Systems | Development | Analytics | API | Testing

Driving Business Value from a Data Mesh Approach

Irrespective of what it’s called, the market has talked about what amounts to data mesh for several years. The concept of decentralized data management that is driven by business domains helps support the need for business-focused data outcomes. It also helps place value on where the value of data projects should be - on business needs. Data driven organizations need to look at business domains as a way of organizing the various desired outcomes of analytics and data movement initiatives.

Modern Data Architectures | Data Mesh, Data Fabric, & Data Lakehouse

For years, companies have viewed data the wrong way. They see it as the byproduct of a business interaction and this data often ends up collecting dust in centralized silos governed by data teams who lack the expertize to understand its true value. Cloudera is ushering in a new era of data architecture by allowing experts to organize and manage their own data at the source. Data mesh brings all your domains together so each team can benefit from each other’s data.

Developers Rejoice! Snowflake Is All in on Python, Pipelines, and Apps

Snowflake is committed to helping developers focus on building their apps and businesses rather than on infrastructure management. At this year’s Snowday, Snowflake announced a series of advancements that empower developers to do more with their data, enhancing productivity and unlocking new ways to develop applications, pipelines, and machine learning (ML) models with Snowflake’s unified data platform.

Snowpark for Python: Large-Scale Feature Engineering, Machine Learning Model Training, and More

As data science and machine learning adoption has grown over the last few years, Python is catching up to SQL in popularity within the world of data processing. SQL and Python are both powerful on their own, but their value in modern analytics is highest when they work together.

Winning the race: data as the ultimate competitive edge, with Susie Wolff

Susie Wolff, former Formula 1 driver and founder of Dare to be Different, knows a lot about using data to thrive under pressure. In racing, data is the difference between being a champion and falling behind. How can your business become data driven the way Formula 1 has? How can you get the insights you need to thrive — not tomorrow, not next week, but right now? Industry analyst and digital transformation expert Maribel Lopez interviews Wolff, extracting takeaways that every business can apply.

Using Snowpark For Python And XGBoost To Run 200 Forecasts In 10 Minutes

Snowpark for Python, now generally available, empowers the growing Python community of data scientists, data engineers, and developers to build secure and scalable data pipelines and machine learning (ML) workflows directly within Snowflake—taking advantage of Snowflake’s performance, elasticity, and security benefits, which are critical for production workloads. Using user-defined table functions (UDTFs) and the new Snowpark-optimized warehouse with higher memory, users can run large-scale model training workloads using popular open-source libraries available through Anaconda integration.