Snowflake Native MDM | Solution

Challenge

Master Data Management is a data governance discipline under which people, processes, and technologies are aligned to introduce and maintain a unified, accurate, and consistent view of data assets across an organization. By establishing an enterprise-wide single source of truth, MDM helps organizations break down data silos and power reliable data sharing across departments and geographies. This unified view of the organization’s data empowers stakeholders at every level by giving them better trust in their data across multiple domains, including products, customers, and securities. MDM also reduces the amount of time organizations spend manually identifying, reconciling, and remediating data issues, freeing up data teams and other valuable resources to focus on insight and innovation.

Inefficiencies in or an outright lack of Master Data Management can have far-reaching negative consequences for an enterprise, including cost leakage, incomplete or erroneous records, and oversights in mission-critical business intelligence. Unfortunately, costly, rigid, and unscalable legacy MDM systems are often a major blocker for organizations, whose MDM initiatives are quickly sidelined as they struggle to integrate MDM platforms with their existing systems, databases, or applications. The limitations of these programs also introduce hidden costs into data governance processes, often requiring extensive workarounds and manual interventions that snowball into additional infrastructure investments and strain data team resources.

Solution

Hakkoda’s Snowflake Native MDM is a master data management and data governance enablement utility that leverages Snowpark’s machine learning engine to modularly enable data profiling, rule management, and exploration management all within a Snowflake environment. Snowflake Native MDM enables governance stewards with circular data management of quality, observability, exploration, and stewardship while automating anomaly detection, deduplication, rule application, and profiling features to streamline data and metadata management.

Other benefits of Snowflake Native MDM Include:

A One-Stop Shop for MDM: Snowflake Native MDM leverages all the advantages of the modern Snowflake platform to eliminate expensive integration challenges and security risks by performing all MDM functions within the Snowflake ecosystem. This Snowflake-native, Governance First approach also makes it easy to integrate Snowflake Native MDM with reporting tools like Sigma, data catalogs like data.world, Alation, and Atlan, and collaboration tools like Slack and Microsoft Teams. Snowflake Native MDM is also compatible with standard SSO and multi-factor authentication providers.
Cost Reduction and Process Automation: Snowflake Native MDM slashes the time organizations spend identifying, reconciling, and remediating data issues by introducing built-in data quality functionality and reference data management. Snowflake Native MDM makes it easy to work on data quality issues, merge/match issues, and workflows via a built-in task queue, and allows for the configuration of both match and merge rules without the need for complicated configuration files.
Shortened Time-to-Insight: By ensuring a single source of truth, Snowflake Native MDM improves the quality and accessibility of critical business data across domains and industries. This enables faster and better insights, opportunities, and decision-making. Snowflake Native MDM also allows business leaders to better trust their data by initiating data checks against business rules both pre- and post-mastering.
AI-Enabled Matching: Snowflake Native MDM improves an organization’s ability to systematically identify unique data entities and remove duplicates by employing AI techniques and machine learning models. This reduces the number of exceptions requiring human analysis and resolution.

Ready to learn more?

Speak with one of our experts.