MSPTDA 18: DAX Iterators Table Functions Grain Cardinality Materializing Tables Excel & Power BI
This course covers the fundamentals of DAX Iterators, Table Functions, Grain, Cardinality, Materializing Tables, Excel and Power BI. It provides an introduction to Iterator Functions, how to use SUMX and AVERAGEX Iterating Over Fact Table at Transaction Grain, and how to use DAX Studio to time DAX Formulas. It also covers the use of Power Query to add Primary Key, AVERAGEX at Day Grain, VALUES and CROSSJOIN DAX Functions, and DISTINCT and ALLNOBLANKROW DAX Functions. Finally, it covers Excel Existing Connections and the use of DAX VALUES Function to pull a variable from an Excel Sheet into the Data Model. ▼
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Course Feature
Cost:
Free
Provider:
Youtube
Certificate:
Paid Certification
Language:
English
Start Date:
On-Demand
Course Overview
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Updated in [February 21st, 2023]
This course, MSPTDA 18: DAX Iterators Table Functions Grain Cardinality Materializing Tables Excel & Power BI, provides an introduction to the DAX language and its Iterator and Table Functions. It covers topics such as Iterator Functions, Context Transition, Materializing Tables, DAX Studio, Power BI, Grain of Fact Table, VALUES, CROSSJOIN, CONCATENATEX, DISTINCT, ALLNOBLANKROW, FILTER, CALCULATETABLE, ADDCOLUMNS, and Excel Existing Connections. Participants will learn how to use these functions to create measures, tables, and visualizations in Power BI and Excel. They will also learn how to time DAX formulas and reduce cardinality. At the end of the course, participants will have a better understanding of the DAX language and its Iterator and Table Functions.
[Applications]
The application of this course can be seen in the use of DAX Iterators and Table Functions to create more efficient and accurate data analysis. Students can use the knowledge gained from this course to create measures and tables that are optimized for performance and accuracy. Additionally, students can use the techniques learned to create pivot tables and Power BI reports that are more efficient and accurate. Finally, students can use the knowledge gained to create Excel connections to pull data from the Data Model into Excel sheets, and use the DAX VALUES function to pull a variable from an Excel sheet into the Data Model.
[Career Paths]
1. Data Analyst: Data analysts are responsible for collecting, organizing, and analyzing data to help inform business decisions. They use a variety of tools and techniques to uncover trends and insights in data, and then communicate their findings to stakeholders. Data analysts are in high demand as businesses increasingly rely on data-driven decision making.
2. Business Intelligence Developer: Business intelligence developers are responsible for designing and developing data warehouses and business intelligence solutions. They use a variety of tools and techniques to create data models, develop ETL processes, and create reports and dashboards. Business intelligence developers are in high demand as businesses increasingly rely on data-driven decision making.
3. Data Scientist: Data scientists are responsible for extracting insights from large datasets. They use a variety of tools and techniques to uncover patterns and trends in data, and then communicate their findings to stakeholders. Data scientists are in high demand as businesses increasingly rely on data-driven decision making.
4. Data Visualization Specialist: Data visualization specialists are responsible for creating visual representations of data. They use a variety of tools and techniques to create charts, graphs, and other visualizations that help stakeholders understand data. Data visualization specialists are in high demand as businesses increasingly rely on data-driven decision making.
[Education Paths]
1. Bachelor's Degree in Data Science: Data Science is a rapidly growing field that combines mathematics, computer science, and statistics to analyze and interpret data. It is used to gain insights from data and make predictions. With a Bachelor's Degree in Data Science, you will learn the fundamentals of data analysis, data visualization, machine learning, and more. You will also gain the skills needed to work with large datasets and develop algorithms to solve complex problems. As the demand for data scientists continues to grow, so does the need for qualified professionals with a Bachelor's Degree in Data Science.
2. Master's Degree in Business Analytics: Business Analytics is a field that uses data to make decisions and improve business performance. With a Master's Degree in Business Analytics, you will learn how to analyze data, develop models, and create strategies to improve business operations. You will also gain the skills needed to interpret data and make informed decisions. As businesses become increasingly data-driven, the need for qualified professionals with a Master's Degree in Business Analytics is growing.
3. Doctorate Degree in Artificial Intelligence: Artificial Intelligence (AI) is a rapidly growing field that uses algorithms and data to create intelligent systems. With a Doctorate Degree in Artificial Intelligence, you will learn the fundamentals of AI, including machine learning, natural language processing, and computer vision. You will also gain the skills needed to develop AI systems and create algorithms to solve complex problems. As AI continues to become more prevalent in our lives, the need for qualified professionals with a Doctorate Degree in Artificial Intelligence is growing.
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