We are all familiar with this scenario, you work on your training code, fix “all” of the bugs (the ones you know about), wait for a few iterations, see that batch size wasn’t wrong and nothing blows up, and then you happily go home. However, when you come back into the office the next day look at your loss and test accuracy you’re horrified to find that the experiment crashed on the first test cycle because you pointed your test set in the wrong folder 🙁

The Industry Transformation category at the Data Impact Awards has never been more timely. While the business world is mostly focused on digital transformation, Cloudera and our customers know that true, data-driven change is reshaping whole enterprises and entire industries.

Our new dbt package will help you make sense of Stripe’s detailed API and improve your finance analytics.

For many companies, cloud costs are among the top investments these days. With a growing number of services, instances and regions, cloud cost optimization is becoming increasingly painful. Companies use cloud management platforms to optimize costs and increase cloud visibility and security. But staying on top of AWS budgets requires proficiency, agility and time—especially when any glitch can result in massive cost bleeds.

Cloud for analytics may be the biggest bait and switch in recent history. Until now. Not long ago, cloud was billed as the promised land – a mystical paradise of flexibility, scalability, performance and, best of all, lower costs than we ever thought possible.

“Every organization — no matter how big or how small — needs data quality,” says Gartner in its newly published Magic Quadrant for Data Quality Solutions. However, with more and more data coming from more and more sources, it’s increasingly harder for data professionals to transform the growing data chaos into trusted and valuable data assets.