The Synergy of Big Data Analytics and Master Data Management

In the information age knowledge and information are two characteristics that organizations receive a sheer volume of information from different sources. As more such data are produced, the challenge of making sense of these figures becomes even more critical. Big Data and the system of Master Data Management are two main sub-processes that contribute to effective management of big data. In their own right, they deliver value but, when linked together, there are large gains to be made in terms of data reliability, decision making and organizational performance. 

 

Big Data Analytics is a process of analysing big and heterogeneous data to find out useful and meaningful information such as patterns, associations, trends and many more. The data can be collected through various sources like social media, sensors, transactional systems, and many other streams. These are some of the factors that make big data analysis to be unique; the amount of data is large, and it comes in various forms, and most of it is time sensitive. The objectives of big data analytics are to support companies in decision-making, improving performance and improving their position in the market. 

 

 On the other hand, Master Data Management is a business discipline that deals with the constant and correct management of master data. Master data consists of important company data that are common to an organization or business they include customers, products, and services, financial data among others. The result of MDM is that such data is consistent, accurate and timely across the numerous processes within a business, thus providing a strong base for numerous business processes. If appropriate MDM is not implemented then it results in creation of duplicate data, inconsistency and errors in data which can greatly hamper the decision-making process and turn the organizational processes into inefficient ones.

When it comes to big data and especially Master Data Management, the synergy that is created between the two can be the key strength of the organizational model, as far as data is concerned. The need for clean, consistent, and correct data that forms the basic foundation and key to big data are offered by MDM. In this sense, the term ‘master data’ refers to the quality of data involved in decision making and if the master data involved in decision making is inaccurate, the triangle of big data might be wrong. On the other hand, big data can complement the improvement of MDM by discovering defects in data quality and usage patterns and recommend crucial focus. 

 

Big Data and MDM when implemented together reduces the confusion and creates a single perspective of the data present in an organization. This integration increases the probabilities that analytics are done on excellent data, and hence improving insights and decision making. For instance, a firm can employ big data for the purpose of understanding CBA involving analysing client's behaviour patterns and trends. However, from the viewpoint of invulnerability of data analysis to the data quality, it is crucial to refer to such a nefarious effect due to poor MDM as when the underlying customer data is inconsistent or inaccurate. In other words, with help of big data and MDM integration, organizations can be confident that their analytics leverage data of high quality. 

 

Furthermore, there is a possibility that the integration of these two disciplines will enhance data governance. Since MDM would apply control over the master data making it appropriate and standard across the organization and big data would show how data is consumed and where possible challenges could be expected, organizations could be in a better place to create better data governance. From this, there can be enhanced compliance with the set regulations, increased data security as well as data organization. 

 

Conclusion,

Both big data analytics and master data management should be implemented in organizations with an aim of obtaining a competitive edge in their data. Each of them has its place but the fact that they are different can be advantageous in ensuring that the insights gathered for decision making are a result of integrated data that is clean, quality data. The integration of big data and MDM therefore leads to establishment of a strong, effective and relevant data environment with the ability to enhance business success.