Intro to Power BI

Welcome to Power BI

Intro to data analysis

Data science, big data and data analysis 2.0

What is data analysis? 2.0

Data analysis: Info and Knowledge 2.0

QUIZ: Data pyramid 2.0

Data analysis: good vs bad data 2.0

Stages of Data Analysis: 1

Stages 2-3: data analysis

Stage 4: data analysis

Data analysis recap 2.0

Introduction to Data Analysis 2.0

Introduction to Power BI 2.0

What is Power BI 2.0

Brief overview of Power BI 2.0

Preparing your working folder 2.0

Part 1 Demo Tour: Power BI

Quick tour of PowerBI 2.0

Loading Data To Power BI 2.0

Transforming Data 2.0

Profiling Data >> View tab 2.0

Transforming Tables >> View tab 2.0

Transforming Tables >> Changing & merging columns

Transforming Tables >> Deleting, sorting, grouping

TASK: Transforming Tables

Part 2 Demo Tour: Power BI

Power BI Reports overview 2.0

TASK: Power BI reports

Visual Interactions 2.0

Visualisation: Slicer

Decorating a report 2.0

Saving a Report 2.0

Final task & recap

TASK: final report

Next course: Part 2

Extract, Transform and Loading Data 2.0

Stage 2: Data Modeling 2.0

Stage 3: Data Visualisation 2.0

Stage 4: Data Analysis 2.0

QUIZ: Shaping Data 2.0

QUIZ: Understanding Objectives 2.0

QUIZ: DAX and Model 2.0

QUIZ: Power BI Visuals 2.0

Introduction to Data Analysis 2.0

Intro to Power BI Intro to data analysis Introduction to Data Analysis 2.0

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Question 1 of 10

1. Question

Why is data analysis important?

Data analysis is important for visualising the data.

Data analysis is useful for obtaining insights that can help make better informed decisions.

Data analysis is important for modeling data

Data analysis is important for knowing what your data represents

Data analysis is important for finding meaning in your data

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Question 2 of 10

2. Question

Which of these are not stages of data analysis?

Data Processing

Data Preparation

Data Visualisation

Data Modeling

All of the above

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Question 3 of 10

3. Question

Which statement is correct about information?

Information is data

Information needs to be prepared for analysis

Information is data that has been processed to be meaningful

Information is just raw facts

None of the above

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Question 4 of 10

4. Question

Which statement is correct about data?

Raw data is meaningful and gives lots of insight

Data should not be processed before it is analysed

You can use any random data to find useful information

Data needs to be clean, relevant and consistent

Data needs to be accurate, relevant and consistent

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Question 5 of 10

5. Question

What happens during the data modeling stage of analysis?

Data is prepared for analysis

Data is re-organised in accordance to the obtained requirements to ensure that its optimised to answer provide answers to the problem questions

Data is visually represented to gain understanding or communicate the data to others

Data is extracted, transformed and loaded

Data is removed from the store

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Question 6 of 10

6. Question

What is data visualization?

Data visualisation is the process of visually representing data in a meaningful way to make it easier to understand and communicate the data

Data visualisation is preparing the data for analysis

Data visualisation is the process of modeling data for analysis

Data visualisation is the process of seeing the data as a picture

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Question 7 of 10

7. Question

What happens during the analysis stage of analysis?

Data is cleaned and transformed into a format that is useful for analysis

Data is used to create visualisations that best describe the data

Data is prepared into the format that is required

The data that has been collected, modeled and visualised is used to find answers or insight to the provided requirements

Data is modeled for analysis

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Question 8 of 10

8. Question

How is data prepared?

Once the data has been collected, it is transformed (from many data sources) into a format that can be easily and correctly analysed

The data is modeled for analysis

Data is extracted from the visualisations to get the raw data.

After analysing the data, it is prepared for presentation.

I don’t know.

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Question 9 of 10

9. Question

What are the stages of data analysis in order?

data preparation, data analysis, data visualisation, data modeling.

data analysis, data modeling, data visualisation, data preparation.

data cleaning, data collection, data management, data visualisation.

data preparation, data modeling, data visualisation, data analysis

data collection, data cleaning, data management, data visualisation

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Question 10 of 10

10. Question

What are the 4 types of analysis?

data analysis, information analysis, knowledge analysis, insight analysis.

descriptive analysis, informative analysis, preparation analysis, prescriptive analysis.

prescriptive analysis, diagnostic analysis, exploration analysis, preparation analysis.

data analysis, information analysis, prescriptive analysis, insight analysis

descriptive analysis, diagnostic analysis, predictive analysis, prescriptive analysis

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