For Starburst and Trino developers and data engineers, this announcement means that they no longer need to offload data to frameworks like PySpark and Snowpark to handle complex transformation ...

While Python is ideal for complex and highly customized data transformations, it demands a steep learning curve. Power Query: Power Query simplifies the data cleaning process with its intuitive ...

The second part is LakeFlow Pipelines, which is essentially a version of Databricks’ existing Delta Live Tables framework for implementing data transformation and ETL in either SQL or Python.

It is a handy tool for keeping a record of data explorations, creating charts, styling text and sharing the results of that work. For data analysis, the cornerstone package in Python is “Pandas”.

A transformation factory approach creates a repeatable process that lays the proper data foundation for your transformation.

In 2025, the integration of AI and Python will become increasingly tight. OpenAI's free inference model, o3 - mini, has excelled in areas such as mathematical code generation and physical simulation.

Fostering a data-driven culture is essential in creating the conditions for success in the digital transformation projects that lie ahead for every organization.

Discover 1-minute Python hacks to automate tasks, clean data, and perform advanced analytics in Excel. Boost productivity effortlessly in day ...