Aspire Journeys

Data Visualization Mastery

  • 24 Courses | 29h 36m 46s
  • 2 Labs | 16h
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Data Visualizations play a key role in helping companies make data driven decisions. This Skillsoft Aspire journey will help you understand the significance of creating user-centered visuals, best practices to follow along with various types of charts, plots, graphs and diagrams to represent data visually. Along with eye catching visualizations using Excel from various imported data formats, you will also learn to create various types of visualizations using BI tools like QlikView. You will then explore creating interactive dashboards and infographics for your visualization projects. You will also explore various techniques for creating visualizations using various Python libraries like Matplotlib, Plotly, and Bokeh before modeling the data.

Track 1: Data Visualization with Excel

In this track of the Data Visualization Skillsoft Aspire journey, the focus will be on data visualization best practices and data visualization using Microsoft Excel.

  • 7 Courses | 8h 34m 56s

Track 2: Data Visualization with BI Tools

In this track of the Data Visualization Skillsoft Aspire journey, the focus will be on data visualization using QlikView.

  • 4 Courses | 5h 34m 28s
  • 1 Lab | 8h

Track 3: Creating Infographics for Data Visualizations

In this track of the Data Visualization Skillsoft Aspire journey, the focus will be on creating infographics with Infogram and Visme.

  • 6 Courses | 7h 9m

Track 4: Data Visualization with Python

In this track of the Data Visualization Skillsoft Aspire journey, the focus will be on data visualization with Python using Matplotlib, Bokeh, and Plotly.

  • 7 Courses | 8h 18m 22s
  • 1 Lab | 8h


Data Visualization: Best Practices for Creating Visuals
Most organizations depend on data visualization to help drive business decisions. Using the correct charts and graphs helps communicate the right information and identify patterns and trends within your data. You'll begin this course by identifying the importance of data visualization and its application in curating data that is easy to digest, understand, and interpret. Next, you'll discover best practices for visualizing data and the significance of creating user-centered visuals. You'll then explore different presentation types such as comparison, composition, distribution, trends, and relationship, and learn how to map your charts to these categories. Finally, you'll investigate the use cases for popular charts such as line charts, pie charts, histograms, scatter plots, and others. You'll also recognize when to use specialized charts such as Gantt charts, sunburst charts, and Sankey diagrams.
11 videos | 1h
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Excel Visualization: Getting Started with Excel for Data Visualization
Excel charts can be used for a myriad of data visualizations, including categorical data and continuous data, like time-series data. In this course, you'll learn how to bring data into Excel and build and customize various charts. You'll start by importing data from an existing workbook into a new spreadsheet. You'll then import data from CSV and JSON file formats and Microsoft Access database files. Next, you'll use the Power Query editor to perform various operations. Moving on, you'll create column and clustered column charts and perform various formatting operations on the clustered column chart, such as adding data labels, error bars, axis titles, and trendlines. Lastly, you'll create a simple line chart, formatting various aspects, such as the line, background, title, legend, axes, and position of charts relative to each other.
9 videos | 1h
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Excel Visualization: Building Column Charts, Bar Charts, & Histograms
Data visualizations in Excel reveal the insights uncovered by your data in easy-to-consume representations. You can identify categorical values, recognize how parts sum up to a whole, see percentages rather than absolute values, discretize continuous variables, and approximate the probability density function of variables. In this course, you'll build charts to uncover all of this information. You'll start by working with column and bar charts. You'll then create and differentiate between clustered and stacked column charts. You'll move on to formatting and customizing bar and column charts before working with 2D and 3D chart types and customizing them in various ways. Lastly, you'll work with histograms, examining how they work, what they're used for, and how to customize them to your needs.
10 videos | 1h
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Excel Visualization: Visualizing Data Using Line Charts & Area Charts
Line charts are possibly the most common type of visualization for time-series data, enabling you to see time trends at a glance. These can be augmented with trendlines, used to visualize time trends in data. Stacked area charts are a powerful type of visualization, combining information about trends over time with information about composition and parts of a whole. In this course, you'll learn how to create and customize all of the visualization types above. You'll begin by exploring the purpose of line charts before moving on to formatting and customizing them. You'll then practice using trendlines to evaluate different regression models on data in a line chart. You'll also customize and format these trendlines. Following this, you'll work with area charts and stacked area charts, examining, in detail, the several types of stacked area charts in Excel and customizing their appearance.
13 videos | 1h
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Excel Visualization: Plotting Stock Charts, Radar Charts, Treemaps, & Donuts
Data visualization options in Excel are vast. You should choose your visualization type based on the data and what you want to show from it. For example, using High-Low-Close and Open-High-Low-Close charts (also called candlestick charts), you can summarize several stock performance aspects. Excel also lets you build radar charts - great for visualizing multivariate ordinal data, such as ratings or scores, to spot strengths or spikes. In this course, you'll not only learn how to build and customize the charts mentioned, but you'll also create treemaps to visualize hierarchical data and pie charts to display parts of a whole. You'll then generate pie-of-pie and bar-of-pie charts, both of which use a secondary visualization to complement a pie chart. Finally, you'll create donut charts to visualize composition using multiple concentric donut rings to represent points in time.
10 videos | 1h
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Excel Visualization: Building Box Plots, Sunburst Plots, Gantt Charts, & More
Once you grasp how to work with the scope of standard Excel chart types, you can expand into more complex visualizations. For example, you can use box-and-whisker plots to convey a wealth of information about the statistical distribution of a variable and identify outliers in a data series. You can use sunburst charts to visualize hierarchical data with differing levels of detail, waterfall charts to show the cumulative effect of positive and negative values, and Gantt charts to illustrate progress toward a goal involving multiple parallel tasks. Additionally, you can avail of band charts to quickly eyeball the trend in a line chart, scatter plots to uncover the relationship between two variables, and waffle charts to visualize progress towards KPIs. In this course, you'll create all of these charts either via Excel's built-in tools or by building them manually using nifty workarounds.
11 videos | 1h
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Final Exam: Data Visualization with Excel
Final Exam: Data Visualization with Excel will test your knowledge and application of the topics presented throughout the Data Visualization with Excel track of the Skillsoft Aspire Data Visualization Journey.
1 video | 35s
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QlikView: Getting Started with QlikView for Data Visualization
QlikView, a guided data analytics solution from Qlik, allows you to develop and deliver interactive guided analytics applications and dashboards rapidly. In this course, you'll set up QlikView Personal on your Microsoft Windows machine and build some standard visualizations. You'll first demonstrate and explore in detail the associative data model in QlikView, which allows you to probe and highlight all associations in your data. You'll then import custom data using Excel and CSV files into QlikView before visualizing and exploring your data using bar charts, pie charts, and grid charts. Furthermore, you'll also use special sheet objects, such as the table box, which, when every row's content is logically connected, displays several fields in your data simultaneously. Moreover, you'll use the multi box to represent values from multiple fields as drop-down values.
14 videos | 1h
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QlikView: Creating Line Charts, Combo Charts, Pivot Tables, & Block Charts
At QlikView’s core is a patented associative engine allowing for an associate experience across data types regardless of where they’re stored. In this course, you’ll explore how to use your time-series data to build line charts. You’ll then customize these charts in various ways, such as using smoothing techniques to represent approximations or multiple lines to demonstrate values in more than one variable. Next, you’ll configure stacked area charts to visualize the composition of variables over time before using combo charts to visualize multiple chart types on the same axes. Finally, you’ll examine how you can explore hierarchical data using pivot tables and block charts. You’ll identify the differences between pivot tables and straight tables and distinguish how each of these represents underlying data.  
12 videos | 1h
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