NVivo vs SAS Visual Analytics

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Our analysts compared NVivo 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.

NVivo Software Tool

Product Basics

NVivo is a qualitative data analysis solution for academic and industrial research. It lets users code and visualize their findings from interviews, surveys, text documents and demographic information. It’s helpful in social sciences, education and healthcare.

It has a friendly interface, powerful searches and advanced graphics. Once set up, the system can perform automatic sentiment analysis. Users can record the coding schemes and use them across the data. Documenting the steps enables future researchers to validate the research.

The vendor offers exclusive modules for collaboration and transcription. Its Collaboration Cloud lets many people work on the same project.

Pros
  • Powerful data management
  • Rich coding and query tools
  • Visualizations and data exploration
  • Team collaboration features
  • Support for various data formats
Cons
  • Steep learning curve
  • Can be expensive for individuals
  • Limited free trial/demo
  • Not ideal for simple projects
  • Occasional bugs and glitches
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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/User, 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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Videos
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Knowledge Base
24/7 Live Support
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24/7 Live Support

Product Insights

  • Boost ROI: Tap into buyer sentiment by noting their needs and preferences and applying them to product development. Push sales by fine-tuning marketing campaigns.
  • Innovate: Launch new products and improve existing offerings. Go beyond numbers and discover what customers think and feel with thematic and sentiment analysis.
  • Act: Save time while searching for information. Organize data from various sources, such as interviews, surveys and social media, in one system.
  • Improve Services: Build stronger customer associations by serving them better. Identify their pain points and improvement areas by analyzing feedback.
  • Save Money: Free resources for more strategic work by automating tasks like transcription — auto-code interviews with NVivo 14.
  • Test Drive: Try it for 14 days free, including the Collaboration Cloud.
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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 Import: Pull data from mobile apps like Evernote and organize it using folders, sets or file classifications. It supports transcripts, articles, audio/video recordings and social media content.
  • Qualitative Analysis: Uncover hidden insights using powerful search tools. It turns interviews, surveys and documents into charts, word clouds and maps.
  • Thematic Analysis: Understand findings after digging deep into gathered data and spot emerging themes.
  • Integrations: Combine research materials in one place. Allows direct imports from Microsoft Office. Plus, it can use data from SurveyMonkey and social media platforms.
  • Sharing and Publishing: Export results, models and charts to various formats, including Excel, Word, text, rich-text and PDF files. Use the system clipboard to copy and paste graphics into reports and presentations.
  • Transcription: Review and edit transcripts, tag speakers, and add notes, then import transcripts directly into NVivo for analysis. NVivo Transcription auto-transcribes uploaded audio files, with support for 28 languages.
  • Multilingual Options: Analyze data in Chinese, Japanese, English, French, German and Portuguese, among other languages.
  • Collaboration Cloud: Work together to co-author research projects. A user uploads a master project to a secure cloud workspace, enabling others to download and work on it offline and then seamlessly merge their edits back into the main project.
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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

#42

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Business Intelligence Tools

#28

among all
Business Intelligence Tools

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Analyst Rating Summary

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Analyst Ratings for Functional Requirements Customize This Data Customize This Data

NVivo
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 179 reviews
Great User Sentiment 137 reviews
82%
of users recommend this product

NVivo has a 'great' User Satisfaction Rating of 82% when considering 179 user reviews from 2 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.

4.1 (133)
3.8 (11)
n/a
4.3 (33)
4.1 (46)
4.3 (38)
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4.3 (10)
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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

Data Management: Organize and store various data types (text, audio, video, images) in one secure location.
Flexible Coding: Employ diverse coding approaches (tree, auto and query) to categorize and analyze data based on research questions.
Relationship Exploration: Uncover connections and hierarchies between codes using visual network maps and relationship coding.
Advanced Querying: Search coded data for specific terms, patterns or code combinations to identify key themes and trends.
Visualizations: Generate various visualizations (word clouds and concept maps) to present complex data findings clearly.
Collaboration: Share and collaborate on projects with other researchers using cloud-based options or file exports (depending on the version).
Support & Resources: Benefit from extensive online resources, tutorials, and user communities for troubleshooting and learning best practices.
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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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Steep Learning Curve: New users often report difficulty in mastering NVivo's features quickly, which impacts their productivity and project timelines.
High Cost: Some users find NVivo's pricing to be prohibitive, particularly those from smaller institutions or independent researchers with limited budgets.
Limited Cross-Platform Support: NVivo's limited compatibility with non-Windows operating systems can be a barrier for Mac or Linux users, who may have to seek alternatives or use virtual machines.
Resource Intensiveness: NVivo can be demanding on computer resources, leading to performance issues on less powerful machines, which can frustrate users when handling large data sets.
Occasional Software Bugs: Users occasionally encounter bugs that can disrupt workflow and require waiting for patches or updates, affecting the software’s dependability.
Rigid Licensing Policy: NVivo's licenses can be inflexible, and transferring a license to another computer can be problematic, causing inconvenience to users who need mobility.
Complex Data Importation: Some users find importing data from various sources into NVivo cumbersome, which could lead to a time-consuming setup process.
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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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NVivo is qualitative data analysis software that received positive reviews from users. They appreciate its user-friendly interface, powerful features and ability to handle large datasets.However, some users complained about lax customer support and the occasional bug.NVivo is popular but not as robust as some of the other options. It’s also expensive. However, many users believe that the extra cost is worth it for the additional features and functionality. It has robust coding features to analyze large amounts of data quickly.Overall, NVivo is a user-friendly qualitative data analysis software that can be expensive and complex for individual users but is a handy assistant for teams.

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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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