Our experience has taught us that building data pipelines can be complex, especially if you are new to them. Here are some of the pitfalls we’ve come across when building data pipelines in partnership with clients. It’s our hope it will help you to navigate them in the future.

Data and analytics are critical to business operations, so it’s important to engineer and deploy strong and maintainable data pipelines. Here are some of the essential practices we recommend you follow to achieve this.

Here we introduce six of the practices you should follow when creating data pipelines. From how to use raw data to starting with a steel thread, applying these practices will allow you to integrate new data sources faster at a higher quality.

Pipelines bring data from important business sources. To endure for a long time, these will always need to follow a few simple key principles to ensure they are fit for purpose. Here are our six key principles for adoption.

Creating more effective data pipelines helps your organisation to benefit from faster innovation, higher quality (with improved reliability), reduced costs, and happy people. There are many benefits, so here we have highlighted our top six.

A data pipeline transports your data from where it is generated to where it can be analysed. Discover how effective ones are critical for any organisation that wants to take data analysis seriously and generate insight that leads to business value.