Four Best Practices for Accelerating Time-to-Value of Master Data Management

Email     |     Share  
1 | 2 | 3 | 4 | 5 | 6
Next Four Best Practices for Accelerating Time-to-Value of Master Data Management-4 Next

Incorporate Big Data into your MDM strategy – and vice versa. Before the end of 2013, Big Data will be driving an essential part of the requirements for MDM programs as incorporating new types of data becomes a strong requirement. This trend, initially driven by customer-centric organizations or divisions, is already expanding to other domains such as manufacturing or logistics. Big Data augments conventional MDM sources to provide a complete view of the required domain.

Adding Big Data to MDM does not mean that the master data hub will be stored in Hadoop (although some organizations are exploring the use of NoSQL databases), nor does it mean that its size will grow exponentially in a short timeframe. Rather, it means that some of the Big Data (or new data) will be managed in the MDM hub itself, linked from the MDM hub in a federated approach, or will simply benefit from the consistency, resolution and enrichment services that MDM provides.

Master data management (MDM) has become recognized as a key way for businesses to gain consistent and valuable insight on data, usually distributed across applications and systems. While the anticipated benefits of MDM are usually clear, a number of factors must be considered to implement an effective MDM program, ensuring actual success and return on investment. Talend has identified four best practices for accelerating successful returns on an MDM initiative.


Related Topics : APC, Resellers, Data Replication, Extract Transform and Load, Structured Data Integration

More Slideshows

mobile87-190x128.jpg How to Find Business Value in Your Data Through Modernization

Data only becomes a meaningful and valuable asset when organizations can transform it into actionable insights. ...  More >>

LiaisonTechUncontrolledData0x 5 Steps to Wrangle Uncontrolled Data Flow

As the availability of data exponentially increases, unprecedented opportunities exist to do all kinds of amazing things, but these opportunities also come with data wrangling challenges. ...  More >>

Misc70-190x128.jpg 5 Data Warehouse Design Mistakes to Avoid

If you are designing a data warehouse, you need to map out all the areas where there is a potential for your project to fail, before you begin. ...  More >>

Subscribe to our Newsletters

Sign up now and get the best business technology insights direct to your inbox.