As more and more organizations deploy data at the center of their business strategy, the two terms- Master Data Management and Enterprise Business Intelligence have come to gather increased attention. Let us take a closer look at what exactly do they mean.
What is Master Data Management or MDM?
Every organization has a central repository of data that brings together data from all internal and external platforms, known as the master data. The process of managing, maintaining, and organizing master data in line with business functions is called master data management.
Master Data Management helps organizations streamline their data processes and makes them more reliable to be used for analytics and business intelligence applications.
What is Enterprise Business Intelligence?
Business Intelligence (BI) refers to the process of collecting, storing, and analyzing data from all business operations, and when this system is applied throughout a large enterprise, it is called Enterprise Business Intelligence (EBI). Note that both BI and EBI stand for the same concept, however, EBI is used for large enterprises as they work with an unusually large amount of data regularly.
How good MDM complements an effective EBI program?
Implementation of a successful Master Data Management strategy is key to deploying an effective Enterprise Business Intelligence. Here’s how.
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Ensures high-quality data for input into EBI systems
MDM serves as the starting point for implementing a Business Intelligence strategy. How? Suppose you have a minor data inconsistency while collecting data. While it may not be significant during the initial stages, however, it may amplify as you build upon that data to derive results. You will notice that the minor inconsistency is not insignificant anymore and has distorted your results considerably.
Therefore, MDM ensures high-quality cleansed data that can be fed into the business intelligence systems to derive meaningful and accurate conclusions.
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Helps companies save on expenses
According to a Harvard Business Review, bad data causes the US economy to lose over $3 trillion annually! Poor data management practices cost companies heavily in terms of lost opportunities, productivity impacts, reduced customer satisfaction, increased operating costs, and more.
Having efficient data management practices in place helps organizations make better use of their assets, gain deeper insights into their customer habits, improve profits and opportunities for scaling up.
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Serves as a single source of truth
Often employees waste a lot of time and resources debating duplicated data and inconsistencies. MDM solves this problem by maintaining a single record for all existing data and thus helps leaders make an informed decision. This not only prevents pointless arguments but also saves your employees’ precious time, which would’ve otherwise been wasted in correcting and reorganizing data.
Assuming this is the case, we’ll pursue the open door here to give some industry use cases that request that there be a solitary, concentrated perspective on dependable information for a compelling business insight procedure:
The financial business is going through a significant development, as conventional organizations endeavor to expand their deftness to answer upstart balance specialists and online-just contenders. First of all, they could investigate all their client information – regardless of where it lives – to acquire a 360-degree image of every client.
With extraordinary client information close by, a bank could work on designated promoting. Perhaps, for example, it could examine and section every one of its clients into various “boxes” to figure out which of them are bound to need new kinds of administrations – maybe, for example, recent college grads may be most intrigued by new highlights for portable banking.
In the assembling area, an organization’s actual organization might incorporate plants, stockrooms and different offices spread all through various geological regions. Product offerings might differ a considerable amount, as well. Such variety frequently amounts to having cracked client, item and area records across division conditions. That could make issues, for example, having one line-of-business stretching out credit to the very client that one more division had requires to briefly wait for non-installment.
Having the option to have a comprehensive perspective on their clients and item deals across areas would permit the maker to perform at a lot more significant level of business investigation and take out inadmissible dangers.
With regards to medical services, a major pattern is toward combination, for example, those among medical clinics and clinician practices or care conveyance administrators with insurance agency. At times, either of the consolidation or procurement parties works different offices, for example, nursing homes or non-intrusive treatment habitats, to support patient populaces.
Solidification of all their office related information may be hampered by the way that either of the substances don’t have a method for guaranteeing precise and steady information in-house, also across one another’s surroundings. Resolving that issue will make the solidification more straightforward: Analytics around it will improve and speed undertakings, for example, distinguishing which offices ought to be offered to try not to copy administrations in a similar geological region.
Ideally it is clear, the organizations in these areas – to be sure, in organizations of each and every sort – rely upon business knowledge answers for examination purposes, fully intent on creating exact reports, outlines, diagrams, etc to respond to questions that include client and item use, functional area, and consolidations and procurement correlation information, to give some examples.
Takeaway
An organization cannot execute a functional enterprise business intelligence model without a reliable Master Data Management program. Creating an intersection between the two can help your business scale for better opportunities. And the best part is, the benefits of MDM increase in number as the diversity and complexity of systems across the organization expand!