Systems | Development | Analytics | API | Testing

Struggling to create a comprehensive customer service report? Here’s everything you need to know, including tips for better data analysis.

ETL pipelines help companies extract, transform, and load data so it is ready to provide insights and value to the company. But running a smooth data operation depends on building reliable and scalable data ingestion pipelines. SaaS vendors like Keboola and Azure Data Factory take away the heavy lifting.

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.

ETL (extract, transform, load) is the backbone of modern data integration, efficiently migrating massive quantities of information into a data warehouse like Snowflake. But with so many Snowflake ETL tools on the market these days, how can you choose the best for migrating your data? Below we’ll discuss our favorite Snowflake ETL tools, including their pros, cons, and user reviews so that you can make the choice that’s right for your situation.