At Snowflake Summit 2023, Snowflake announced the private preview of a new capability to observe data quality metrics. Using a SQL-based interface, data engineers and platform administrators will be able to configure, measure and monitor quality in terms of freshness, validity, accuracy and more for their business-critical data.
This development underscores the need for trusted data and will provide exciting new integration possibilities with Informatica Cloud Data Quality, a service of our Intelligent Data Management Cloud (IDMC). Powered by our CLAIRE AI engine, IDMC is the first and only AI-driven cloud dedicated to data management, with a microservices-based architecture and over 200 intelligent cloud services in a single platform.
Customers such as Paycor, a human resources software platform, rely on IDMC and Snowflake to drive their businesses forward. For example, by implementing data quality rules and aligning metrics across different business units, Paycor has improved the accuracy, completeness and timeliness of their client-billing analysis and closed potential billing loopholes.
Make Sharper Business Decisions with Modern Data Quality Management
Cloud-based data platforms have become the default choice for organizations to power their data processing and data analytics use cases at scale. However, to extract meaningful insights and drive informed decision-making, it is imperative that the data in the data warehouse or data lake is of high quality and can be trusted.
Poor data quality not only results in inaccurate analytics but can also lead to a lack of trust in the data, which can impede decision-making and data-driven innovation. Reliable, accurate data can help:
- Enhance Decision-Making: When data is reliable, consistent, and trustworthy, decision-makers can have confidence in the insights and analytics derived from it. This leads to more effective strategic planning, improved operational execution and better overall decision-making across the organization.
- Improve Customer Experience: Clean and reliable customer data enables personalized interactions, targeted marketing campaigns and tailored experiences. This helps lead to improved customer satisfaction, increased engagement and higher levels of customer loyalty.
- Boost Data-Driven Innovation: By leveraging reliable data, businesses can uncover valuable insights, patterns and trends that drive innovation and unlock new opportunities. This helps enable organizations to stay ahead of the competition and adapt to changing market dynamics by leveraging data-driven approaches, advanced analytics and emerging technologies.
- Ensure Regulatory Compliance: Organizations need to adhere to data quality standards, ensure data governance, and implement security and privacy measures. By prioritizing data quality, businesses can help mitigate compliance risks, avoid penalties, and build trust with customers, partners and regulatory bodies.
7 Key Capabilities of Cloud-Native Data Quality Management
To achieve these benefits, organizations need a modern, cloud-native data quality service that provides deep integration with cloud data platforms such as Snowflake. Informatica Cloud Data Quality, a service of IDMC, empowers Snowflake customers to perform:
- Data Profiling: Analyze and understand the quality of your data by profiling it. Automatically examine data patterns, identify anomalies, and assess the completeness and accuracy of data using hundreds of pre-built data quality rules, including industry-specific rules.
- Data Standardization: Standardize and cleanse data by applying predefined or custom rules to ensure consistent formats, values and structures, including names, addresses, phone numbers and dates.
- Data Matching and Deduplication: Identify and eliminate duplicate records within your data. Advanced matching algorithms compare data elements and determine similarity, helping you to merge or remove redundant information.
- Data Monitoring: Real-time monitoring capabilities allow you to track the quality of data and trigger alerts when issues are detected.
- Data Remediation: Fix identified data quality issues in data pipelines with prebuilt data cleansing transformations.
- Data Governance: Support data governance initiatives by establishing data quality rules, policies, and standards. Define ownership, stewardship, and accountability for data quality across the organization.
- Data Quality Dashboards and Reporting: Interactive dashboards and reports help business users and data stewards visualize data quality metrics and trends, empowering them to gain insights into data quality issues and make informed decisions.
We believe the addition of native data quality rules and monitoring capabilities in Snowflake will provide several opportunities to enhance the overall informatica Cloud Data Quality offering for Snowflake. Potential benefits include in-database performance for data quality rule tracking and monitoring, and new types of data quality insights.
Informatica IDMC is designed to provide holistic data management capabilities across your entire data estate. It provides user experiences for virtually all relevant data management personas to manage data and analytics environments at enterprise scale. We plan to work closely with the Snowflake team to seamlessly integrate Snowflake’s new data quality capabilities with IDMC and Cloud Data Quality — so stay tuned.
In the meantime, we invite you to explore all our exciting Snowflake Summit announcements. You can also learn more about the integration between IDMC and Snowflake Data Cloud by visiting www.informatica.com/snowflake.