Data Integration

Master Data Management (MDM) and role of Artificial Intelligence

Read in-depth discussion on Master Data Management (MDM) and role of AI
DataChannel Research
7 min to read

What is Master Data Management (MDM)?

Master Data Management (MDM) involves building a well-coordinated version of truth out of different customers, suppliers, locations, and products data scattered across different source systems. This unification of scattered data takes place after much necessary data transformation steps involving deduplication, enrichment, and cleaning that results in the creation of the ultimate source of truth. 

Master data once created successfully can be used unanimously within any organization to perform required analytics, reduce pertinent data redundancy or any associated errors to power informed decision-making out of business-critical data.

How Master Data Management (MDM) helps?

MDM helps businesses unprecedentedly by creating a central layer of reference that easily eliminates redundancies and other upfront costly endeavors associated with scattered data ( and data sources).

A few business areas where MDM proves to be highly beneficial are

✓ User experience

✓ Data Analytics

✓ Data Governance and Security

✓ Supply chain management

✓ Product Performance

Components of Master Data Management (MDM)

By incorporating the following components in their MDM strategy businesses can effectively foster agile and data backed decision making. 

1. Data Governance: Efficient data governance begins with putting the necessary policies, protocols, and role based access controls in place. This not only helps in increasing data democratization but also in clearly defining data ownership roles.

2. Data Quality Management: Data Quality is the component that can make or break the game and by leveraging the right tools that enable easy data quality management is business critical. Data Quality Management usually involves making data more consistent and eliminating pertinent errors, duplicacies and inaccuracies.

3. Data Integration: Data integration involves creating a unified master record for your disparate data sources. This can be achieved either manually or by using a tool that supports integrations with different source systems and allows easy data transformation and management.

4. Data Security and Compliance: Data Security and Compliance revolves around safeguarding customer’s personal data. This can be achieved by following the necessary regulatory and security compliances and using data hashing, and encryption, etc to ensure master data integrity and reliability. 

Importance of Master Data Management (MDM)

Master Data Management ensures data uniformity by eliminating data silos and building a unified data repository. It takes care of data integrity, security and other governance related concerns. With a unified data repository businesses can effectively make data-driven decisions with confidence. Furthermore, with reliable data backing businesses can also foster innovation and agility across departments and also boost positive customer experience. 

Here’s how MDM proves to be crucial for businesses.

✓ Making sure that data is accurate and consistent 

✓ Providing a central, authoritative data reference for informed decision-making.

✓ Taking away your dependency on manual interventions and efforts

✓ Ensuring data security and privacy while following the necessary security and regulatory compliances.

Role and of AI in MDM

  • Data Quality: Tools like DataChannel enable efficient data transformation that automate and take care of much of the data cleaning and enrichment process, but AI can take your efforts of data quality management  a whole new level by leveraging machine learning (ML) algorithms to automate much of identification and resolution of discrepancies and inconsistencies within data sets.
Image Courtesy:
  • Data Governance: Ensuring efficient data governance is a challenge that organizations often grapple with. From building the desired governance procedures and protocols from the ground up to applying them uniformly within an organization, it demands significant time and resource investment. However, with AI, businesses can easily automate the application part. AI can automatically ensure that the necessary protocols are being followed and may even inhibit the next steps in the process if governance protocols are not adhered to.
Image Courtesy: The symbiotic relationship between Data Governance and AI
  • Data Democratization: Again, platforms like DataChannel power data democratization using its data centralization functionality via a low/no-code approach in order to make desired data as accessible as possible, but the potential is for AI to take this to a whole new level by further increasing data accessibility across teams regardless of their background and expertise. 
  • Data Maintenance: Data Maintenance is one another avenue where AI can help businesses big time. With data being generated at such a rapid pace it becomes very challenging to ensure that data is always up-to-date. AI can help in that again by incorporating ML algorithms that can identify changes in data sets and update them accordingly to ensure that downstream steps don’t get affected due to stale data.
  • Data Lineage: DataChannel also lets you track and visualize your data journey via its data orchestration feature. By adding relevant nodes starting right from data extraction, transformation to data activation and business intelligence you can observe your data journey easily. It is absolutely necessary for businesses to be able to visualize their data movement journey so as to easily attribute which change leads to which error and which step. Data lineage with AI can be further meticulously mapped and monitored which are becoming increasingly important in simplifying this data lineage journey for users.

Choosing the Right MDM Tool

Choosing the right MDM tool for your business is of paramount importance and should only be chosen after meticulously thinking through your business and data requirements. The right MDM tool enables you to work easily with data while ensuring efficient data integration, governance and a scalable architecture.

Crucial steps that should be following when choosing the right MDM tool could be:

  • Apt Evaluation: Evaluation for the right MDM tool must involve a 360 approach and the decision should be based on the functionalities that the tool offers, constructive customer feedback and reviews, its performance, and how it stacks up with its competitors.
  • Meets your Requirements: The right tool should also meet your business and data requirements as mentioned  earlier (be it data integration, activation, no-code approach or ease of use, etc).
  • Pricing & Budget: Reasonable pricing is also a big factor when considering your choice of MDM tool. Make sure you compare different tools available in the market as per industry standards.

By selecting the right MDM solution, organizations can ensure that their MDM implementation is reliable and involves a robust and scalable platform.

Why should DataChannel be your ideal MDM partner?

In the preceding heading we discussed some of the most crucial criterias for choosing the right MDM solution for your business. Here’s how DataChannel might be able to meet those criterias:

Vendor Evaluation & Selection: DataChannel as a third party vendor checks all the criteria: offering multiple capabilities within a single tool such as data integration, activation, transformation and orchestration needs. With an extensive repository of more than 125 connectors, DataChannel also enjoys credible and positive reviews on G2. Apart from that DataChannel can also be your vendor partner owing to its reasonable pricing window without compromising on the functionalities.

Data Integration & Transformation: DataChannel can integrate customer data from various sources, allowing organizations to get a comprehensive view of their efforts. Loading integrated data into your central source of truth, making sure that it is reliable, accurate and up-to-date. Transforming data from different formats and structures to ensure compatibility and consistency for streamlined storage and master data management.

Data Activation: With DataChannel’s Reverse ETL functionality, user’s can also activate their data into relevant business applications. Data Activation enables businesses to better segment their customers and to ultimately boost their retargeting and remarketing initiatives. With your customer 360° data (based off of their purchase or cart history, demographic, and buying preferences) at your fingertips you can create a consistent, refined cand a holistic customer experience across different channels.

Data Observability & Lineage: DataChannel’s low code interface fosters a cross-functional team comprising representatives from different departments and business functions to provide input, share expertise, and drive the MDM implementation. With DataChannel’s data orchestration feature you get to build custom workflows for your unique business needs.

DataChannel enables you to trace back your data flow right from the origin i.e, the data extraction from any data source. The main components of data lineage involve data source, transformation, storage, data consumers, data processing steps, etc. With DataChannel you not only get to build your end-to-end workflows involving all of these steps but also get to view logs for each and every step of your workflow to easily identify what worked and what didn’t in the bigger picture. This easy data lineage can be used to monitor and maintain even the smallest of changes in data down the stream. Along with data lineage, data observability is also a big enabler in DataChannel, you get to view all the moves within any workspace (or the accounts within) easily to get the gist of your overall data movements and pipeline as well as sync runs. You can also get real-time alerts or notifications to easily identify where things went wrong or to optimize your workflows accordingly.

Scalable Architecture: Deciding on the right tool also involves choosing a vendor with a scalable architecture that can scale with the organization's growth, handle increasing data volumes, and support future integration with new systems and applications. DataChannel offers a scalable, robust architecture with an intuitive interface that can support multiple functionalities and can scale as per your unique business needs, be it for a small startup or an enterprise with multiple clients.

Data Governance: One important factor when deciding your ideal MDM solution is data governance. Anyone’s personal data or identifiable information must be protected at all times and certain regulatory compliances and certifications have been put in place to safeguard personal data. DataChannel is ISO certified and is also GDPR and HIPAA compliant. Your data is safe within our storage systems and only the concerned stakeholders can access it and based on their access controls. Moreover, your personal identifiable information is hashed, encrypted and protected from unauthorized access or breaches.

The role of Artificial intelligence (AI) in Master Data Management (MDM) is ever changing. While cloud-based and no-code solutions like DataChannel offer the much needed flexibility and customization into MDM, AI can and will shape the future of MDM immensely. Cloud based holistic platforms offer scalability and value for money when it comes to Master data management and can easily enable organizations to make data-driven and innovative initiatives with confidence.

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