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course | Data Visualization

Join our Data Visualization course in GCC. Gain practical data visualization skills with expert guidance, real cases, and a certificate.

DIGTR-910 | Data Visualization

Course Sector : Digital Transformation and Innovation

Duration
Date from
Date to Course Venue Course fees Book a course
5 Days19/10/202623/10/2026Online$2,150 Book now
5 Days15/03/202719/03/2027Los Angeles$5,950 Book now
5 Days24/05/202728/05/2027Abu Dhabi$4,250 Book now
5 Days15/08/202719/08/2027Jeddah$4,250 Book now

Course Introduction

Nearly every organisation bases its key decisions on sound data. This data may have been generated from past reports or may comprise future projections. The data initially collected is just a bunch of numbers and statistics. It bears no meaning to managers until it is converted into suitable information. Data visualization allows the conversion of this information into a pictorial representation, which is much easier to understand and read. These visual representations might be in the form of graphs, charts, maps, videos, dashboards, or any type of visual format. This enables the rapid identification of trends and patterns present in the data that would otherwise have been difficult to recognize and understand.
 

Why is data visualization important?
 

The human brain can comprehend a visual data set much more easily than rows and rows on a spreadsheet. Since data has become such an integral part of strategic decision-making for any organisation, data visualization has spread to every sphere where data is utilized.
 

How can Data Visualization be made good?

How to position the data, use the color scheme, and other techniques to enhance the readability of the data? How to achieve data cleansing for better data visualization? What are the different tools available for data visualization? Which tool will be suitable for which data set? Data visualization is not merely the plotting of charts and tables but requires acute preparation beforehand in the form of these questions. Data visualization is a subtle science and art. It requires comprehension of raw data and apt application of visual tools meticulously enough to draw valuable insights from the dataset.
 

Training has brought a sought-after Data Visualization course that elaborates on both the science and art part of data visualization. Numerous available tools have been discussed in detail along with their application, pros, and cons. Professionals from all fields experience the vital need to present their data in a convenient form to prolifically state their points and derive enhanced understanding from it. This course is mindful of this requirement and therefore discusses important features, techniques, and concepts related to data visualization in the most beneficial manner.


Course objective

  • Enable the development of visual mediums that will help data analysts to interpret the key points promptly
  • Encourage faster decision-making through a better understanding of visuals
  • The large dataset may contain valuable information that often goes ignored; however, hidden insight is discovered when the data is visualized
  • Observing data correlation through visual representation between different variables enables the entity to explore opportunities
  • Allow easy recognition of trends and patterns of a large dataset that can prove to be a tedious task
  • Allow faster identification of errors and mistakes

Course audience

  • Data Analysts
  • Data managers
  • Strategic managers
  • general managers
  • departmental managers
  • Business Analysts
  • Database Administrators
  • Startup founders
  • Entrepreneurs

Course Outline | 01 DAY ONE

Module 1: Why data visualization?
 

  • Introduction to data visualization and its importance
  • Benefits of data visualization
  • Users of data visualization
  • Briefs of data visualization techniques: infographics, graphs, charts, etc.
     

Module 2: Data Visualization  Process
 

  • Developing a research question
  • Gathering and cleaning data
  • Data mining
  • Selecting visual tools, criteria for selection
  • Making data interactive

Course Outline | 02 DAY TWO

Module 3: Use of Mapping
 

  • Map types: heatmaps, statistical map, point map, line map, interactive map
  • The increasing role of an interactive map
  • Suitable for what kind of data
     

Module 4: Use of Bar Graphs
 

  • Functions: drawing comparisons and identifying patterns
  • Creating bar charts
  • Data suitable for bar graphs
  • Types of bar graphs: horizontal, vertical, stacked, and clustered


Module 5: Use of Pie Charts
 

  • Functions: Cross-sectional visualization, showing the proportion
  • Constructing a pie chart
  • Data suitable for Pie-charts

Course Outline | 03 DAY THREE

Module 6: Use of Histograms
 

  • Functions: identify the range, patterns, comparison, etc
  • Constructing a histogram: parts, dos and don’ts
  • Distributions: normal, bimodal, skewed
  • Data suitable for a histogram
     

Module 7: Use of Line Graphs
 

  • Functions
  • Data suitable for Line Graphs
  • Constructing a Line Graph: quantitative, independent, and dependent variables

Course Outline | 04 DAY FOUR

Module 8: Use of Scatter Plots
 

  • Functions: relationships
  • Identifying types of correlation
  • Constructing a scatter plot
  • Line of best fit/ trend line
     

Module 9: Challenges in Data Visualization
 

  • Cognitive disadvantages- ambiguity, change blindness
  • Emotional disadvantages- disturbing, visual stress
  • Social disadvantages- cultural differences, framing effects, etc.

Course Outline | 05 DAY FIVE

Module 10: Current Trends
 

  • Geo-spatial visualization
  • Using Chart junk
  • Real-time visualization
  • Video visualization
  • Data stories
     

Module 11: Excel Activity
 

  • Creating charts and graphs in Excel
  • Styling the tool in Excel
  • Exporting from Excel
  • Excel exercise- creating charts and graphs
Course Certificates
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BOOST’s Professional Attendance Certificate “BPAC”

BPAC is always given to the delegates after completing the training course,and depends on their attendance of the program at a rate of no less than 80%,besides their active participation and engagement during the program sessions.

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Data visualization is the process of presenting data in graphical formats—such as charts, graphs, maps, and dashboards—to make information easier to understand, identify patterns, and support data-driven decision-making.
A commonly used framework for effective data visualization includes:Clear – Present information in a simple and easy-to-understand way.Concise – Eliminate unnecessary details and clutter.Consistent – Use consistent colors, labels, scales, and formatting.Compelling – Highlight the most important insights and tell a meaningful story.Correct – Ensure the data is accurate and represented without distortion.
No. SQL (Structured Query Language) is a database query language used to retrieve, manipulate, and manage data. It is commonly used before visualization to prepare data, but it does not create charts or dashboards by itself
Four of the most widely used data visualization tools are:Microsoft Power BI – Interactive business intelligence dashboards.Tableau – Advanced visual analytics and reporting.Microsoft Excel – Charts, pivot tables, and basic dashboards.Looker Studio (formerly Google Data Studio) – Cloud-based dashboards and reporting integrated with Google services
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