High quality data is critical in driving innovation and effective decision making for businesses. Here, Sanket Gaikwad outlines example processes and tools to help ensure data quality in your processes.

Serving a wide range of stakeholders, the Australian Trade and Investment Commission (also known as Austrade) delivers services to grow Australia’s economic prosperity. To support the team in their excellent work, I was happy to deliver a brief presentation on the importance and value of data pipelines. Here are some of the key points that seemed to resonate throughout the presentation.

Learn why we advocate that data oriented projects should always use the well-known software engineering best practices. This article shows how you can apply TDD using the emerging dbt data transformation tool.

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.