Hope you are finding your zen in the Zoom way of life! Here at Datacoral, we have settled down into a cadence that allows us to move quickly and provide improved capabilities and services to our customers. Check out the latest news and product updates below
- We achieved the Amazon Redshift Ready designation, part of the Amazon Web Services (AWS) Service Ready Program. This designation recognizes that Datacoral has demonstrated successful integration with Amazon Redshift.
- We are proud that AWS has selected Datacoral as one of the seven finalists from San Francisco for the AWS Startup Architecture of the Year Program.
- Datacoral has leveraged Redshift’s Data API to build a fully serverless event-driven data pipeline. We were a launch partner for the feature.
- We relaunched our website with new and improved content on the data integrations we offer and our focus on data quality guarantees.
Over 800 improvements were released to our customers over 6 releases during Q3. These improvements include new connectors, performance and scalability improvements, increased data observability, and better data orchestration and pipeline administration.
- Change data capture connectors: Our change data capture connectors are becoming popular with customers who need robust connectors with data quality checks. We improved the administration of these connectors w.r.t managing logical replication slots for PostgreSQL and performing historical syncs and seamlessly handing off to the change data capture updates. We also added the ability for customers to choose between performing soft deletes vs hard deletes in the data warehouse.
- Rollbar connector was recently released to allow engineering teams to analyze how their software deployments affected their application performance, crash rates, and customer support tickets.
- JIRA connector now fetches data using the Agile and ServiceDesk APIs in addition to the main REST API and can handle deleted issues. In addition, Datacoral customers get a prepackaged set of transformations to simplify the schema of the nested structures in Jira data and incorporate additional data like holiday schedules in the analysis. These transformations allow our customers to easily answer questions like how long were issues in a specific status and how did linked issues affect the SLAs of support desk tickets.
- Several other connectors were enhanced like JDBC, NetSuite, Drift, S3, Google Spreadsheets, and Github.
With Datacoral, analysts automate data pipelines by just writing SQL transformations. However, analysts do end up having to debug data issues and fix the transformations. They can already quickly pinpoint broken transformations through the navigable data lineage graph. And, when they are debugging data issues, they would like to prevent new “bad data” from being published. They now have the ability to, with one command, pause and resume all the transformations that are downstream of a particular connector or transformation that they are debugging. This feature enables them to control when data is refreshed.
We introduced a user management console within the Datacoral application. Users can now easily invite new users and manage the permission for different team members.