From the course: Complete Guide to Power BI for Data Analysts by Microsoft Press

Learning objectives - Power BI Tutorial

From the course: Complete Guide to Power BI for Data Analysts by Microsoft Press

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Learning objectives

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- As data analysts, chances are you have spent or will spend a lot of time wrangling data that comes in many shapes and sizes and from a multitude of disparate sources. In most organizations, data is scattered and sometimes not managed properly, which complicates the process of preparing data for analytics. Data preparation is often a data analyst's least favorite task. It is estimated that 70% of the work in any analytic endeavor is spent getting your data report ready. The task of consuming and transforming data has long been one of the hardest, yet most important skills for a data analyst to master as they prepare datasets for consumption and presentation. This usually involves removing rows and columns, cleaning erroneous column values, enhancing datasets with new columns, and merging the pending datasets. If you've used Excel for analytics, as many you have for years, you've relied on the mastery of advanced functions inside of Excel, such as VLOOKUP, IF, FIND, CLEAN, and SUBSTITUTE, on top of many traditional import means. In this lesson, we'll explore the capabilities of PowerGrid to help simplify and better automate the process of ingesting and transforming data. If you're used to traditional means using Excel, this functionality is often considered a game changer. Some of the key features of PowerGrid are the following. It has many data connectors available and more being added periodically. You'll see the data gathering and shaping capabilities are fast, easy, and intuitive to use. And one of my favorite things are that transformations are recorded, which allows you to repeat the steps to save manual and repetitive work. Plus, there's some excellent documentation features we will cover. So what does all this add up to? It is often estimated that optimizing the repetitive activities around collecting, combining, and transforming data using Power Query will cut your data preparation time by up to 80%. What we're going to do here is we're going to look at, in Power Query, connecting to data sources, bringing them through the Power Query Editor, doing the extractions, transforming and cleansing data, taking a look at the M language, which is all transformations, and we'll look at loading data into our data model. The learning objectives here that we're going to do an overview of Power Query in 2.1. In 2.2, we'll import United States sales data. We'll import customer data. In 2.4, we'll import sales territory data. We'll import product data in 2.5. Product roll-up in 2.6. Then look at merging the product and product query roll-up queries together. We'll import the other countries' sales data, append the United States sales or other countries' sales query. We'll create columns, We'll manage model loading and cleanup. And finally, we'll organize and document Power Query. Let us begin.

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