BigID is partnering with Databricks to increase the value that organizations get from their data in a Lakehouse built on Databricks: BigID adds data context and intelligence around that data to enable fast and accurate data-driven decisions, achieve compliance, and proactively protect data.
Many of the world’s largest organizations are embracing the advantages of a lakehouse for data engineering, analysis, ML-based applications, and collaboration across teams. The rapid adoption of this architectural pattern and supporting technology and the ever-increasing number of use cases means that more sensitive data is making its way into data lakes, making the discovery and management of that data more important than ever. In addition, with vast data available for use, data analysts and data scientists need to be able to identify the best data for all analytics use cases.
Organizations want to migrate to cloud data environments to benefit from cost savings, flexible storage, and fast analytics, and they need to know what data they have, where it is, and what it is, to know what data needs to be protected for compliance, and what data is good to use for business decision making.
Identify Sensitive Data for Compliance, Policy, and Protection
Data privacy and protection regulations are rapidly changing. Evolving standards and variance by country, regulation, and type make it difficult for data leaders to manage data compliance, especially for organizations operating across multiple countries and serving global customers. CDOs, CSOs, and CPOs struggle to enable analysts and data scientists working on Databricks to know what data is affected by privacy regulations and business policies to use and share appropriately. Data leaders need to identify sensitive data in cloud environments to know what data needs to be protected for both company policies and local privacy regulations.
With BigID + Databricks, customers are able to:
- Mitigate data risk
- Know what data is safe to use or how to treat data based on policy guidelines
- Identify sensitive data that needs to be masked or protected
Increase Accuracy of Data Decisions
Building analytics with bad data can lead to the wrong business decisions. Data scientists and analysts working in Databricks need to understand data context to select the best data for analysis. With vast amounts of data in enterprise environments, data analysts and data scientists may not be aware of all of the data available in Delta Lake and what it is. They may not be using the best data for business decisions because they can’t see all of the available, relevant data.
BigID automatically discovers, classifies, and adds context to data in Delta for analysis. Adding context to data at scale makes enterprise data more valuable because data analysts and data scientists working in Databricks can discover and understand the data available to choose the right data for analysis and modeling.
With BigID + Databricks, customers benefit by:
- Understanding data to make better business decisions
- Finding data faster for faster time to value
- Seeing all data in Delta with context for full data discovery
Accelerate Value with Faster Cloud Migration
Organizations want to benefit from cloud technologies but cloud migration projects take a long time to plan and execute. IT doesn’t know what data to prioritize for migration and can’t easily identify redundant data, data that needs to be protected, and data sources to prioritize to build data pipelines.
BigID automates and scales data intelligence to identify data to protect and redundant data to eliminate, making it easier for data owners and IT to determine which data to migrate to a cloud environment. Insight and intelligence about the data accelerates cloud migration projects, lowers project execution risk, and helps to establish efficient data pipelines.
With BigID + Databricks, customers can:
- Accelerate cloud migration planning to get to the cloud faster
- Innovate fast with data in the cloud
- Reduce risks related to expired, duplicate, and sensitive data in data lakes
BigID enables customers to get to a cloud environment faster, discover sensitive data to protect in Delta Lake for Databricks, and add context to data to find the right data for all of their data-driven use cases on Databricks’ Lakehouse Platform.
- Register for free to attend the session ‘Identify Sensitive Data and Mitigate Risk in Apache Spark and Databricks’ at Databricks’ Data + AI Summit 2021 on May 28, 2021 10:30 AM PT.
- See the partnership in action in a 1:1 demo