SPSS Statistics vs SAS Visual Analytics

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Our analysts compared SPSS Statistics vs SAS Visual Analytics based on data from our 400+ point analysis of Business Intelligence Tools, user reviews and our own crowdsourced data from our free software selection platform.

SPSS Statistics Software Tool

Product Basics

IBM SPSS, or Statistical Product and Service Solutions, is a data analysis platform that provides advanced statistical insights to propel business decision-making and research by crunching large datasets. With a user-friendly interface, it empowers everyone from basic users to experienced data scientists to perform statistical analysis. Scalable and agile, it is suitable for companies of all sizes.

Users can purchase it through an on-premises license or a subscription plan to a hybrid SaaS. Users who choose either monthly or annual subscription receive access to the base version and can choose which of three optional add-ons to include, if any, between Custom Tables and Advanced Statistics, Complex Sampling and Testing, and Forecasting and Decision Trees.

Perpetual and term licensees can choose between four editions that offer different levels of functionality: Base, standard, professional and premium. It was first launched as Statistical Package for the Social Sciences by three Stanford students in 1968 and later acquired by IBM in 2009.
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SAS Visual Analytics offers fast answers to complex questions drawn from datasets of all sizes. It provides guided exploration, interactive dashboards, smart visualizations and self-service analytics to users of all technical skill levels, promoting data literacy and visibility. Its versatile, scalable design helps users make better business decisions based on data transparency. Built on a cohesive in-memory architecture, it promotes intelligent action driven by insight.
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$99 Monthly
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Tailored to your specific needs
$8,000 Monthly
Get a free price quote
Tailored to your specific needs
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Product Assistance

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Knowledge Base
24/7 Live Support
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24/7 Live Support

Product Insights

  • Increase Reliability of Analysis: Data analysts and scientists can reach more dependable conclusions and ensure high accuracy, backed by numbers and models made from their data.
  • Assists in Decision Making: Organize and analyze data sets in order to draw conclusions, glean insights and make data-driven business decisions.
  • Statistics with Speed: Maximize productivity by quickly crunching data sets. Handle complicated tasks in a third of the time of many non-statistical programs.
  • Data Management: Remove manual work, as the system does all the legwork in preparing and organizing data sets for analysis. It estimates and uncovers missing values, improving the accuracy of reports.
  • Ease of Use: According to the IBM website, 81% of reviewers rank SPSS as easy to use. A point-and-click interface and natural language processing allow analytics capabilities to be accessed by those without coding skills or advanced statistics knowledge.
  • Scalability: Built to scale and work with large volumes of data, supporting anything from basic descriptive analytics to advanced statistics simulations. Purchase as many licenses as needed, ensuring cost-efficiency for small businesses as well as robustness for large scale enterprises.
  • Customized Predictive Analytics: Tailor predictive analytics to unique needs and perform ad hoc analysis to find the information needed, making better predictions over time.
  • Free Trial: Access all capabilities with a free 14-day trial period.
  • Academic Versions: An academic version is optimized for higher education and research. Program availability varies based on user roles, including students, teachers, researchers and campus-wide administrators.
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  • Easily Create Models and Explore Data: Build models that are stable, accurate and easy to create, based on proven techniques. Interact with and prepare data for self-service analysis or visualization. Unify diverse datasets and present in an easy-to-interpret format.
  • Discover Data Relationships and Patterns: Make data relationships easy to see and understand through machine learning that visualizes narratives from the data. Identify patterns in data through algorithms and pre-defined related measures.
  • Visualize Data in Intuitive Graphics: Discover and display trends in the form of intuitive graphics, reports and dashboards, including geographical data displayed on interactive maps, making them easier to explain, share and understand.
  • Glean Data-Based Insights: Gain insights and understand the business more thoroughly by identifying patterns, trends or important points in data. Improve transparency at every level — answer specific business questions, identify pain points in workflows, highlight areas for improvement and forecast future results much more accurately.
  • Perform Guided and Augmented Analysis: Leverage a variety of augmented or automated features that facilitate the data discovery and analysis processes. Get suggestions on the best-fit graphic for a given set of data via augmented analytics. Identify potentially related groups of data based on pre-set factors through automated explanation, uncovering insights potentially missed by the naked eye.
  • Make Better Business Decisions: Make data-driven business decisions based on historical information. Glean insights from data trends and patterns and apply them to forecasting, budgeting and other business planning.
  • Share and Collaborate: Collaborate on dashboards and share them easily with internal teams, clients, management and other key groups. Add comments to reports, create alerts for report objects to notify key members when a trigger factor is met, distribute PDF reports securely and restrict access to maintain the report’s integrity.
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  • Data Source Connectivity:  Enables reading and writing data from a wide spectrum of file formats and sources. These include ASCII text files, spreadsheets and databases like Microsoft Excel and Microsoft Access, as well as those from other statistics packages. 
  • Data Preparation: Streamlines the data preparation process. Identify invalid values, view patterns of missing data and automate data preparation to analyze and clean up large data sets in a single step. Validate the accuracy of analysis with a thorough, efficient data conditioning workflow. 
  • Point-and-Click Interface: Allows users without coding knowledge to leverage point-and-click data analysis with drop-down menus and drag-and-drop functionality. 
  • Automated Analytics: Automate common tasks with syntax and create customized data analyses that run using algorithms. 
  • Comprehensive Statistical Analysis: Perform many kinds of statistics tests, including but not limited to linear and non-linear models, simulation modeling, bayesian statistics, custom tables, complex sampling, advanced and descriptive statistics, and regression.
  • Ad Hoc Analysis: “Slice and dice” data by creating customized tables to dig deeper and improve understanding.
  • Predictive Analytics:
    •  Uncovers complex relationships between variables with functions like time series analysis, forecasting, neural networks and temporal causal modeling. 
    •  Simulates values and accounts for the uncertainty of the future using probability distributions. 
    •  Improves predictive models with multilayer perception and radial basis function. 
  • Geospatial Analysis: Explore the relationship between data points that can be tied to specific locations.
  • Direct Marketing: Improve campaigns and target key customers. Conduct advanced statistics analysis of customers or contacts with RFM (recency, frequency, monetary) analysis.
  • Open-Source Integration: Enhance syntax with programming languages R and Python through a library of more than 100 free extensions on the IBM Extension Hub, or opt to build programs.
  • Export with Ease: Export data to a proprietary file format. Can be exported to a variety of widely accessible formats such as text, Microsoft Word, PDF, Excel, HTML, XML, XLS and more. Export to a variety of graphic image formats.
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  • Ad Hoc Reporting and Analysis: Assemble reports from data creatively in real time as opposed to relying on a predesigned template. Run queries and perform analysis on data on demand without knowing code.
  • Predictive Analysis: Make predictions about future conditions based on historical data through data mining, machine learning and predictive modeling.
  • Mobile Apps: Leverage the power of native apps on iOS, Android and Microsoft devices, with an optimized mobile interface. Interact with visualizations on the go, view previous reports, leave comments, capture screenshots and set mobile notifications.
  • Interactive Discovery: Identify outliers, clusters, relationships, trends, etc. by exploring data in a natural query-based way rather than through coding.
  • Location Analytics: Lasso data points on a map through OpenStreetmap or Esri ArcGIS to select them for analysis and then enrich demographic data through point clustering, map pins, custom polygons and more.
  • Trend Indicators: Identify which types of data to observe through built-in trend indicators that attempt to predict future movement of data points based on historical trends.
  • Visualizations: Get desired insights from data and easily discover patterns through a range of visualization options, such as bar graphs, pie charts, donut graphics, line graphs, scattergrams, heat maps, bubble maps, dot maps, needle graphics, numeric series, schedule charts, vectors, key value infographics and more.
  • Scheduled Reporting: Programmable to send reports at scheduled intervals or based on triggered events to ensure they are delivered regularly.
  • Customizable Dashboard: Access only relevant tools, visualizations and data through the customizable dashboard interface. Engage with data as well as collaborate with others on data visualizations, irrespective of technical skill levels.
  • Embedded BI: Embed the system into web applications or other software solutions for a seamless interface and direct data draw. Also, embed individual reports and dashboards using SAS SDK.
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Product Ranking

#86

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#28

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Analyst Rating Summary

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Analyst Ratings for Functional Requirements Customize This Data Customize This Data

SPSS Statistics
SAS Visual Analytics
+ Add Product + Add Product
Advanced Analytics Augmented Analytics Data Management Data Pre-processing Data Transformation Data Visualization Embedded Analytics Capabilities Geospatial Visualizations And Analysis Mobile Capabilities Platform Capabilities Reporting 79 64 80 100 100 92 86 88 79 83 100 0 25 50 75 100
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Analyst Ratings for Technical Requirements Customize This Data Customize This Data

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User Sentiment Summary

Great User Sentiment 1881 reviews
Great User Sentiment 137 reviews
87%
of users recommend this product

SPSS Statistics has a 'great' User Satisfaction Rating of 87% when considering 1881 user reviews from 6 recognized software review sites.

83%
of users recommend this product

SAS Visual Analytics has a 'great' User Satisfaction Rating of 83% when considering 137 user reviews from 5 recognized software review sites.

4.3 (18)
n/a
4.2 (712)
3.8 (11)
4.51 (528)
4.3 (33)
4.5 (425)
4.3 (38)
4.6 (40)
4.3 (10)
4.2 (158)
3.9 (45)

Awards

we're gathering data

SelectHub research analysts have evaluated SAS Visual Analytics and concluded it earns best-in-class honors for Data Pre-processing.

Data Pre-processing Award

Synopsis of User Ratings and Reviews

Research Analysis: It’s easy to analyze and interpret large and complex datasets to generate insights, according to 96% of reviewers who mention this feature.
Ease of Use: The platform is user-friendly and easy to navigate as observed by almost 95% of reviewers mentioning ease of use.
Interface: The interface has a clean layout and visually appealing design according to 75% of users referencing it.
Syntax: It’s easy to use (copy and paste) and proof syntax, and save for later, as noted by 95% of reviewers who talk about this feature.
Resources: Of users mentioning support, 93% agreed that access to various support manuals and courses, as well as an extensive user community, was helpful.
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Data Analysis: Around 81% of users who reviewed its data analysis capabilities said that the tool offers out-of-the-box advanced analytics to identify patterns and relationships in business data.
Functionality: Citing its powerful in-memory technology, approximately 62% of users who reviewed functionality said that the solution provides a single, compact interface for data exploration and modeling for faster analytic computations.
Data Visualization: Around 60% of users who reviewed data visualization said that they can perform exploratory data analysis with a multitude of graphics options, such as bubble charts, line charts, dual axis charts.
Ease of Use: Approximately 54% of users who mentioned ease of using the software said that it is easy to generate reports with some basic SQL knowledge.
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Learning Curve: It needs extensive learning to understand advanced tools and different aspects, as observed by almost 75% of reviewers mentioning training.
Cost: More than 90% of users referencing the price remarked that the product is a bit expensive.
Slow Operation: The system runs slow at times while using huge or complex data sets, and needs to restart, as observed by 92% of reviews on this topic.
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Cost: Around 80% of users who discussed the platform’s cost said that they find the pricing to be cost-prohibitive.
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SPSS Statistics is a point-and-click data analysis software that allows non-technical users to leverage advanced statistical analysis. Users praised its user-friendly, visually appealing interface. Many reviews also appreciated how easy it is to use and proof syntax, along with the extensive help documentation available for better understanding. Despite its ease of use, a majority found that using advanced tools involved a steep learning curve. Additionally, its cost runs on the high side and processing large amounts of information slows down its performance, as observed by most reviewers. It’s a good fit for students, data scientists and companies that want to analyze data sets but don’t have the technical resources and expertise to use a more advanced tool.

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SAS Analytics is a versatile business intelligence and analytics tool that empowers users to explore and understand data through interactive data visualizations. Many users who reviewed data analysis said that, coupled with the power of predictive analytics, the platform offers a plethora of graphics options — charts, graphs and dashboards — with deep-dive capabilities, such as filtering, to zero in on pertinent business data. Many users who reviewed functionality and data preparation said that, possibly because of its capable ETL engine and in-memory architecture, data processing speed is very high and reports load faster. A majority of users who reviewed data connectivity said that the tool is efficient in pulling data from multiple sources for data modeling and analysis. On the flip side, quite a few users who reviewed functionality said that the platform’s integration with Python and R is still in the development stage and this limits its functional scope. Some users who discussed user-friendliness said that the processes are not the most intuitive — errors and warnings in logs are misleading, and new users may find adoption difficult. Though the industry scope of user tutorials is limited, a majority of users said that the steep learning curve of the platform is sufficiently addressed by training. For many users, its cost-prohibitive licensing plans caused them to not consider it their first choice when it came to purchasing a BI solution. Overall, SAS Visual Analytics is a versatile tool with fast data processing capabilities and strong visualizations to generate reports for insightful data analysis.

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