Systems | Development | Analytics | API | Testing

This week we introduce new user interface menu and navigation improvements, making user interaction more consistent, organized and easier to use.

Prevent lost sales with automated machine learning for out-of-stock prediction and trigger timely stock alerts while automating replenishment processes. Find out how to do all this and more with Qlik Cloud Platform.

We have closed a $50 million Series D round of funding, led by Third Point Ventures with participation from Bridge Bank and existing investors that include Menlo Ventures, Point72 Ventures, GCV Capital, and Harmony Capital. Kunal Agarwal, CEO and Co-Founder, shares what this funding means for you.

Unravel is a DataOps observability platform that enables your data teams to optimize the cost of your data operations intelligently, run faster data pipelines, and troubleshoot mission-critical applications. Watch this video to discover what’s new in Unravel Data 4.7.5.0 release.

In times of economic uncertainty, businesses need to get the most value from their data, while minimizing pressure on their systems and databases. But with the exponential growth of the variety and volume of data, extracting business value out of that data is only getting increasingly difficult. The result is data transfer latency, data loss, high cost of managing such data, data sources, leading to an inability to use data to make high-ROI business decisions.

The Cloudera Applied Machine Learning Prototype (AMP) for continuous model monitoring acts as a customizable template for your data science team to quickly build an accurate way to track drift.

For DataOps teams, job failures are common. But finding the issue is (traditionally) where things get even worse. It can take hours or days to troubleshoot a job failure. Unravel Data provides a single view where DataOps teams can locate exactly where–and why–a job failed, along with precise recommendations to troubleshoot the error. DataOps teams are now able to both diagnose and troubleshoot job failures in minutes instead of days or weeks.

Data pipelines fail all the time for a variety of reasons; service downtime, data volume fluctuations, etc. Diagnosing these failures manually is very difficult and time consuming. Unravel Data allows DataOps teams to troubleshoot pipeline failures automatically – showing exactly where and why a pipeline failed, and precise recommendations to remedy the issues. Using Unravel, DataOps teams can now diagnose and fix data pipeline failures in a fraction of the time.