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API Management 5 min

The Right Data with Boomi MDH

Discover how Boomi Master Data Hub (Boomi MDH) helps businesses streamline their data governance processes. This blog explains how Boomi MDH ensures data accuracy, synchronizes data across applications, and improves overall operational efficiency. Stay ahead with better data quality.

RZW pasfoto 2020
Ruben van der Zwan
CEO & Founder
The Right Data with Boomi MDH

Data is an asset of extreme importance and value for nearly all businesses; therefore, treating it with the respect and care it deserves, is a significant factor in a company’s growth and success story. Understanding the various types of data within your organization is a crucial step to proper and proactive management of your holdings and policies. In this blog we focus how to get correct master data and use it in our application landscape.

Boomi Master Data Hub: Ensuring the Right Data Quality

In the world of data it is always important to know if you are using the right data. The right data is the data that lets your processes run smoothly, makes your communications clear and understandable, and your finances flow and compliant to regulators demands. But how do you know if the data you have/get is the right data? For this we have to define what is the right data first.

Data that is complete, actual, valid, consistent, unique and has integrity, can be seen as correct data. These 6 dimensions are the basic foundations for good data quality. To reach the right level of data quality you have to perform actions on your data to get there. This can be done by a variety of tools within a wide scale of scenarios. You have tools that focus primarily on improving data quality where you also have tools that have data quality as a secondary feature (like integration tools) or the good old programming languages where you can add data validation etc within the code. These are just 3 examples, but there are many forms and ways to improve data quality while handling data.

Master Data, Freeform, Transactional, and Reference: Key to Data Governance

Within an organization’s data, there are typically four different types of data, each serving a different function. These types of data are:

  • Freeform Data
    Freeform Data, often referred to as unstructured data, is not organized or formatted in a predefined manner. Freeform data can include written content on web pages or documents, journal articles, emails… Most user interaction driven applications natively produce freeform data.
  • Transactional Data
    Transactional Data is foundational for any given business. It includes all data related to the documentation of business transactions, both B2B, and B2C. It usually operates on a much larger scale than Master Data or Reference Data. Privacy and security is a critical factor of Transactional Data. (examples are orders, bank transactions, shipments).
  • Reference Data
    Reference Data is stable and commonly accessed information that categorizes data, usually more uniform, and less volatile than Master Data. Generally, reference data stays the same, or changes very slowly over a period of time. (like ISO Country codes)
    and
  • Master Data
    Key information (nouns) that is shared across the enterprise. Master data is the functional data for business entities and often considered mission critical for the business. Stored such that it can be accessed by various applications for specific business processes or functions.

Boomi Master Data Management (Boomi MDM): Efficient Data handling

Master data facilitates high level and critical business processes. “Master Data Management” is the practice of responsibly managing and distributing master data throughout the organization.

Often Master Data consists of a ‘master list’ of customers, products, partners, etc. This data consistently shares overlap with the business’s CDEs, or Critical Data Elements, which are for each company different domains. For an eCommerce it is products and customers, for a delivery firm it is products and locations and for a job agency it is people and jobs. If a tool supports this, we call it multidomain support.
A ‘master list’, per domain, is a single repository where only one version of the data is active. This ‘master list’ repository contains master data records, a single point of definition of a domain item.

Inserting or updating of master data is a process of upserting (update or insert in one action) the new information to the master record. Based on a match, merge the new information with the existing data to form a new version of the master data record or when no match, create a new master data record. This process needs to be controlled by rules. These rules decide if a certain field within the master data record will be updated or not. These rules are based on the previous mentioned data quality dimensions. So, if data is coming from an unreliable source, data is not updated, if data is coming from a customer communication app, then fields like email or phone number are updated. If a financial application provides new data, the related fields to finances are updated etc.

So, by the constant control of business rules based on quality requirements, the single instance of a domain record is managed within the master data application.

Now we have the record we need to use it. Master data needs to be shared and accessible across the company, while remaining safe, redundant, and adherent to policies. For this it needs to be accessible in different ways so external applications can use the latest and greatest version of the data to be consistent.

Integrating Master Data Management with Boomi Datahub: Synchronization & Efficiency

The Right Data with Boomi MDH

Within the Boomi platform all these functionalities come together with the Integration layer and the Master Data Hub module. With the integration layer of the Boomi platform we can connect to any source of data, applications (SAP, IFS, AFAS etc), databases (MSSQL, Oracle DB, MongoDB etc), file locations (Drives, SFTP, Azure Blob etc), services (Kafka, MSQ, Solace, Salesforce Events etc) and other generic technologies as email, APIs (REST, SOAP, OData) and other technologies like JMS. In the above picture this is valid for the Sync and Engage parts.

As soon as the integration layer has collected data from the data source it can transform it to a canonical data model which is also created in the Master Data Hub repository as place of storage. Then, internally in the platform the integration process sends the data to the HUB where additional validation and enrichment rules check and enrich the data. Based on matching rules the data is inserted or updated. In the above picture this is located in the Govern section.

Now we have a central storage of a master data record. Every time a record is updated by such an integration process, other applications can receive the updated data. This works in a pub/sub structure, so if an application would like to receive some of the data fields of the complete master data record, it can subscribe to that data. An integration process will transport the data from the Hub towards the requesting application every time an update takes place.

Now by this last action all applications that provide or subscribe to the master data hub records will have the same data (synchronized). Production, Finance, Sales and Logistics departments will have the same information and will not have any conflicts in their data exchange processes (at least the ones related to master data).

Interested to learn more or see the Boomi platform in action with Master Data Management? Contact us and we get you started.

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