Blog Article
March 25, 2025
Shift Left Data Conference
March 30, 2025
Data Quality
March 5, 2024
August 14, 2024
Change is inevitable in data-driven organizations—but for data leaders, this can't mean taking data change management for granted.
June 23, 2025
Data platform modernization requires data leaders employing a sound data platform strategy—one informed by platform maturity modeling. Learn why.
The value of data is often industry-agnostic—but healthcare data quality in particular comes with higher stakes for many data leaders and the teams they manage.
Videos
Watch a short video demonstrating how gable prevents PII from being shared with a large language model such as those from OpenAI
May 30, 2025
Learn how to assess and improve your data platform with a data platform maturity model to drive business growth and innovation.
May 23, 2025
Shift‑left governance that keeps downstream stakeholders safe and productive.
May 19, 2025
Due to the growing industry needs for high quality data, data platform modernization is going from "would be nice" to "need to do now." Learn exactly why.
April 28, 2025
The rapid rise of AI has dramatically elevated the value and strategic importance of data, transforming how upstream software engineers perceive and interact with data workflows. In this expert-led panel, industry leaders will share their experiences and insights into effectively bridging the gap between data teams and software engineers. They will discuss practical strategies for proactively managing data infrastructure, enhancing collaboration, and ensuring high-quality data to support advanced AI-driven development initiatives.
April 1, 2025
Good Data and not Big Data is becoming more important in today's ecosystem. Machine Learning models rely on good quality data to make their model training more efficient and effective. We have traditionally applied Data Quality checks and balances in manual, centralized way, putting a lot of onus on our customers. Shifting Left Data Quality will bring the data quality checks closer to where data is being created, while preventing bad data from flowing downstream. Also auto-detecting, recommending and auto-enforcing data quality rules will make our customers job easier, while creating a more mature and robust data ecosystem.
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