Systems | Development | Analytics | API | Testing

It takes vision, purpose, and skill to unlock the power of data. It also takes the right strategy. For ExxonMobil, Ares Trading (Merck), and the University of California San Diego (UCSD), the right strategy is taking full advantage of the cloud. All three organizations have partnered with Cloudera, leveraging a hybrid or cloud-based architecture to improve the lives of the people who depend on their organizations’ data.

Machine learning (ML) models have become key drivers in helping organizations reveal patterns and make predictions that drive value across the business. While extremely valuable, building and deploying these models remains in the hands of only a small subset of expert data scientists and engineers with deep programming and ML framework expertise.

At Snowflake, putting the customer first is an essential company value. But “customer-centric” is more than just a buzzword: We use a data-driven, outside-in lens on everything we do, at all levels of the company. In particular, here’s how Snowflake Support is listening to you—our customers—and continuously improving the Snowflake customer experience at every touchpoint.

The business world is rapidly pivoting all the time. Strategic shifts, reprioritization and being first all require being smart while moving fast. The value of agility has never stood out more due to the need to react to new realties in everything from public health, remote and in-office business policies and workflows, to broader economic concerns like supply chain as we move into recovery and revitalization.

In part 1 of this blog post, we discussed the need to be mindful of data bias and the resulting consequences when certain parameters are skewed. Surely there are ways to comb through the data to minimise the risks from spiralling out of control. We need to get to the root of the problem. In 2019, the Gradient institute published a white paper outlining the practical challenges for Ethical AI.