include:
Factors affecting which Master Data Management implementation style to use include:
Does your business need Operational MDM or Analytical MDM? Explore the different approaches and its features to determine which you need.
“Digital transformation” has become a bit of a buzzword, but in essence it is how organisations are approaching an increasingly digital world, to stay relevant and competitive.
Digital transformation is the integration of technology into all areas of an organisation. It can involve adopting new technologies such as cloud computing and artificial intelligence. While often the remit of the IT department, it generally affects all areas of the organisation.
Successful digital transformations result in organisations becoming more efficient, agile, and relevant.
The benefits of digital transformation include:
What is Master Data, why is it so crucial for businesses, and how can you talk to stakeholders about it? Scott Taylor, The Data Whisperer, shares his expertise on this matter.
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Profisee is the fastest growing vendor in the Master Data Management market. It enables organisations to build a trusted foundation of data and brings together every domain, source, user and record to deliver a single source of truth.
Profisee offers a complete end-to-end solution to handle key business data and important data management challenges. Profisee is known for its ease of use, cost effectiveness and rapid deployment.
QMetrix is a Profisee Field Certified Partner – Gold Status.
The benefits of Profisee include:
Our consultants share features and highlights of each new Profisee release, including the most useful and our favourite features of this MDM solution.
Learn how this government education organisation gained a full lifecycle view students, staff and schools. This was enabled by an upgraded MDM platform, which also provided a solid foundation for modernising their technology stack.
Discover insights from Harvard Business Review’s report on AI adoption, challenges, and strategies. Learn how businesses can build a solid data foundation to leverage AI effectively.
QMetrix has worked with organisations across many industries to achieve their data management goals. Learn about the challenges, solutions and outcomes in these case studies of real businesses like yours.
“We no longer have to manually source, integrate and align data from multiple systems to get what we need.
The data integrates with Profisee and makes it easily available for consumption through an integration layer or MDM reporting functionality.” – Senior Data Analyst from a large energy producer in Australia
Learn how this government education organisation gained a full lifecycle view students, staff and schools. This was enabled by an upgraded MDM platform, which also provided a solid foundation for modernising their technology stack.
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After experiencing disparate data and discrepancies between systems, learn how this energy company turned things around by applying MDM to deliver value.
We’ve worked with businesses across Australia to do just that. Let’s chat about how it could work for your organisation too.
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