In this four-part blog series, we explore the critical, complementary disciplines of data governance and master data management (MDM). While these principles hold true for any deployment, here we focus on the Azure cloud.
This is Part 4 in the series. Be sure to read Part 1 on whether you can trust your data in Azure, Part 2 on the risks poor data quality poses to your cloud investment and Part 3 on how MDM can unleash the power of your governance program.
Today, companies are working to leverage their ever-increasing amount of data as a strategic asset and source of competitive advantage. The first steps for many organizations often include leveraging other Software as a Service (SaaS) applications and migrating their data to the cloud.
But for these new initiatives to truly drive value, the underlying data must be clean, complete and trusted. And it must be continually governed so it builds and maintains this high quality as it travels across data warehouses, organizational siloes and geographic regions.
Without high-quality data in their data estate, organizations cannot realize the business value of their Azure investment — or any data-related investment.
Building a Strong Data Governance and Management Foundation
To truly leverage their enterprise data as a strategic asset, organizations must build a strong foundation of data governance to comprehensively scan, catalog and specify governance standards for their data and master data management to enforce these standards and remediate any deficient data.
And rather than add “governance extensions” to an existing MDM platform or use a governance application that claims to enforce data standards, the ideal solution is to deploy both a dedicated governance program to determine lineage, write business rules and begin writing data standards and then using a dedicated, robust MDM platform to enforce the rules developed in the governance phase.
When organizations seamlessly integrate two robust, complementary data governance and master data management (MDM) solutions, they can unleash the power of their data while maximizing the value of their Azure investment. And with the new native integration between Microsoft Purview and Profisee MDM, organizations can integrate two complementary tools that can leverage and reinforce one another without compromise.
Using Purview to Achieve Unified Data Governance in Azure
With the release of Microsoft Purview, organizations utilizing the Azure technology stack have a native option for unified data governance of on-premises, multi-cloud and SaaS data.
Purview allows organizations to easily create a holistic, up-to-date map of their data estate with automated data discovery, sensitive data classification and end-to-end data lineage.
This provides an excellent foundation for data governance and enables data architects to make informed decisions when considering the appropriate data standards to impose on enterprise data.
The Purview Data Map helps organizations establish a foundation for effective data governance by creating a unified data map of all enterprise data across all sources. Users can classify data using built-in and custom classifiers and Microsoft Information Protection sensitivity labels.
Data sensitivity labels are consistently applied across SQL Server, Azure, Microsoft 365 and Power BI — and all other data systems can be easily integrated using Apache Atlas APIs.
When organizations can visually assess the locations of sensitive data by label or classification, and drill down to the details of each data asset, they can better inform their master data model and start their master data management implementation on solid footing.
Master Data Management in Azure
While Purview can comprehensively scan source systems, catalog data and define business rules, it does not actually enforce those data standards, nor remediate deficient data.
And while Azure Data Factory can be used to deduplicate rows where sufficient identifiers are available for an exact match, organizations would have to invest significant time and resources in developing and deploying custom hardcoded scripts to de-duplicate rows — and even then Azure Data Factory could not actually merge identified matches.
Similarly, Azure Maps can provide data verification and standardization for address data, but standardization of any other data type would likely require hardcoded scripts as well.
The Profisee MDM platform offers these features, and more, out of the box with no custom coding or complex configurations. Organizations can quickly build on their governance and classification work in Purview and then complement the existing Azure investment without any functional overlaps or duplicate features.
And while Profisee can accept master data from any source, comprehensively defining scanning data sources and determining lineage, metadata and other rules in Purview saves times and ultimately adds more value to the MDM investment.
Once organizations have identified and cataloged their data, they can use MDM to match, merge, standardize, verify, correct and synchronize it across systems, ensuring data can be properly integrated and will meet the needs of downstream systems like Power BI, Azure Machine Learning and more — now data is becoming a strategic asset and is available to business users across the enterprise.
Better Together: Microsoft Purview and Profisee Master Data Management
Microsoft Purview and Profisee MDM each serve distinct roles in the enterprise data estate with no functional overlap. And they are better together thanks to a native, bi-directional integration jointly developed by Microsoft and Profisee.
This is possible thanks for Profisee’s Governance subsystem, which provides two distinct flows to and from Purview: changes to the master data model in Purview are published to Purview as they occur so the two applications are always in sync; and governance details are published to Profisee MDM so data stewards and business users can view and remediate data-quality issues in Profisee’s FastApp Portal.
The Purview catalog and glossary can also further maximize the value of an integration with Profisee MDM by informing master data model design and capturing crucial institutional knowledge for data stewardship.
Master Data Model Design
One of the challenges when preparing an MDM is determining what constitutes master data and from which data sources will populate the master data model. Purview creates a rich source of enterprise metadata that informs the master data model and enriches the catalog of data that master data models can use to better align with line-of-business (LOB) systems.
Organizations can use Purview to help with this effort by scanning critical data sources and engaging their data governance team and subject matter experts. This way, they can enrich their data catalog with information that master data modelers can then use to better align master data model with your LOB systems.
This enables users to easily reconcile conflicting terminology, yielding a master data model that optimally reflects the terminology and definitions that business users need while avoiding outdated and misleading terms, key functions of data governance.
Large enterprises with correspondingly complex and expansive data estates can present challenges to data stewards, who are responsible for managing and remediating issues as they arise. Key data domains can be complex — with many obscure attributes that only tenured employees with significant institutional knowledge understand.
Profisee’s integration with Purview allows this institutional knowledge to be captured within Purview and made available for use within Profisee, thus bringing knowledge of corporate data closer to when users need it most — when managing critical and time-sensitive information.
Profisee’s Governance Data Service integrates with both Microsoft Purview and Azure Active Directory. It provides lookup services to portal users, which allows them to retrieve enriched governance data about the entities and the attributes that they are working with in the FastApp portal.
Governance services also resolve contacts received from Purview to their full profile details, which are available in Azure Active Directory. Complete profile details allow stewards to effectively collaborate with data owners and experts, as they work to enhance the quality of master data.
The Profisee Governance dialog is the user interface through which data stewards and users interact with governance-level details. It renders information obtained from Purview to the users, allowing them to review the details behind the data from which the dialog was launched. If the information provided in the Governance Dialog is insufficient, it also allows the user to directly navigate to the full user experience of Purview.
These are just a few details of the Profisee and Purview bi-directional integration, and additional technical details are available at the Microsoft Reference Data Architecture for Data Governance with Profisee and Microsoft Purview.
Complete Your Azure Data Estate Today with Purview + Profisee MDM
As companies transition their data estate to Microsoft Azure, they need improved visibility and governance of their data assets.
Microsoft Purview helps organizations catalog, classify and govern the broad data estate while Profisee MDM can match and merge master data into a trusted golden record to enforce data-quality standards across data sources.
This deep integration and bi-directional sync further enhance the functionality of two individually robust data platforms. And organizations using both can build a foundation for data governance that maximizes the business value of their data.
To see the Profisee platform and its deep integration with Microsoft Purview and the rest of the Azure stack, schedule a demo today.
For the full story and technical details, download the The Complete Guide Data Governance and Master Data Management in Azure.