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The Complete Power BI Interview Guide

You're reading from The Complete Power BI Interview Guide

Product type Book

Published in Apr 2024

Publisher Packt

ISBN-13 9781805120674

Pages 482 pages

Edition 1st Edition

Languages

Concepts

Business Intelligence

Authors (3):

Sandielly Ortega Polanco

Gogula Aryalingam

Abu Bakar Nisar Alvi

View More author details

Table of Contents (19) Chapters

Preface

Part 1:Getting Your First Interview

Chapter 1: Exposing Your Profile

Chapter 2: Support Skills for Power BI Developers

Part 2: Beyond the Borders of Power BI

Chapter 3: The Power BI Workflow

Chapter 4: Data Analysis with Power BI

Chapter 5: Preparing, Transforming, and Modeling Data

Chapter 6: Exploring, Visualizing, and Sharing Data and Deploying Solutions

Chapter 7: DAX Programming

Chapter 8: Expert Report Building

Chapter 9: Effective Data Storytelling

Chapter 10: Using Dashboards and Apps and Implementing Security

Part 3: The Final Stretch – Preparing for the HR Round and Beyond

Chapter 11: Understanding the HR Interview Process and Preparing for Success

Chapter 12: Tips for Negotiating Salary and Benefits

Chapter 13: Best Practices for Accepting and Rejecting Job Offers – Onboarding and Beyond

Index

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Other Books You May Enjoy

Programming languages

As a data analyst, another skill that I recommend you start including in your toolkit if you don’t already have it is a programming language, and even better if this language is specifically oriented toward data analysis.

Although solutions such as Power BI offer you countless functions to create any type of indicator, there will always be gaps or improvement opportunities that many programming languages already include, such as Python.

Python is currently the most popular programming language for both data-related areas and general programming. This means that you can use Python as a backend programming language, but also use the libraries it contains to analyze data, perform complex mathematical calculations, or create predictive models.

Among the existing libraries that you can use within Python for data analysis, we have the most common ones, which are numpy, pandas, plotly, and scikit-learn. We will learn a little more about them in a bit...

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Authors (3)

Sandielly Ortega Polanco

Sandielly Ortega is a data enthusiast and Business Intelligence advocate, he combines programming expertise with Power BI proficiency to drive data-driven decision-making. With over 8 years of experience, he empowers businesses in various sectors, including hospitality and supply chain. Sandielly is also a content creator on YouTube, a speaker, and resides in Puerto Plata, Dominican Republic, with his family.

See other products by Sandielly Ortega Polanco

Gogula Aryalingam

Gogula Aryalingam has 18+ years of global experience in data analytics and business intelligence, Gogula is a data & AI architect at Fortude. He holds multiple Microsoft MVP awards and certifications, contributing significantly to the development of database and analytics certifications for Microsoft. Gogula is also an author and technical writer for various publications.

See other products by Gogula Aryalingam

Abu Bakar Nisar Alvi

Abu Bakar N. Alvi is a seasoned Product Manager and Project Management Professional with 23+ years of industry experience, Abu Bakar excels in leading cross-functional teams. Holding degrees in Computer Engineering and Satellite Communications, he's a Senior Digital Consultant and Microsoft Certified Trainer. Abu Bakar has earned global certifications, including recognition from the Government of Pakistan.

See other products by Abu Bakar Nisar Alvi

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