Introduction to SAS Visual Analytics: A Comprehensive Overview

Gyansetu Team Business/Data Analytics

SAS Visual Analytics is a tool that helps people explore data and find useful information. It works for all kinds of users, whether they are experts in data analysis or not. With it, you can check data to solve problems and see how different pieces of data are connected. You can also make and share reports with data. Let’s explore what a SAS tool is and how to use it!

What is the Statistical Analysis System (SAS)?

Statistical Analysis System (SAS) is an exceedingly powerful tool that helps in rendering a contemporary and integrated setting for administered discoveries as well as promotes exploration for users in skills like progressive analytical skills.
In simple words, it can be explained as a Business Intelligence tool used for the facilitation of data mining, predictive modeling, and reporting with the assistance of interactive dashboards and significant visualizations.

It makes it quite easy to create & share data reports for several dashboards capable of monitoring the business and user operation or performance quite easy. The data analysis as well as visualization can be shared with the group to get everyone’s insight and allows the transfer of data for solving complicated business problems with ease. It sets the skill level based on the user’s visualization performance and experience.

What are the Main Features of a Statistical Analysis System?

Here are some of the most beneficial features of SAS Visual Analytics.

  • Exploring Data with Visuals

SAS Visual Analytics goes beyond just analyzing data; it creates important charts and reports. This helps users understand complex data easily, find unusual patterns, and analyze trends more effectively. It also allows them to discover new possibilities within the data.

  • Insightful Analytics

This tool helps users identify connections between different pieces of data more accurately. It also helps them find outliers, make predictions about future trends, and visualize these trends in a simple and clear manner.

  • Mobile App for Easy Access

A SAS Visual Analytics mobile app is available for iOS and Android devices. This app has a user-friendly interface, making it easy for users to access their business data from anywhere at any time. It offers simple controls and allows creative interaction with reports, dashboards, and charts.

  • Interactive Dashboards

SAS Visual Analytics lets users build clear and precise reports. It also provides features like built-in data access, data filtering, and data transformation. This means users can access and manipulate data effortlessly within the tool.

  • Integration with Microsoft Office

Users can seamlessly integrate SAS BI and Analytics with Microsoft Office tools like Outlook and Excel. This integration allows them to access SAS tools directly from their Office applications. Users can also create reports using Office and distribute them through these tools. Additionally, they can create Storyboards to convey their data stories effectively.

How to use SAS visual analytics?

The analytical capacity is more customized and easy to use for quickly analyzing the probable outcomes for the estimation of unidentified parameters in support of adequate business analytics. The users get responses based on their needs after an in-depth data analysis is done. This facilitates business analysts in quickly accessing the feasible outcomes of the unidentified parameters. Here are some of the best ways of using SAS Visual Analytics.

  • Automated Forecasting

It’s the most relevant forecasting method in the favorable data despite the users being quite amateur regarding forecast reliability. Users can utilize the SAS visual data creators for organizing data, resulting in better exploration and easy data mining. They can be outlined to combine significant data with improved predictive strengths with the help of data builders.

  • Path Analysis

It pictures the relationship of data between the distinct sequence of data events along with path analysis and the display of the flow of data from one event to another as a sequence of paths.

  • Goal seeking

Determining the user goals for accomplishing the underlying aspects requires additional features and other skills that rely on the project requirements and execution team to attain the target forecast or predictions in the user dependencies. The SAS Visual Analytics also allows the users to add visualization cells, such as bars in charts, to accomplish user operations.

  • Scenario Analysis

This includes identifying the most crucial variables and primarily configuring how to accomplish the user changes after being influenced by the forecasts. It particularly conducted the automated calculations and drillable structures in a self-serviced way without requiring any pre-defined or user-defined paths.

  • Network diagrams

This shows complex data and how to interconnect the table cells with data for visualizing the bar charts. It uses as well as shares the modified data, which includes the network diagrams as well as correlation matrices on the line and pie charts. It also allows forecasting and combining the data with the donut charts, parallel plots, decision trees, etc.

  • Text Analysis

It applies the sentiment of data acquired after analyzing the social account with related data on sites such as YouTube, Facebook, and Twitter, as well as Google Analytics data on the customer remarks. It also procures the users fast insight into what topic is trending on social media, except for data.

SAS visual analytics procures displayed data with more simple words on the data subjects with categorization for text analysis. It also enables data compression for accessible data sources in various types of load available under the huge set of data memories functional in the business users. 

Benefits of the SAS Visual Analytics tool

  • Understand Your Data with Ease

SAS Visual Analytics uses smart technology like machine learning and natural language explanations. It does this to help you discover, visualize, and explain insights in a way that’s simple to grasp. This means you can figure out why things happened, explore different possibilities, and uncover hidden opportunities within your data.

  • User-Friendly

SAS Visual Analytics is designed to be user-friendly. Even if you’re not a data expert, you can use its predictive analytics features. This means that business analysts and non-technical users can assess potential outcomes. This helps your organization make informed, data-driven decisions without needing specialized skills.

  • Effortless Reporting

Creating reports and dashboards is a breeze with SAS Visual Analytics. You can make interactive reports that summarize important performance metrics swiftly. Additionally, you can easily share these reports over the web or on mobile devices. This ensures that critical information gets to the right people quickly.

  • Empower Users with Self-Service Data

One standout feature is self-service data preparation. It lets users bring in their own data, combine different tables, create new calculated columns, and apply data quality checks, among other things. This means that your team can access, combine, clean, and prepare data on their own quickly and flexibly. This not only speeds up the analytics process but also encourages more people in your organization to embrace data analysis.

SAS Visual Analytics Pricing 

The pricing of SAS is varied due to subscription costs and licenses and is administered to the user capacity, which comprises the hosting infrastructure price. The maintenance cost is precise with the on-premise price for both support and upfront that is paid for steady support and maintenance.

The cost of customization is a little due to additional functional prerequisites with configurable requirements, along with other dashboards with basic tracking. The pricing criterion and other minor commitments are necessary for the data purchases.

Conclusion 

SAS Visual Analytics provides users the ability to connect with third parties, as well as merge data from different systems. It also helps in analyzing the data structure and similar relevant information or input with even better and more precise ways for the powerful business intelligence system with extensive features.

Gyansetu Team

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