Data science is proving to be a major competitive advantage for companies. While business intelligence (BI) helps companies with reporting and historical analysis, data science goes a step further and predicts the future. It can leverage much more data from many more sources, and using machine learning (ML) principles, it automatically identifies patterns and trends to model, predict, or forecast future outcomes.

Managing access to sensitive data is the name of the game when it comes to security and data governance. It’s required to protect sensitive data from unauthorized changes or exposure, and it’s now a mandate as part of privacy regulations such as GDPR and the California Consumer Privacy Act (CCPA). Companies all over the world are now focused on protecting sensitive PII associated with their customers and employees.

Michelin is a global organization well known for its high-performance tires, popular travel guides, and numerous innovations around materials, services, and connected solutions. Many consumers recognize the French brand by the famous “Michelin Man” mascot, whose body is composed of stacked white tires.

Data analytics is going through tremendous growth while helping businesses succeed in a challenging economy. But cybersecurity presents increasing challenges for businesses. Prologis, however, has combined data analytics and cybersecurity to improve visibility, cut costs, and reduce risk. Prologis plays an essential role in the global supply chain.

We are pleased to share the findings of a Forrester Consulting Total Economic Impact™ (TEI) study that evaluates the cost savings and business benefits enabled by Snowflake’s cloud data platform. Snowflake commissioned the study to gain insight into the return on investment we’re delivering for customers and learn how we can serve them better.

In keeping with its continued focus on building the most powerful and flexible cloud data platform for data-driven companies, Snowflake released a host of new features in July. The following roundup briefly describes several of them.

Organizational leaders worldwide agree that data governance is important. However, data governance programs in most companies are still being planned or in progress. In a 2020 Dataversity report¹, only 12 percent of companies had fully implemented programs, while 38 percent of programs were a work in progress, and 31 percent were just getting started. That’s because companies often run into roadblocks while executing data governance. Below are five common obstacles organizations face.