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Here's What You Should Know About Visual Analytics

This describe about visual analytics in details, talk about it's benefits, and describe about the difference between Data Visualization and Data Analytics.

Let’s discover the unexpected from data. It’s all about the journey. If you’re a beginner or student aspiring for a career in Visual Analytics, then this article is for you. Visual analytics helps you navigate a world drowning in data. It is a type of reasoning that uses interactive visual representations of data and analytical processes. It facilitates high-level, complex activities such as improved data-driven decision-making. It is a part of business intelligence and business analytics that refers to visualization of data analysis. Visual analytics answers the “what” questions - like “what are the challenges” or “what are the emerging trends.” However, when searching for data insights, you need to be able to ask why. This is where the power of visual analytics enables you to dig deeper into the data.

This article will help list the benefits of visual analytics, the difference between Data Visualization and Data Analytics.

So, let’s get started,
Visual analytics is an integrated approach that combines visualization, human factors, and data analysis. It helps gain insights from data. Visuals make research much easier and faster for users to interpret. The complex issues are much easier to understand for even non-technical users with visual analytics. Both data scientists and business owners can leverage it. The interactive and visual elements are often beneficial for communicating what one sees in the data to others and making better-informed business decisions.

Benefits of Visual Analytics

Businesses are increasingly implementing data analytics and visualization tools to enhance their business performance. It also helps improve business decisions. Let's have a look at critical benefits visualization in data analytics:
Help interpret data easily that makes analytics more user-friendly to non-experts.

  • Minimizes overall cost
  • Improved data analysis and data exploration capabilities
  • Faster and better understanding of data for smarter decisions
  • Consumes large volumes of data in less time, which improves operational efficiency
  • Real-time updates and instant feedback keep data current and accurate


Difference Between Data Visualization and Data Analytics

They are often used interchangeably but possess different capabilities and are used for various applications. Both give you a specific set of data to answer particular questions. They provide visual ways to represent data, making it easier to communicate findings and telling stories with your data. Both give you data points, highlight problems and critical indicators. Following is a comparison table Data Analytics and between Data Visualization:

Parameters

Data Analytics

Data Visualization

Definition

Process of examining data sets to decide the information increasingly with specialized software and system. Helps answer the “why” questions in your data.

Graphical representation of information and data in a visual or graphic format. It helps you answer the “what” in your data

Application

Data analytics helps you make more informed business decisions by analyzing the data.

The main objective of data visualization is to communicate information clearly and efficiently to users by presenting them visually.

Relation

Data visualization and analytics together conclude the datasets. In few instances, it might act as a source for visualization.

Provides better perception

Target Industries

Commercial, Finance, Healthcare, Crime detection, Travel agencies, and more

Finance, Banking, Healthcare, Retail, and more

Tools

Trifecta, Excel, Hive/Spreadsheet, Hive, Polybase, Presto, Trifecta, Excel /Spreadsheet, Clear Analytics, SAP Business Intelligence, etc.

Plotly, DataHero, Tableau, Dygraphs, QlikView, ZingCHhart etc.

 

 

Technique

Prescriptive and Predictive analytics

static or interactive.

Responsible

Data Analysts

Data Engineers

If you have made up your mind about pursuing a data analysis career, enroll in an on-job Data Analytics Course to develop work-ready skills. This is a great way to dip your toe in the water.

Source: Free Articles from ArticlesFactory.com

ABOUT THE AUTHOR


I am anannya Agrawal. I have 3.5 years of experience in the field of application development. I am a professional trainer for mobile and web application development.



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