FINXL is top Power BI training institution that provides the Power BI training course in UAE , FINXL being among the Top 3 POWER BI training institutions conduct their POWER BI course in a workshop format i.e. FINXL conducts their POWER BI training in a workshop format wherein they conduct 1 month workshop sessions across various colleges in UAE , with a basic motto of providing high quality POWER BI training course with maximum satisfaction for all our students.
Trainers: FINXL being the best Power BI training institution assignee a team of highly experienced trainers that have over 10 years of working experience in this particular field, the trainers conduct the training with a basic motto of providing maximum learning satisfaction for all our students.
In order to achieve our main motto our trainers conduct the Power BI course training in a very interactive manner that include engaging with the students in order to develop maximum interest of all our students, that in return helps in achieving our main motto of providing maximum satisfaction for all our students.
Following are the topics that we being the top Power BI training institution include in our Power BI course.
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We being among the top 5 Power BI training institution have sub -divided our Power BI course curriculum into the following section
This module explores the different roles in the data space, outlines the important roles and responsibilities of data analysts, and then explores the Power BI portfolio environment.
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This module explores the identification and extraction of data from various data sources. You'll also learn about connecting and storing data, and understand the difference and performance impacts of directly connecting to data versus importing it.
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This module will teach you the process of profiling and understanding the health of data. They will learn to identify anomalies, look at the size and shape of their data, and perform proper data cleaning and transformation to prepare the data for loading into the model.
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Through this module, the candidates can acquire knowledge of the fundamental concepts of designing and developing a data model for proper performance and scalability. This module will also help you understand and solve many common data modeling problems, including relationships, security, and performance.
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This module will introduce you to the world of DAX and its true power for model enhancement. You'll learn about aggregations and measure concepts, calculated columns and tables, and Time Intelligence for solving calculation and data analysis problems.
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In this module, you will learn the data modeling steps, processes, concepts, and best practices necessary to optimize your data model for enterprise-level performance.
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This module introduces you to the basic concepts and principles of designing and building a report, including choosing the right visuals, designing a page layout, and using basic but critical features. The important topic of designing for accessibility is also discussed here.
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In this module, you will learn how to tell a compelling story using dashboards and the various navigation tools available to provide navigation. You will be introduced to features and functionality and how to improve dashboards for usability and insight.
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This module helps you use additional features to enhance the report with analytical insights into the data and walks you through the steps to use the report to analyze real data. You'll also perform advanced analytics using AI visuals on the report to gain even deeper and more meaningful insights into the data.
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Through this module, the candidates will acquire knowledge of Workspaces, including how to create and manage them. The candidates will also learn how to share content, including reports and dashboards, and then learn how to distribute your app.
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This module introduces you to parameters and datasets. You'll also learn how to manage datasets and parameters, create dynamic reports with parameters, and set dataset recovery options.
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This module will introduce you to row-level security, static and dynamic methods, and how to implement them.
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