By Liam Bastick – In Power BI Desktop, a dataset is defined by a single query that specifies what data to include and how to transform it. The query is made up of related steps that build upon one another to produce the final dataset, which can be used to create visualisations for reports and dashboards that may be published to the Power BI Service (which you may recall is the cloud-based service where you will typically upload your data, run cloud-based analytics tools, and share reports and dashboards).

Anyone can get started on Power BI. The interface is highly intuitive, and with practice, you will soon become efficient and effective. Power BI offers a ribbon with almost every function you need to transform a dataset and provides a list of APPLIED STEPS where you may track your work, as shown in the screenshot below.

As you become more experienced, you may be seduced into working with the Advanced Editor, which is backed by the Power Query M formula language, a case-sensitive, data mashup language used to transform your data. M is a step-by-step sequential language structure: usually, every line in M script is a data transformation step, and the step after that will use the result of the previous step, as illustrated in the screenshot below. Read On: