Data visualization uses visual representations to show patterns and trends in data and provide readers with easy access to key insights. Data visualization tools offer an easy approach to observing and analyzing trends, outliers, and patterns in data by utilizing visual components like charts, graphs, and maps.
Data visualizing has gained immense popularity across the globe resulting in huge demand for certified professionals.
Why is Data Visualizing important?
Business users may utilize data visualization to understand their massive data sets. They gain by being able to spot fresh patterns and data mistakes. The users can focus on locations that show red flags or progress by making sense of these patterns. This procedure then propels the company forward.
Data visualizing certified professionals, executives and managers are in high demand in companies across the globe.
Who should take the Data Visualizing Exam?
Managers, senior executives, executives
Business Intelligence Professionals
ETL Developers
SQL Developers
Database Architects
Mainframe Professionals
Analytics and Testing Professionals
Knowledge and Skills required for the Data Visualizing
Critical thinking and communication skills helps candidate to gain quick success for career in data visualizing.
Skills Required
To succeed in the exam, you should have the following technical and analytical skills:
Data Literacy
Visualization Tools Proficiency
Design and Communication
Data Analysis
Business Acumen
Course Outline: Data Visualization Practice Exam
Module 1: Introduction to Data Visualization
What is data visualization?
Importance of visual data communication
Overview of common visualization tools
Module 2: Understanding Data Types and Structures
Categorical vs numerical data
Time series, hierarchical and geospatial data
Dimensions and measures in visualization tools
Module 3: Chart Types and Their Uses
Bar charts, pie charts, line graphs, scatter plots
Histograms, box plots, heat maps
Waterfall, bullet charts, treemaps, and Gantt charts
Dos and don’ts of chart selection
Module 4: Data Preparation and Cleaning
Handling missing data and duplicates
Data transformation and aggregation
Using calculated fields and conditional logic
Importing and combining multiple data sources
Module 5: Tools-Specific Training
Excel
Pivot tables and charts
Conditional formatting
Dashboards with slicers and linked visuals
Tableau
Dimensions vs measures
Filters, parameters, and calculated fields
Interactive dashboards and storyboards
Power BI
Data model and Power Query
DAX functions for custom metrics
Drill-throughs and bookmarks
Python (Optional Advanced)
Matplotlib and Seaborn basics
Creating custom plots with Plotly
Jupyter Notebook integration
Module 6: Dashboard Design Principles
Layout and user experience
Designing for storytelling vs exploration
Responsive and mobile-friendly dashboards
Real-world dashboard case studies (Sales, Marketing, HR)
Module 7: Applying Visual Analytics
Identifying patterns, trends, and correlations
Highlighting outliers and KPIs
Forecasting and predictive visualizations
Business case studies and mock projects
Module 8: Sharing & Publishing Insights
Exporting reports (PDF, PNG, CSV)
Embedding dashboards in web portals
Managing access and permissions (Power BI/Tableau Server)
Version control and report refresh schedules
Module 9: Practice Exams and Mock Tests
MCQs on chart selection, visualization best practices
Tool-based exercises (Excel, Tableau, Power BI)
Scenario-based problem solving
Timed full-length practice tests
Scorecards with analysis and improvement areas
Module 10: Final Capstone Project
Choose a dataset (sales, finance, or marketing)
Clean, analyze, and visualize insights
Build and present a complete dashboard
Peer and instructor review with feedback
Exam Format and Information
Certification name – Certificate in Data Visualizing
Exam duration – 60 minutes
Exam type - Multiple Choice Questions
Eligibility / pre-requisite - None
Exam language - English
Exam format - Online
Passing score - 25
Exam Fees - INR 1199
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