PWRBI-EXCEL.AP1
Analyzing Data with Power BI and Power Pivot for Excel
Learn to effectively analyze, visualize, and report on data using Excel, Power BI, and Power Pivot to make informed business decisions.
- Practice in 21 Laboratorios prácticos — nothing to install
- 13 Lecciones interactivas y 69 topics mapped to the official exam objectives
- 123 Preguntas del examen de práctica
Intermediate A tu propio ritmo · 1 año de acceso 4.6/5 (141 Revisar)
21 LiveLabs prácticos
Practice real IT tasks in guided environments.
- Entornos reales
- Calificación automática
- Sin instalación
13Lecciones interactivas
69Topics
21Laboratorio en vivo
123Preguntas del examen de práctica
43Tarjetas didácticas
43Glosario de términos
01 / Habilidades que obtendrás
What you will be able to do
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No se requiere tarjeta de crédito
Get your hands dirty with data analysis using the Power BI app and Power Pivot tool within Excel. This hands-on training course arms you with skills to analyze, visualize, and report information. You’ll learn to connect various data sources, build data models, create dashboards, and perform advanced analysis techniques that will spot hidden insights. With this “Analyzing data with Power BI” course, you’ll make decisions to improve your business processes and get ahead of the competition in the data-centric industry.
- Become proficient in using Excel, Power Pivot, and Power BI for data analysis and data visualization
- Connect various data sources, such as Excel, SQL Server, CSV files, and online databases
- Learn to create effective star and snowflake schemas, establish relationships, and implement hierarchies
- Utilize DAX (Data Analysis Expressions) to create calculated columns, measures, and perform complex calculations
- Develop visually appealing and informative dashboards and reports to communicate insights effectively
- Understand and apply various data analysis techniques, including time intelligence, data cleansing, and performance optimization
- Integrate Power BI with other tools and technologies, such as SQL Server and Python
Target Career Roles
- Contadores Estimador de costos Periodista de datos Gerente minorista Gerente de proyectos Analista de negocios Analista financiero Empleado de información Asistente administrativo
02 / Lecciones y laboratorios
See exactly what you will learn and practice
Plan de estudios
13 Lecciones interactivas · 69 topics01 Introduction 3 topics +
- Who this course is for?
- Organization of this course
- Conventions
02 Introduction to data modeling 5 topics · 1 Laboratorio en vivo +
- Working with a single table
- Introducing the data model
- Introducing star schemas
- Understanding the importance of naming objects
- Conclusions
1 Laboratorio en vivo in this lesson — see the labs panel →
03 Using header/detail tables 4 topics · 1 Laboratorio en vivo +
- Introducing header/detail
- Aggregating values from the header
- Flattening header/detail
- Conclusions
1 Laboratorio en vivo in this lesson — see the labs panel →
04 Using multiple fact tables 5 topics · 2 Laboratorio en vivo +
- Using denormalized fact tables
- Filtering across dimensions
- Understanding model ambiguity
- Using orders and invoices
- Conclusions
2 Laboratorio en vivo in this lesson — see the labs panel →
05 Working with date and time 10 topics · 1 Laboratorio en vivo +
- Creating a date dimension
- Understanding automatic time dimensions
- Using multiple date dimensions
- Handling date and time
- Time-intelligence calculations
- Handling fiscal calendars
- Computing with working days
- Handling special periods of the year
- Working with weekly calendars
- Conclusions
1 Laboratorio en vivo in this lesson — see the labs panel →
06 Tracking historical attributes 6 topics · 1 Laboratorio en vivo +
- Introducing slowly changing dimensions
- Using slowly changing dimensions
- Loading slowly changing dimensions
- Rapidly changing dimensions
- Choosing the right modeling technique
- Conclusions
1 Laboratorio en vivo in this lesson — see the labs panel →
07 Using snapshots 5 topics · 3 Laboratorio en vivo +
- Using data that you cannot aggregate over time
- Aggregating snapshots
- Understanding derived snapshots
- Understanding the transition matrix
- Conclusions
3 Laboratorio en vivo in this lesson — see the labs panel →
08 Analyzing date and time intervals 7 topics · 4 Laboratorio en vivo +
- Introduction to temporal data
- Aggregating with simple intervals
- Intervals crossing dates
- Modeling working shifts and time shifting
- Analyzing active events
- Mixing different durations
- Conclusions
4 Laboratorio en vivo in this lesson — see the labs panel →
09 Many-to-many relationships 5 topics · 2 Laboratorio en vivo +
- Introducing many-to-many relationships
- Cascading many-to-many
- Temporal many-to-many
- Using the fact tables as a bridge
- Conclusions
2 Laboratorio en vivo in this lesson — see the labs panel →
10 Working with different granularity 3 topics · 1 Laboratorio en vivo +
- Introduction to granularity
- Relationships at different granularity
- Conclusions
1 Laboratorio en vivo in this lesson — see the labs panel →
11 Segmentation data models 5 topics · 3 Laboratorio en vivo +
- Computing multiple-column relationships
- Computing static segmentation
- Using dynamic segmentation
- Understanding the power of calculated columns: ABC analysis
- Conclusions
3 Laboratorio en vivo in this lesson — see the labs panel →
12 Working with multiple currencies 5 topics · 2 Laboratorio en vivo +
- Understanding different scenarios
- Multiple source currencies, single reporting currency
- Single source currency, multiple reporting currencies
- Multiple source currencies, multiple reporting currencies
- Conclusions
2 Laboratorio en vivo in this lesson — see the labs panel →
13 Appendix A. Data modeling 101 6 topics +
- Tables
- Data types
- Relationships
- Filtering and cross-filtering
- Different types of models
- Measures and additivity
Laboratorios prácticos Our edge
21 Laboratorio en vivos- Exploring a Dataset
- Aggregating Values from the Header Table
- Analyzing Denormalized Fact Tables
- Understanding Model Ambiguity
- Creating a Date Dimension
- Analyzing Slowly Changing Dimensions
- Analyzing Snapshots
- Analyzing Derived Snapshots
- Understanding the Transition Matrix
- Understanding Temporal Data
- Analyzing Events that Cross Dates
- Analyzing Active Events
- Mixing Different Durations
- Exploring Many-to-Many Relationships
- Exploring a Temporal Many-to-Many Relationship
- Analyzing Relationships at Different Granularity
- Analyzing Calculated Physical Relationships
- Analyzing Dynamic Segmentation
- Understanding ABC Analysis
- Producing a Report Containing Information With a Single Type of Currency
- Producing a Report in Multiple Currencies
Los laboratorios se ejecutan en tu navegador; no hay nada que instalar.
03 / Preguntas frecuentes
Preguntas antes de empezar
What is Power BI and Power Pivot?+
Power BI is a business intelligence tool for analyzing and visualizing data, while Power Pivot is a data modeling engine within Excel.
How do Power BI and Power Pivot work together?+
Power Pivot is used to create data models, and Power BI is used to build interactive dashboards and reports based on those models.
What is the prerequisite knowledge required for this course?+
Basic knowledge of Excel is recommended for our Power BI and Excel for data analysis training, but no prior experience with Power BI or Power Pivot is necessary.
How can this course benefit my career?+
Learning Power BI and Power Pivot can enhance your skills in data analysis and visualization, making you an attractive candidate in the job market.
Develop Data Analytic and Visualization Skills
Use Excel Power Pivot and Power BI integrations to analyze data and transform it into compelling visuals to tell a story.
- 1 año de acceso completo
- 21 LiveLab incluido
- Certificado de finalización
No se requiere tarjeta de crédito