Trends that will Define Master Data Management and Data Governance in 2019

May 21, 2019 0 comments

Master Data Management and Data Governance products have a critical and imperative role to play especially when an increasing variety of systems, IT professionals, and customers are creating and accessing data throughout enterprises as well as partner organizations. As data gets more consolidated and refined, organisations are increasingly relying on Data Management and Data Governance to provide information that can be relied upon for decision-making and outreach to customers.

 

The Dynamic Master Data Management (MDM)

Master data management is a framework of processes and technologies for creating and maintaining a sustainable, accurate, authoritative, reliable and secure data environment which is accepted and adopted by intra- and inter-enterprises spanning across lines of business, user communities and application systems.

While in a broader sense, Data Governance collaborates people, processes and technologies which are essential to manage and protect an organisation’s data assets with an aim to secure vital corporate data.

 

1. Data Quality Forms the Core of Data Management and Data Governance

Poor data quality can derail all the efforts made to extract meaningful insights from any data source. Data quality is often compromised while integrating complex architecture from multiple non-integrated data sources. The unclear responsibilities for data quality defined at each application level is also the culprit.  Data management and Data Governance issues arise the way data is addressed, with mismatched data syntax’s, formats, and unclear structure.

 

2. Expanding the Scope of Data Relationships Beyond Organisations

 Gone are the days when data management was restricted to organisations and corporate boardrooms. At the current pace, organizations are looking out for significantly better ways to understand the relationships between its different stakeholders like individuals and corporate entities; informal groups and organizations and individuals and households. The changing regulatory requirements like the Basel II Committee are creating a demand for MDM technologies which understand and assimilate the relations between entities.

With the latest trend, many companies have dedicated resources devoted to understanding these relationships, and to help companies better understand relationships, MDM vendors are all set to enhance their offerings with advanced algorithms capable of recognizing relationships and hierarchies in data.

 

3. Creating Customised Data Security Solutions to Resolve Data Quality Issues

In the modern times, most companies will have an informal, de facto data stewardship processes to resolve data quality issues in a reactive way which includes complaints from customers or business users or failures in automated processes. Formal processes and employees with day-to-day responsibilities and performance metrics for data stewardship are more the exceptions than the rule. In the times to come, MDM technologies will also need to proactively identify data issues and conditions of interest and generate configurable issue queues that can be directed, prioritized, reviewed, escalated and resolved by individuals with data stewardship responsibilities.

 

 

4. Integration with Workflows and Business Processes

 Many industries face complex supply chain challenges that require near-real-time synchronization of master data across participating systems. This integration will require the development of and compliance with interoperability standards, which will enable enterprises to more easily leverage the benefits of MDM to improve business processes to achieve other business advantages. The integration of MDM with business rules engine and workflow technologies will also significantly enhance the collaborative capabilities and qualities of the data stewardship process.

Once data management has been integrated with business rules engines and workflows and the data is accessible across the entire enterprise, security of enterprise data becomes an even greater requirement and challenge. The best way for this to be accomplished, and the fourth disruptive trend, is for MDM solutions to consume existing enterprise security policies owned by enterprise security management applications and systems such as LDAP (Lightweight Directory Access Protocol).

 

5. Expanding the Security and Data Visibility Umbrella

Organisations have come to terms that enterprise data access controls are best handled with its dedicated data security and visibility systems, rather than being redundantly owned by multiple individual applications which include master data management solutions. Open MDM products capable of sending data to and receiving data from a single enterprise-wide data security and visibility product will help improve the quality and robustness of data security and visibility solutions and reduce their cost.

While securing critical data is obviously a top enterprise priority, being able to read and understand data across multiple applications and systems is also a critical MDM success factor.

 

Summing Up

Additional changes will likely also come around the matching of non-western names and details (such as addresses). At the moment they can be notoriously tricky as, for example, algorithms such as Soundex simply can’t be applied to many languages. This will change and we should see support for more and more languages.

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