Databricks Lakehouse Validation and Trust Scoring within 2 weeks
Ensure Superior Databricks Data Quality With the Help of Data Trust Score
Data Quality Validation for Databricks
With 97% of reporting companies investing in big data analytics and AI-driven tools, Databricks has become an integral part of modern data management strategies. This is why, in the intricate landscape of Databricks, the integrity of your data is paramount. Imagine a scenario where flawed data infiltrates your critical business processes – decisions go awry, business partners lose trust, and the IT team faces unwarranted blame. At FirstEigen we recognize that the repercussions of data quality issues extend far beyond the digital realm; they pose a genuine threat to the success of your business.
Data Trust Score to
Assess Data Quality
We go beyond conventional data validation by introducing the concept of a 'Data Trust Score.' By observing changes in data fingerprints over time, we generate a score that reflects the trustworthiness of your data. This score empowers our clients to gain a quick and intuitive understanding of the reliability of their data, enabling better decision-making.
Traditional methods of setting thresholds for anomaly detection can be time-consuming and prone to errors. FirstEigen leverages the power of deep learning to dynamically find the right thresholds for anomaly detection. This ensures that potential data issues are identified promptly, allowing for proactive measures to maintain data quality and enhance overall data reliability.
Circuit breaking and
Unity Data Catalog Integrity
FirstEigen's data pipeline circuit breaking functionality acts as a robust safeguard against incorrect data infiltrating your downstream operations. When significant inconsistencies in data quality and matching are detected, our solution springs into action, halting the data flow and issuing timely alerts. Furthermore, by prominently showcasing Data Trust Scores (DTS) within your Unity Data Catalog, we bolster stakeholder confidence in the data they rely on, empowering them to make more informed and reliable decisions.
Have 1000's of tables
validated in minutes
For databases encompassing thousands of tables with millions of rows, a scalable solution is crucial. DataBuck, leveraging advanced AI/ML technologies, offers rapid validation capabilities. Its sophisticated checks are tailored for extensive databases and intricate schemas, enabling it to validate entire databases swiftly – all within mere minutes. This efficiency transforms your data validation process, ensuring speed and reliability in handling vast data volumes.
FirstEigen's quick turnaround with DataBuck ensures that you don't have to wait months to catch faults in your data. Our on-prem solution operates seamlessly within your Databricks environment thus eliminating the need for data transfer while also minimizing security risks. Our team of experts will help you every step of the way as you go from onboarding to identifying and tracking your data issues within just 2 weeks.
Experience the future of data quality assurance with FirstEigen – where machine learning meets the unique challenges of Databricks. Secure your data's integrity and fortify your decision-making processes with DataBuck.
What DataBuck users say…
“What took my team of 10 Engineers 2 years to do, DataBuck could complete it in <8 hrs”
- VP Technology, Enterprise Data Office, Major US bank
“DataBuck’s Data Quality automation does 80% of the heavy lifting for us with just 5% of the effort.”
- CIO of US Financial Services firm
“Streamlining the DQ monitoring and validation process w/DataBuck has reduced our time-to-market. With fewer resource we auto discover DQ rules, which also self-heals as the data evolves.”
- Head of Enterprise Data Quality Monitoring, Major US bank
“DataBuck can really add a lot of headcount efficiency for us. This tool makes it easy for us to not only profile and discover the rules, but also to operationalize them and auto-heal as the data evolves over time.”
- VP, Enterprise Information Management, Information Governance Leader, Insurance Company
“AML is on the rise. We have data from 10 countries in different formats and standards that need to be validated. We could not keep up doing it manually. DataBuck has automated and streamlined our data pipeline.”
- Sr. Exec. Technology Office, Top-3 African bank
“In the last 3 years we’ve had a 100x increase of API’s and microservices on the Cloud. This proliferation is beyond what Data Stewards can manage. As Cloud-native tool designed for Data Engineers, DataBuck autonomously validates data upstream and tremendously eases the burden on Stewards.”
- Sr. VP Data Mgmt and Analytics, US Investment Bank
“Monitoring and validating files and data at ingestion directly impacts our revenues. DataBuck gives us the reliability, intelligence and speed we need to eliminate revenue-leakage.”
- VP Technology, Enterprise Data Office, Telehealth provider
“Aggregating weekly sales data from many dozens of sources and validating them is laborious and error prone. With DataBuck’s AI/ML-driven DQ automation we got more accurate data with less than 10% effort.”
- Director, Commercial Data Operations, US pharmaceutical
“With the traditional Data Quality tools, we could not thoroughly audit the financial data for the Street w/in our audit window. DataBuck’s performance has reduced data validation times from 11 hrs to 2 hrs, and w/higher accuracy.”