BI and data visualization skills are in demand and Microsoft Power BI skills are a great way to get ahead. Here's our guide to Microsoft's Data Analyst Associate certification. Credit: DNY59 / Getty Images Data analysts work with data to help their organizations make better business decisions. Using techniques from a range of disciplines, including computer programming, mathematics, and statistics, data analysts draw conclusions from data to describe, predict, and improve business performance. They form the core of any analytics team and tend to be generalists versed in the methods of mathematical and statistical analysis. (See CIO’s guide to top big data and data analytics certifications.) The data analyst role is in high demand, as organizations are growing their analytics capabilities at a rapid clip. In August, research firm IDC forecast worldwide spending on big data and business analytics solutions would reach $215.7 billion this year, up 10.1% over 2020. The firm believes spending will continue to gain strength over the next five years, with a compound annual growth rate (CAGR) of 12.8% from 2021-2025. According to Glassdoor, data analysts with Power BI skills command salaries of $62K to $125K per year ($88,303 average). What is a Microsoft Certified: Data Analyst Associate? Microsoft certified data analyst associates are subject matter experts that can design and build scalable data models, clean and transform data, and provide business value via data visualizations. The certification is intended for data professionals and business intelligence (BI) professionals who use Power BI to develop reports and dashboards that visualize data, whether in the cloud or on-premises. The certification requires passing the Analyzing Data with Microsoft Power BI certification exam administered via Pearson VUE. The exam measures the candidate’s ability to prepare data, visualize data, analyze data, and deploy and maintain deliverables. How to prepare for the Analyzing Data with Microsoft Power BI exam Candidates have two options to prepare for the exam: free online courses or instructor-led, paid training. For the free courses, Microsoft recommends a series of six learning paths that cover the necessary skills: Get started with Microsoft data analytics: This learning path provides an overview of data analysis and the role of a data analyst, as well as the skills, tasks, and processes they employ to tell a story with data. It consists of two modules and takes 1 hour and 10 minutes to complete. Prepare data for analysis: This learning path focuses on using Power Query to extract data from various data sources (Microsoft Excel, relational databases, NoSQL data stores) and how to choose a storage mode and connectivity type. It teaches how to profile, clean, and load data into Power BI in preparation for modeling data. It consists of two modules that take 3 hours and 26 minutes to complete. Model data in Power BI: This learning path teaches how to design data models and use Data Analysis Expressions (DAX), the native formula and query language of Microsoft Power BI, to create measures. It consists of three modules that take 5 hours and 31 minutes to complete. Visualize data in Power BI: This learning path teaches analysts how to select the right visuals to solve a given problem. It covers report design and formatting, how to use report navigation to tell data-driven stories, and how dashboards can help users target report visuals to meet specific needs. It consists of four modules that take 5 hours and 5 minutes to complete. Data analysis in Power BI: This learning path teaches how to use Power BI to perform data analytical functions. It covers identifying outliers in data, performing time-series analysis, using advanced analytic features, and working with AI visuals. It consists of two modules that take an hour and 52 minutes to complete. Manage workspaces and datasets in Power BI: This learning path covers creating workspaces in the Power BI service. It teaches how to deploy Power BI artifacts and share them with users, how to connect Power BI reports to on-premises data sources, configure automatic refresh for Power BI datasets, and apply row-level security to restrict users to the data that applies to them. It consists of three modules that take an hour and 10 minutes to complete. Microsoft also provides a paid, four-day, instructor-led training course for the certification via its learning partners. The course covers the methods and best practices for modeling, visualizing, and analyzing data with Power BI. It teaches how to access and process data from a range of data sources, including both relational databases and nonrelational data stores. It also covers how to implement security standards and policies, and how to manage and deploy reports and dashboards for sharing and content distribution. The price varies by country and learning partner. Numerous practice tests and training resources are also available for the exam, including: Power BI Practice Sets Year 2021 from Udemy ($18.99)Analyzing Data with Microsoft Power BI (DA-100) Practice Exam from testprep training ($11.99)DA-100 Exam Prep – Power BI Certification from BI Elite Training ($29) Taking the Analyzing Data with Microsoft Power BI exam The Analyzing Data with Microsoft Power BI exam is offered via Pearson VUE and costs $165 in the US (the price varies based on the country in which the exam is proctored). For a limited time, Microsoft is offering discounted certification to qualifying individuals who have been laid off or furloughed due to the COVID-19 pandemic. To be eligible for the discount, individuals must schedule their exam before Dec. 30, 2021, and have until Dec. 31, 2021, to complete the exam. The exam measures the candidate’s ability to perform technical tasks, including: Prepare data (20%-25%)Model data (25%-30%)Visualize data (20%-25%)Analyze data (10%-15%)Deploy and maintain deliverables (10%-15%) Microsoft offers a thorough breakdown of the skills measured within each task. Related content opinion The cyber pandemic: AI deepfakes and the future of security and identity verification Attackers have seen huge success using AI deepfakes for injection and presentation attacks – which means we’ll only see more of them. Advanced technology can help prevent (not just detect them). By Aaron Painter May 02, 2024 5 mins Artificial Intelligence Security brandpost Sponsored by Cisco Transform the modern data center: From today to the future Embrace agility, elasticity, and cognitive intelligence capabilities for a data center strategy that’s performance-ready and sustainable for the future. 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