Data Analyst Training: Microsoft Power BI at QLS Level 7 Diploma

** Designed by Industry Specialist | FREE 2 CPD Courses With Certificates | QLS Level 7 Diploma Course | QLS Hard Copy Certificate Included | 180 CPD Points | Lifetime Access | Installment Payment | Tutor Support **

In an era where 2.5 quintillion bytes of data are produced daily, the ability to process and visualise that data is paramount. Enter Power BI—a tool that's taking the business world by storm. As the global market becomes increasingly data-driven, the role of a competent Data Analyst cannot be overstated. Introducing the "Data Analyst Training: Microsoft Power BI at QLS Level 7 Diploma." Designed by an industry specialist, this all-around course will guide you from the basics to the complicated nuances of Power BI, ensuring that you're not just a participant but a commander in the data revolution.

Experience beyond simple data processing. Get into 14 meticulously crafted modules that cover everything: from establishing a solid foundation in Module 01 to storytelling with data in Module 08 and even integrating advanced languages like Python in Module 07. With each module endorsed by the Quality Licence Scheme, explore mini-projects that bolster your application abilities. By the end, you'll be adept at transforming raw data into actionable insights and compelling stories—giving you a distinctive edge in the global job market.

As businesses globally recognise the vast potential of data, the demand for adept Power BI professionals skyrockets. But why be just another analyst when you can be the best? Train yourself with the "Data Analyst Training: Microsoft Power BI at QLS Level 7 Diploma" and harness the power of data to shape tomorrow. Your journey to global recognition begins here. Enrol now!

★ ADDITIONAL GIFT ★

• Free Course 01: Google Data Studio
• Free Course 02: Business Intelligence and Data Mining

Learning Outcomes:

• Be competent in the foundational concepts of Microsoft Power BI, from installation to interface navigation.
• Develop proficiency in data transformation techniques using the Query Editor.
• Acquire advanced data transformation skills, including dynamic data operations with the M formula language.
• Comprehend the intricacies of creating robust and efficient data models with diverse relationships.
• Formulate compelling visual representations of data, exploring visuals like pie charts, treemaps, and matrix visuals.
• Integrate Python within Power BI, enabling advanced data manipulation and machine learning capabilities.
• Narrate compelling data-driven stories, leveraging effective visualisation and storytelling techniques.
• Grasp the essentials of DAX for powerful data operations, from basic aggregations to context manipulations with CALCULATE.
• Navigate and optimise the Power BI Cloud Service, ensuring seamless data presentations and platform sharing.
• Implement advanced security measures, understanding row-level security for safeguarding sensitive data.

Experience the transformative world of data with our "Data Analyst Training: Microsoft Power BI at QLS Level 7 Diploma". Prepared by industry experts, this course bridges foundational concepts with advanced techniques, enabling learners to extract, visualise, and communicate insights effectively. From conquering Power BI's interface to advanced data storytelling, integrate Python and DAX for a holistic analytical experience. Ideal for aspiring data professionals, this course promises hands-on projects and mastery of the global market.

Course Curriculum:

** Data Analyst Training: Microsoft Power BI at QLS Level 7 Diploma **

Module 01: Introduction

• Welcome!
• What is Power BI?
• Download & Installing Power BI Desktop
• Getting to know the interface
• Mini Project: Transform Data
• Mini Project: Visualise Data
• Mini Project: Creating a Data Model
• Course Outline: What will you learn in this course?
• How to learn best with this course?

Module 02: Preparing our Project

• Creating our initial project file
• Working with the attached project files

Module 03: Data Transformation - The Query Editor

• Exploring the Query Editor
• Connecting to our data source
• Editing rows
• Changing data types
• Replacing values
• Close & Apply
• Connecting to a CSV file
• Connecting to a web page
• Extracting characters
• Splitting & merging columns
• Creating conditional columns
• Creating columns from examples
• Merging Queries
• Pivoting & Unpivoting
• Appending Queries
• Practice & Solution: Population table
• The Fact-Dimension-Model
• Practice: Load the dimension table
• Organising our queries in groups
• Entering data manually
• Creating an index column
• Workflow & more transformations
• Module summary
• Exercise 1 – Instruction
• Exercise Solution

Module 04: Data Transformation - Advanced

• Advanced Editor – Best practices
• Performance: References vs. Duplicating
• Performance: Enable / Disable Load & Report Refresh
• Group by
• Mathematical Operations
• Run R Script
• Using Parameters to transform data dynamically
• M formula language: Basics
• M formula language: Values, Lists & Tables
• M formula language: Functions
• M formula language: More functions & steps
• Exercise 2 – Instructions
• Exercise 2 – Solution

Module 05: Creating a Data Model

• Understanding the relationship
• Create & edit relationships
• One-to-many & one-to-one relationship
• Many-to-many (m:n) relationship
• Cross filter direction
• Activate & deactivate relationships
• Model summary
• Exercise 3 Create Model
• Exercise 3 Solution

Module 06: Data Visualisation

• Our first visual
• The format tab
• Understanding tables
• Conditional formatting
• The Pie Chart
• All about the filtered visual
• The filter pane for developers
• Cross-filtering & editing interactions
• Syncing slicers across pages
• Creating drill-downs
• Creating drill throughs
• The treemap visual
• The decomposition tree
• Understanding the matrix visual
• Editing pages
• Buttons & Actions
• Bookmarks to customise your report
• Analytics and Forecasts with line charts
• Working with custom visuals
• Get data using R Script & R Script visual
• Asking questions – Q&A visual
• Wrap up – data visualisation

Module 07: Power BI & Python

• Python in Power BI – Plan of attack
• Setting up Python for Power BI
• Transforming data using Python
• Creating visualisations using Python
• Violin plots, pair plots & ridge plots using Python
• Machine learning (Bayes Text Analyser) using Python
• Performance & Troubleshooting

Module 08: Storytelling with Data

• Introduction
• Show Empathy & Identify the Requirement
• Finding the Most Suitable KPIs
• Choose an Effective Visualisation
• Make Use of Natural Reading Patterns
• Tell a Story Using Visual Cues
• Avoid Chaos & Group Information
• Warp Up – Storytelling with Data

Module 09: DAX - The Essentials

• Introduction
• The project data
• Measures vs. Calculated Columns
• Automatically creating a date table in DAX
• CALENDAR
• Creating a complete date table with features
• Creating a key measurement table
• Aggregation functions
• The different versions of COUNT
• SUMX – Row-based calculations

Module 10: DAX - The CALCULATE function

• Calculate – The basics
• Changing the context with FILTER
• All
• All SELECTED
• All Except

Module 11: Power BI Service - Power BI Cloud

• How to go on now?
• Power BI Pro vs Premium & Signing up
• Exploring the interface
• Discovering your workspace
• Connecting Power BI Desktop & Cloud
• Understanding datasets & reports
• Working on reports
• Updating reports from Power BI Desktop
• Creating and working with workspaces
• Installing & using a data gateway
• Get Quick Insights
• Creating dashboards
• Sharing our results through Apps
• Power BI Mobile App
• Creating the layout for the Mobile App
• Wrap up – Power BI Cloud

Module 12: Row-Level Security

• Introduction
• Creating a Row-Level Security
• Row-Level Security in the Cloud
• Row-Level Security & Data Model
• Dynamic Row-Level Security
• Dynamic Many-to-Many RLS
• Hierarchical Row-Level Security

Module 13: More data sources

• JSON & REST API
• Setting up a local MySQL database
• Connecting to a MySQL database in Power BI
• Connecting to a SQL database (PostgreSQL)

Module 14: Next steps to improve & stay up to date

• Congratulations & next steps
• The End

Disclaimer:

This course has been endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. This course is not regulated by Ofqual and is not an accredited qualification. Imperial Academy is an approved reselling partner for Quality Licence Scheme courses under One Education. One Education will be able to advise you on any further recognition. For details, please visit the Learner FAQs on the Quality Licence Scheme website.

This Data Analyst Training: Microsoft Power BI at QLS Level 7 Diploma course is appropriate for the following:

• Aspiring data analysts eager to kickstart or advance their careers in the data visualization realm.
• Business professionals wanting to harness data-driven insights for strategic decision-making.
• Researchers and academicians aiming to represent complex data sets in easily digestible visuals.
• IT specialists looking to expand their skill set into the booming field of data analytics and visualization.
• Companies and teams aiming to upskill their members for improved data-driven operations and reporting.

No requirements to enrol in Data Analyst Training: Microsoft Power BI at QLS Level 7 Diploma.

• Data Analyst: £25,000 - £40,000
• Software Engineer: £28,000 - £55,000
• Marketing Manager: £30,000 - £50,000
• Civil Engineer: £27,000 - £52,000
• Graphic Designer: £21,000 - £37,000
• Solicitor: £30,000 - £60,000

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Hard Copy QLS Certificate

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