A topic typically under-represented in modern business, Master Data Management is quite often the single most critical system which can positively affect day-to-day operations. Regardless of the type of data created and used internally, the ability to ensure accessibility, accuracy, consistency, and security is crucial to business success. MDM solutions provide the agility, compliance, safety, and performance needed to operate in an informatics landscape which is increasingly more regulated, more advanced, and more competitive than ever.
Much of the difficulty in adopting MDM comes, not from the systems themselves, but migrating from existing solutions already in place. Many organizations have adopted ad-hoc data management as they continue to grow. One of the most powerful factors in many organizations is 'the way things have always been done'.
When it comes to data management, ad-hoc solutions without modern procedures can lead to disaster on many fronts. Often not being able to recall data, holding out of date versions, or losing data to corrupt files is the difference between success and failure on critical contracts.
MDM solutions are built to provide a single point of reference for all of an organization's critical data. The design reduces costly redundancies, conflicts, and should prevent information going out of date. Intelligent and careful system design factors overcome these issues which plague many firms; by doing so, MDM eliminates widespread systematic business problems and reduces their associated costs.
Firms that can strongly benefit from MDM:
Reducing errors and redundancy is often the most significant single difference which helps a highly effective firm win out over its business competition.
Migrating existing, potentially fragmented, systems to an effective MDM implementation utilizes expert knowledge combined with years of data management experience and practical system knowledge. Altering existing processes and procedures is often the most challenging aspect of implementation. An effective solution should target complete end-user adoption of new processes as a metric for success.
The critical components to consider when implementing MDM solutions include data cleansing, transformation, and integration practices. These are built to ensure that standardized and consistent data is compatible with a solution that can index and catalogue business intelligence.
A classic example of effective data management exists where multiple relationships between two entities could easily overwrite or be otherwise confused with one another. Capturing these relationships is one of the great advantages of MDM. A supplier may also be a customer, for example, or the head of multiple organizations. Secondary details can easily be lost to inefficient data storage and management.
The core of building effective MDM is rooted in identifying, collecting, transforming, and repairing data on introduction into the system. Data is manipulated with the goal of ensuring every element meets the quality thresholds, schema, and taxonomies created to the master reference.
With an effective MDM solution in place, a number of tools exist that enable firms to make the most of their data. A data warehouse is one of the most common systems used for data analysis and reporting.
Created from a central repository, the warehouse is considered a core component of business intelligence. Variations of the warehouse include a data mart, for information on a specific subject or client, and an operational data store for operation-specific considerations and decision-making.
In addition to organized file systems, data warehouses, and data stores, key tools and advantages associated with implementing MDM include:
Many firms find exceptional added value from tools that allow them to measure the results and effects of their data. The key to effective MDM is in providing ongoing, demonstrable, and sustainable value within an organization.
The value of MDM can come from numerous avenues such as virtualized data providing multiple points of access, data visualizations making information more readily accessible, and regulatory compliance opening new markets and areas of exploration.
Building trust in the solution is one of the biggest hurdles every implementation faces. Overcoming these hurdles and increasing time spent using the system typically leads to increased buy-in across the entire organization. The quantifiable results demonstrated by MDM solutions are exceptionally hard to argue with.
Contact Us Today
Finding Hidden Patterns and Correlations Innovative technologies such as artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) are transforming the way we approach data analytics. AI, ML and NLP are categorized under the umbrella term of “cognitive analytics,” which is an approach that leverages human-like computer intelligence to identify hidden patterns and correlations in data.Explore
What Is an SQL Query Engine? SQL query engine architecture was designed to allow users to query a variety of data sources within a single query. While early SQL-based query engines such as Apache Hive allowed analysts to cut through the clutter of analytical data, they found running SQL analytics on multi-petabyte data warehouses to be a time-intensive process that was difficult to visualize and hard to scale.Explore
The Cloud is the Key to Transformation Success… Transitioning your applications to the cloud is undeniably a critical factor to a successful digital transformation endeavor. It’s more than just a lift-and-shift, however. Let’s explore several things that you need to consider before migrating your applications to the cloud, including: Readiness of your application portfolio Where to begin – the right business case and migration strategy Technology requirements and considerationsExplore
Application Modernization at Speed and Scale Enterprises are pursuing greater application scalability, cost efficiency, and standardization with containerization and virtualization platforms. So, what’s the difference? Containers are a type of virtualization technology that allows users to run multiple operating systems inside a single instance of an OS. They are lightweight and portable, making them ideal for running applications across different platforms.Explore