Enhancing data quality is essential for producing reliable insights; poor data can not only mislead but also stall growth and undermine confidence in data-driven initiatives. But, monitoring the quality of data within warehouses, data lakes and various pipelines is no easy task – especially without the right infrastructure and tools. The cloud then brings its own intricacies, often necessitating the extraction of data for external testing. Recognising these hurdles, Collibra has introduced a new innovative solution — Collibra Data Quality and Observability with Pushdown for Snowflake.
This new offering is designed to ease the burdens faced by businesses, streamlining data quality processes and ensuring that the data used for critical business decisions is both accurate and trustworthy.
How does it help?
Put simply, it reduces the complexity of controlling data quality. Utilising machine learning, it automatically creates and applies adaptive rules for anomaly detection, directly within the Snowflake environment. Auto-generated SQL queries reduce the need for manual intervention, allowing teams to focus on strategic tasks rather than routine data quality checks.
The addition of Pushdown for Snowflake enhances this process by enabling data quality tasks to be executed where the data resides. Avoiding the transfer of data outside of Snowflake, ensures faster processing times, heightened security and reduced operational costs. This method represents a significant step forward in efficient, in-situ data quality management.
What are the benefits of Collibra Data Quality & Observability?
Strengthened Data Security & Speed
Reduce data vulnerability with faster and more secure data quality processing in Snowflake.
Maximising Efficiency with Snowflake’s Scalable Architecture
Increased efficiency by using the built-in scalability, flexibility and elasticity of Snowflake.
Rapid Data Quality Resolution
Identify and fix data quality issues faster with complete visibility into the quality of the data.
Advanced Data Governance and Compliance through Snowflake
Improve data governance with data discovery and enforcement for compliance.
What are the main features?
AI-generated Adaptive Rules
Traditionally, data managers have manually written rules to check data quality, but these rules can become outdated or not function properly. Adaptive Rules connect to Snowflake databases and generate monitoring controls in minutes.
Data Discovery & Enforcement
Access a ready-made repository of industry-specific validation rules for automatic data discovery and quality enforcement. Automatically detect sensitive data and enforce data quality, allowing for immediate action to rectify any inaccuracies.
Custom Data Quality Rules
Leverage an intuitive SQL editor to create custom rules, avoiding proprietary language dependency and redundant rewrites. Rule templates facilitate the creation of reusable, shareable rules across departments, streamlining processes.
Data Pipeline Monitoring
Avoid business decisions based on outdated data. Gain visibility into data pipelines to spot operational blind spots, separate single occurrences from systematic issues, and evaluate the quality of data by each business unit and source for improved decision-making.
Schema Change Detection
Protect downstream outputs from upstream modifications with automated schema tracking, ensuring dashboard and report integrity. Set up alerts for quick responses to undesired schema changes, maintaining consistent data validity.
Collibra’s integration with Snowflake streamlines data quality management by automating and localising it within the data environment, facilitating prompt and reliable data-driven decisions. This solution simplifies maintaining data integrity and governance, empowering businesses to utilise their data confidently and effectively.
Want to learn more about Collibra Data Quality and Observability with Pushdown for Snowflake? You can do so here. Ready to get started? Reach out using the form below.