From the course: LinkedIn Learning Highlights: Data Science and Analytics

Exploring business intelligence and Power BI

From the course: LinkedIn Learning Highlights: Data Science and Analytics

Exploring business intelligence and Power BI

(upbeat music) - [Chris] What is Power BI exactly? It's a series of tools you can leverage to analyze your data. The goal of data analytics is to find actionable insights that can help you to make clear decisions and improve performance. Using Power BI, you can ingest your data for exploratory analysis, for modeling, and for visualizing those insights. You want your brand to be a welcome sound to your market's ears, and data analysis for awareness with Power BI will help you to ensure that it is. - [Gini] DAX or Data Analysis Expressions is the language that's used to create formulas for Power BI that extend our data model. DAX gives us the ability to create additional information at runtime so that we can quickly and easily generate new information beyond the information that's in our model already. If you already know how to build data models in Power BI desktop, DAX is a logical next step because there are things that we can do with DAX that we can't do as easily or at all without it. - [Chris] Power Query, aka Get and Transform, allows you to do a number of things. First, you can connect to data across a wide-range of sources. Second, you can filter, shape, append, merge, blend, transform raw data, basically do anything to it before it gets loaded up for further analysis and modeling. And then third, you can create stored and saved procedures to automate each step of your data prep, kind of like a VBA macro. - [Helen] The data query aspect of Tableau can be cumbersome. Importing with already perfectly setup data is easy but that is rarely the reality. Power BI has a lot more capability and flexibility for working with data because it uses Power Query on the backend. This not only makes importing data easy but also makes transforming and shaping this data a flexible process for later use. The process of linking data tables in Power BI saves a lot of time because it eliminates lookup calculations and data joining. - [Gini] The most common way that I create dashboards is starting with my report. Unlike a report, a dashboard is a single page, we don't have tabs for different views of our data. Therefore, it's important that the data we choose to show is the most important data that tells the most compelling story. Another significant difference between dashboards and reports is that our dashboard will support natural language queries, which our report here does not. If I'd like to open a dashboard that already exists I can simply click on the dashboard to open it. Notice, Ask a question about your data, that's a dashboard feature, not a report feature.

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