Microsoft Power BI

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Modules: 140 Modules
Duration: 14 hours, 25 minutes
Students: 1

Microsoft Power BI opens the gateway to mastering data like never before, offering a complete journey from transformation to visualization. From the very first step, you will be immersed in the essentials of Microsoft Power BI, gaining deep insight into preparing projects, creating data models, and building powerful visualizations. Discover the art of storytelling with data, unravel the secrets of DAX formulas, and explore the power of Microsoft Power BI in the cloud. This course is designed to strengthen your understanding of Microsoft Power BI, enabling you to handle data confidently, structure information efficiently, and turn complex datasets into impactful stories that inspire action.

Learning Outcomes

Understand data preparation and transformation techniques.
Build and structure efficient data models.
Create insightful and interactive visualizations.
Apply essential DAX formulas to enhance data analysis.
Utilize Power BI Service for cloud-based reporting.
Strengthen data security with row-level security methods.

Why buy this Oil and Gas Management course?

Unlimited access to the course for forever
Digital Certificate, Transcript, student ID all included in the price
Absolutely no hidden fees
Directly receive CPD accredited qualifications after course completion
Receive one to one assistance on every weekday from professionals
Immediately receive the PDF certificate after passing
Receive the original copies of your certificate and transcript on the next working day
Easily learn the skills and knowledge from the comfort of your home

Certification

After studying the course materials of the Microsoft Power BI there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99. Original Hard Copy certificates need to be ordered at an additional cost of £8.

Who Is This Course For

Learners new to data analytics wanting a strong foundation.
Professionals aiming to refine their data storytelling skills.
Students looking to explore data transformation methods.
Analysts interested in enhancing visualization techniques.
Anyone curious about DAX formulas and their applications.
Individuals keen to leverage cloud features in Power BI.

Prerequisites

This Microsoft Power BI does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Microsoft Power BI was made by professionals and it is compatible with all PC’s, Mac’s, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.

Career Path

This course opens doors to various roles in the oil and gas sector, including:

Power BI Developer: £50,000 to £85,000 per year
Business Intelligence Analyst: £39,000 to £50,000 per year
Data Analyst: £25,000 to £60,000 per year
Data Scientist: £45,000 to £100,000 per year
Business Intelligence Developer: £42,000 to £54,000 per year
Data Engineer: £40,000 to £90,000 per year

Course Curriculum

Section 01: Introduction
	Welcome!	00:01:00
	What is Power BI?	00:03:00
	Download & Installing Power BI Desktop	00:04:00
	Getting to know the interface	00:03:00
	Mini Project: Transform Data	00:07:00
	Mini Project: Visualize Data	00:05:00
	Mini Project: Creating a Data Model	00:07:00
	Course Outline: What will you learn in this course?	00:05:00
	How to learn best with this course?	00:03:00
Section 02: Preparing our Project
	Creating our initial project file	00:04:00
	Working with the attached project files	00:04:00
Section 03: Data Transformation - The Query Editor
	Exploring the Query Editor	00:06:00
	Connecting to our data source	00:07:00
	Editing rows	00:08:00
	Changing data types	00:08:00
	Replacing values	00:03:00
	Close & Apply	00:03:00
	Connecting to a csv file	00:03:00
	Connecting to a web page	00:05:00
	Extracting characters	00:06:00
	Splitting & merging columns	00:09:00
	Creating conditional columns	00:06:00
	Creating columns from examples	00:09:00
	Merging Queries	00:17:00
	Pivoting & Unpivoting	00:06:00
	Appending Queries	00:08:00
	Practice & Solution: Population table	00:15:00
	The Fact-Dimension-Model	00:09:00
	Practice: Load the dimension table	00:04:00
	Organizing our queries in groups	00:03:00
	Entering data manually	00:05:00
	Creating an index column	00:03:00
	Workflow & more transformations	00:05:00
	Module summary	00:05:00
	Exercise 1 – Instruction	00:02:00
	Exercise Solution	00:11:00
Section 04: Data Transformation - Advanced
	Advanced Editor – Best practices	00:09:00
	Performance: References vs. Duplicating	00:10:00
	Performance: Enable / Disable Load & Report Refresh	00:05:00
	Group by	00:05:00
	Mathematical Operations	00:05:00
	Run R Script	00:15:00
	Using Parameters to dynamically transform data	00:06:00
	M formula language: Basics	00:07:00
	M formula language: Values, Lists & Tables	00:14:00
	M formula language: Functions	00:13:00
	M formula language: More functions & steps	00:05:00
	Exercise 2 – Instructions	00:01:00
	Exercise 2 – solution	00:05:00
Section 05: Creating a Data Model
	Understanding the relationship	00:05:00
	Create & edit relationships	00:06:00
	One-to-many & one-to-one relationship	00:06:00
	Many-to-many (m:n) relationship	00:08:00
	Cross filter direction	00:06:00
	Activate & deactivate relationships	00:06:00
	Model summary	00:03:00
	Exercise 3 Create Model	00:02:00
	Exercise 3 Solution	00:02:00
Section 06: Data Visualization
	Our first visual	00:08:00
	The format tab	00:12:00
	Understanding tables	00:10:00
	Conditional formatting	00:09:00
	The Pie Chart	00:06:00
	All about the filter visual	00:13:00
	The filter pane for developers	00:09:00
	Cross filtering & edit interactions	00:04:00
	Syncing slicers across pages	00:07:00
	Creating drill downs	00:08:00
	Creating drill throughs	00:07:00
	The tree map visual	00:07:00
	The decomposition tree	00:05:00
	Understanding the matrix visual	00:05:00
	Editing pages	00:07:00
	Buttons & Actions	00:09:00
	Bookmarks to customize your report	00:10:00
	Analytics and Forecasts with line charts	00:10:00
	Working with custom visuals	00:07:00
	Get data using R Script & R Script visual	00:08:00
	Asking questions – Q&A visual	00:04:00
	Wrap up – data visualization	00:08:00
Section 07: Power BI & Python
	Python in Power BI – Plan of attack	00:03:00
	Setting up Python for Power BI	00:03:00
	Transforming data using Python	00:11:00
	Creating visualizations using Python	00:08:00
	Violin plots, pair plots & ridge plots using Python	00:15:00
	Machine learning (BayesTextAnalyzer) using Python	00:00:00
	Performance & Troubleshooting	00:03:00
Section 08: Storytelling with Data
	Introduction	00:01:00
	Show Empathy & Identify the Requirement	00:03:00
	Finding the Most Suitable KPI’s	00:02:00
	Choose an Effective Visualization	00:04:00
	Make Use of Natural Reading Pattern	00:03:00
	Tell a Story Using Visual Cues	00:05:00
	Avoid Chaos & Group Information	00:02:00
	Warp Up – Storytelling with Data	00:02:00
Section 09: DAX - The Essentials
	Introduction	00:03:00
	The project data	00:04:00
	Measures vs. Calculated Columns	00:15:00
	Automatically creating a date table in DAX	00:08:00
	CALENDAR	00:05:00
	Creating a complete date table with features	00:04:00
	Creating key measure table	00:03:00
	Aggregation functions	00:06:00
	The different versions of COUNT	00:14:00
	SUMX – Row based calculations	00:09:00
Section 10: DAX - The CALCULATE function
	CALCULATE – The basics	00:11:00
	Changing the context with FILTER	00:07:00
	ALL	00:08:00
	ALL SELECTED	00:03:00
	ALL EXCEPT	00:07:00
Section 11: Power BI Service - Power BI Cloud
	How to go on now?	00:03:00
	Power BI Pro vs Premium & Signing up	00:04:00
	Exploring the interface	00:04:00
	Discovering your workspace	00:03:00
	Connecting Power BI Desktop & Cloud	00:04:00
	Understanding datasets & reports	00:03:00
	Working on reports	00:04:00
	Updating reports from Power BI Desktop	00:04:00
	Creating and working with workspaces	00:07:00
	Installing & using a data gateway	00:13:00
	Get Quick Insights	00:03:00
	Creating dashboards	00:04:00
	Sharing our results through Apps	00:10:00
	Power BI Mobile App	00:05:00
	Creating the layout for the Mobile App	00:04:00
	Wrap up – Power BI Cloud	00:07:00
Section 12: Row-Level Security
	Introduction	00:03:00
	Creating a Row-Level Security	00:05:00
	Row-Level Security in the Cloud	00:04:00
	Row-Level Security & Data Model	00:05:00
	Dynamic Row-Level Security	00:07:00
	Dynamic Many-to-Many RLS	00:04:00
	Hierarchical Row-Level Security	00:13:00
Section 13: More data sources
	JSON & REST API	00:10:00
	Setting up a local MySQL database	00:14:00
	Connecting to a MySQL database in Power BI	00:05:00
	Connecting to a SQL database (PostgreSQL)	00:05:00
Section 14: Next steps to improve & stay up to date
	Congratulations & next steps	00:06:00
	The End	00:01:00
	Resources – Microsoft Power BI Masterclass 2021	00:00:00