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Ivan Vega, Joseph Lozada, and Daniel Roca

Take your understanding of Data Modeling & Preparation to the next level with Udacity's online training course. Develop the skills you need to grow your career.

Prerequisite details

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Take your understanding of Data Modeling & Preparation to the next level with Udacity's online training course. Develop the skills you need to grow your career.

Prerequisite details

To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:

  • Data quality control
  • Chart types
  • Data analysis process
  • Excel
  • Exploratory data analysis
  • Data visualization

You will also need to be able to communicate fluently and professionally in written and spoken English.

What's inside

Syllabus

Introduction to Data Preparation & Modeling lesson introduces students to the topics, highlights, and prerequisites of the course. And requirements to successfully complete the course are explained.
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Relational Data & Table Structure lesson teaches the core concepts around working with data from multiple sources and tables. It explains what relational data is and how it works.
Power Query & M Overview lesson highlights the Power Query data wrangling system that is used within Power BI. Specific cleaning and organization tools and techniques are explored.
Data Cleaning & Organization lesson takes a practical deep dive into Power Query. Here more complex data cleaning and organization strategies are practiced, and the M language is explained.
DAX Language & Quantitative Analysis lesson dives into DAX, which is the primary analytical language of Power BI. Different foundational concepts around DAX calculations are covered.
The project asks students to gather data about the US economy to understand better the makeup of the economy and how it’s changing. Students will submit a PowerBI report at the end.
In this lesson, you'll learn how to set up a Windows desktop workspace to use Power BI

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores in-demand skills in data preparation and modeling, improving career prospects
Focuses on data cleaning, organization, and analytical calculations using Power BI, fostering practical data handling abilities
Emphasizes foundational data analytics concepts and techniques, building a solid knowledge base for beginners
Taught by industry professionals, ensuring real-world relevance and expertise in data modeling and preparation
Leverages Power Query, a widely used data wrangling system, enhancing practical application and industry relevance
Requires prior knowledge in data quality control, chart types, and data analysis, indicating a suitable fit for learners with some foundational understanding in data handling

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Preparation and Modeling with these activities:
Review Data Modeling Concepts
Reviewing data modeling concepts will provide a refresher of the underlying principles and ensure you have a solid foundation before delving into Power BI.
Browse courses on Data Modeling
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  • Study notes or textbooks on data modeling.
  • Complete practice exercises to test your understanding.
Review Data Analysis with Power BI
Reviewing this book will help refresh your understanding of key concepts from relational databases to DAX and quantitative analysis as it applies to Power BI.
View Optimizing DAX on Amazon
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  • Read the introduction and skim the table of contents to familiarize yourself with the book's structure and topics.
  • Review the chapter on relational data and table structure to solidify your understanding of how to work with multiple sources and tables.
  • Explore the chapter on Power Query and M Overview to get hands-on with data wrangling and manipulation.
  • Dive into the chapter on data cleaning and organization to practice managing complex data sets.
  • Finish by reviewing the chapter on DAX Language and Quantitative Analysis to strengthen your analytical skills with DAX.
Practice Data Cleaning
Practicing data cleaning will improve your proficiency in managing and preparing data for analysis, ensuring you can effectively work with real-world data sets.
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  • Find data sets with common data quality issues.
  • Apply data cleaning techniques to address issues such as missing values, outliers, and inconsistencies.
Four other activities
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Show all seven activities
Explore Power BI Tutorials
Following tutorials will allow you to expand your understanding of Power BI's capabilities and learn new techniques.
Browse courses on Power BI
Show steps
  • Search for tutorials that cover specific topics or features you want to explore.
  • Follow the instructions and complete the exercises provided in the tutorials.
  • Experiment with the concepts learned and apply them to your own projects.
Solve Power BI Practice Problems
Solving practice problems will reinforce your understanding of data preparation and modeling techniques and provide hands-on experience with Power BI.
Browse courses on Power BI
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  • Find practice problems online or in textbooks.
  • Attempt to solve the problems independently.
  • Review your solutions against provided answers or ask for help from instructors or peers.
Attend a Power BI Workshop
Attending a workshop will provide you with a structured learning environment tailored to enhancing your Power BI knowledge and skills.
Browse courses on Power BI
Show steps
  • Identify and register for a relevant workshop.
  • Attend the workshop and actively participate in activities.
  • Network with other participants and industry professionals.
Create a Power BI Report
Creating a report will allow you to demonstrate your ability to synthesize data, analyze it, and present insights effectively using Power BI.
Browse courses on Power BI
Show steps
  • Gather data from relevant sources.
  • Clean and prepare the data in Power BI.
  • Develop visualizations and dashboards to illustrate your findings.
  • Write a report summarizing your analysis and insights.
  • Share your report with others for feedback and discussion.

Career center

Learners who complete Data Preparation and Modeling will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use data to solve business problems and develop new products and services. This course provides a strong foundation in data preparation and modeling, which are essential skills for Data Scientists. The skills and knowledge you'll gain in this course will help you prepare for a career as a Data Scientist.
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models to solve real-world problems. This course provides a strong foundation in data preparation and modeling, which are essential skills for Machine Learning Engineers. The skills and knowledge you'll gain in this course will help you prepare for a career as a Machine Learning Engineer.
Business Analyst
Business Analysts help businesses improve their operations by analyzing data and identifying inefficiencies. This course provides a strong foundation in data preparation and modeling, which are essential skills for Business Analysts. The skills and knowledge you'll gain in this course will help you prepare for a career as a Business Analyst.
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course provides a strong foundation in data preparation and modeling, which are essential skills for Data Analysts. The skills and knowledge you'll gain in this course will help you prepare for a career as a Data Analyst.
Data Engineer
Data Engineers design and build the systems that store and process data. This course provides a strong foundation in data preparation and modeling, which are essential skills for Data Engineers. The skills and knowledge you'll gain in this course will help you prepare for a career as a Data Engineer.
Statistician
Statisticians collect, analyze, and interpret data to help businesses make informed decisions. This course provides a strong foundation in data preparation and modeling, which are essential skills for Statisticians. The skills and knowledge you'll gain in this course will help you prepare for a career as a Statistician.
Financial Analyst
Financial Analysts use data to analyze financial markets and make investment recommendations. This course provides a strong foundation in data preparation and modeling, which are essential skills for Financial Analysts. The skills and knowledge you'll gain in this course will help you prepare for a career as a Financial Analyst.
Marketing Analyst
Marketing Analysts use data to analyze marketing campaigns and make recommendations for improvement. This course provides a strong foundation in data preparation and modeling, which are essential skills for Marketing Analysts. The skills and knowledge you'll gain in this course will help you prepare for a career as a Marketing Analyst.
Risk Analyst
Risk Analysts use data to identify and manage risks. This course provides a strong foundation in data preparation and modeling, which are essential skills for Risk Analysts. The skills and knowledge you'll gain in this course will help you prepare for a career as a Risk Analyst.
Operations Research Analyst
Operations Research Analysts use data to analyze and optimize business operations. This course provides a strong foundation in data preparation and modeling, which are essential skills for Operations Research Analysts. The skills and knowledge you'll gain in this course will help you prepare for a career as an Operations Research Analyst.
Data Architect
Data Architects design and manage data systems. This course provides a strong foundation in data preparation and modeling, which are essential skills for Data Architects. The skills and knowledge you'll gain in this course will help you prepare for a career as a Data Architect.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course provides a strong foundation in data preparation and modeling, which are essential skills for Software Engineers. The skills and knowledge you'll gain in this course will help you prepare for a career as a Software Engineer.
Computer Scientist
Computer Scientists research and develop new computing technologies. This course provides a strong foundation in data preparation and modeling, which are essential skills for Computer Scientists. The skills and knowledge you'll gain in this course will help you prepare for a career as a Computer Scientist.
Database Administrator
Database Administrators manage and maintain databases. This course provides a strong foundation in data preparation and modeling, which are essential skills for Database Administrators. The skills and knowledge you'll gain in this course will help you prepare for a career as a Database Administrator.
Information Security Analyst
Information Security Analysts protect computer systems and networks from unauthorized access. This course provides a strong foundation in data preparation and modeling, which are essential skills for Information Security Analysts. The skills and knowledge you'll gain in this course will help you prepare for a career as an Information Security Analyst.

Reading list

We've selected 15 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Preparation and Modeling.
Classic in the field of data modeling and provides a comprehensive overview of the subject. It is particularly valuable for its coverage of data modeling concepts and techniques.
Practical guide to dimensional modeling, which key technique for data warehousing. It provides step-by-step instructions on how to design and implement a data warehouse.
Provides a comprehensive guide to using Power BI for data modeling and business intelligence. It is particularly valuable for its coverage of Power BI's data modeling capabilities and DAX language.
Provides a comprehensive guide to statistical learning. It is helpful for learners who want to gain a deeper understanding of the concepts and techniques used in statistical learning.
Provides a comprehensive guide to data warehousing. It is helpful for learners who want to gain a deeper understanding of the concepts and techniques used in data warehousing.
Provides a comprehensive guide to deep learning. It is helpful for learners who want to gain a deeper understanding of the concepts and techniques used in deep learning.
Provides a collection of recipes for solving common DAX problems. It is helpful for learners who want to quickly find solutions to specific problems.
Provides a comprehensive overview of data quality best practices and techniques. It is particularly valuable for its coverage of data quality metrics and data cleansing methods.
Provides a practical approach to data modeling for beginners. It is helpful for learners who want to gain a foundational understanding of data modeling concepts.
Provides a simplified approach to machine learning. It is helpful for learners who want to gain a basic understanding of machine learning concepts without getting bogged down in technical details.
Provides a simplified approach to data modeling. It is helpful for learners who want to gain a basic understanding of data modeling concepts without getting bogged down in technical details.
Provides a simplified approach to artificial intelligence. It is helpful for learners who want to gain a basic understanding of artificial intelligence concepts without getting bogged down in technical details.
Provides a simplified approach to natural language processing. It is helpful for learners who want to gain a basic understanding of natural language processing concepts without getting bogged down in technical details.
Provides a simplified approach to computer vision. It is helpful for learners who want to gain a basic understanding of computer vision concepts without getting bogged down in technical details.
Provides a simplified approach to data mining. It is helpful for learners who want to gain a basic understanding of data mining concepts without getting bogged down in technical details.

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