SAS Visual Analytics vs Infor Birst

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Our analysts compared SAS Visual Analytics vs Infor Birst 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.

Infor Birst Software Tool

Product Basics

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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Infor Birst is a cloud-based analytics software tool that aims to help users discover insights without the need for analyst input. It unifies IT-managed enterprise data with user-owned data, supporting the blending of both in a top-down and bottom-up manner. It uses consistent business metrics to structure raw data into organized sets and visualizations. It helps users identify patterns and better understand their organization’s KPIs.

It offers a seamless, integrated UI that allows users to perform every step of the data analysis process in a single interface, enabling a smooth experience. It can be deployed either from the cloud or self-hosted on-premise.

Users can purchase it in three available formats: per-user fee, by department or business unit or by end-customer in embedded scenarios.

To explore other popular solutions that Infor offers, visit our Infor company page.
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$8,000 Monthly
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$2,500 Monthly, Quote-based
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Product Insights

  • 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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  • Scalability on Demand: Prevents data bottlenecks caused by data loads that exceed capacity as business grows by scaling as needed through a multi-tenant architecture across a multi-node environment.
  • Faster Results: Delivers faster analytics across the entire organization by utilizing automated data analysis technology, cloud architecture and reusable metadata.
  • Data Clarity: Promote data clarity and reduce ambiguity by offering unique views into data to help everyone, regardless of technical expertise. Better understand the meaning of individual KPIs via the semantic layer, a set of shared business definitions.
  • Self-Service: Gives employees at all levels of technical skill self-service tools, such as drag-and-drop, to explore, analyze and visualize data through the user-oriented UX.
  • Informed Decisions: Make more data-driven business decisions by better understanding operations. Identify trends in business data by collecting, organizing, exploring and visualizing data.
  • Predict Future Outcomes: Generate actionable insights by leveraging AI to analyze historical data and improve business moving forward.
  • Intuitive Visualizations: Easily interpret trends by cleaning data and building understandable visualizations through machine learning.
  • Networked BI: Builds collective intelligence. Combines IT-managed enterprise data with user-generated data and eliminates data silos, unifying data from every part of an organization.
  • Certified Security: Secures data at every degree of detail, down to the row and column level. Employs strict data security protocols and procedures to protect data in  processes and data centers, which are certified for ISO27001 and SOC II, TYPE II standards and compliant with EU Safe Harbor laws.
  • Free Trial: Try it hands-on via a free trial.
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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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  • Automated Data Refinement: Automatically merge data from different sources into one user-ready data storage and optimize it for analysis. 
  • Semantic Layer: Boosts trustworthiness of data and reduces data anarchy by adding an agile semantic layer between the user and data. Work with data privately while staying connected to the network via a virtual tenant space.">
  • Real-time Access: Directly query on-premise data sources in real-time, eliminating the need to first extract and then upload data to the cloud.
  • Adaptive UX: Create reports and dashboards without coding knowledge via intuitive drag-and-drop tools. Supports different analytic styles, such as visual discovery, and mobile, and third-party tools such as Excel, R and Tableau. 
  • Reusable Rules: Automatically generates a common architecture based on a reusable set of business definitions without manual intervention.
  • Interactive Dashboards: Explore data even further via interactive dashboards that have drill-down capabilities such as lasso filters.
  • Multi-Tenant Cloud Architecture: Scales vertically and horizontally with a multi-tenant architecture built on a multi-node environment. Speeds insight generation by reducing the overall time spent on repetitive on-premise tasks. 
  • One-Click Data Connectivity: Access existing data with one click via its extensive library of pre-built connectors.
  • Embedded Analytics: Scale with clients’ businesses via flexible deployment options including embedding, APIs and localization capabilities.
  • Machine Learning: Recognizes patterns in data via Smart Analytics and automatically builds visualizations based on predictive analytics. Learns over time, and remembers previous search queries, past visualizations and more.
  • Deployment Options: Deploy as a SaaS through the cloud or go hybrid, keeping data in-house but running analytics through cloud-based servers. Or, deploy through a virtual appliance that delivers all the benefits of a traditional cloud-hosted SaaS while being locally hosted on-premise or in a private-cloud.
  • Mobile App: Access reports and dashboards via its native mobile application for iOS and Android.
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Product Ranking

#28

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#22

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Analyst Rating Summary

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Analyst Ratings for Functional Requirements Customize This Data Customize This Data

SAS Visual Analytics
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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 137 reviews
Great User Sentiment 560 reviews
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.

82%
of users recommend this product

Infor Birst has a 'great' User Satisfaction Rating of 82% when considering 560 user reviews from 6 recognized software review sites.

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4.3 (7)
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Awards

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

Data Pre-processing Award

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Synopsis of User Ratings and Reviews

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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Data Integration: About 80% of users who mentioned its data integration capabilities said that the platform, powered by built-in connectivity tools, connected well to many types of data sources.
Data Visualization: Approximately 81% of users who reviewed visualization said that the tool provided attractive and intuitive data presentation options for at-a-glance data analysis and trend charting.
Ease of Use: The platform was user-friendly and intuitive, according to around 77% of users who reviewed the interface.
Functionality: Approximately 68% of users who reviewed functionality said that the platform provided strong capabilities to streamline preparation and consumption of data for developers and end users alike.
Data Management: Automated data warehouse creation made data modeling a breeze, around 65% of users who reviewed the platform’s data management system said.
Setup: Around 69% of users who mentioned implementation said that the solution being cloud-based, coupled with excellent onboarding support from the vendor, made deployment easy.
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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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Performance: Approximately 87% of users who reviewed the platform’s performance said that it was slow and inconsistent in data processing and data refresh.
Learning Curve: About 81% of users who mentioned the learning curve said that documentation was often insufficient and incorrect, and that the platform’s use of proprietary language made the learning curve quite steep.
Service and Support: About 46% of users who reviewed this feature said that support was poor and turnaround times were painfully long, extending up to several months.
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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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Infor Birst is an integrated cloud-based end-to-end solution for sourcing raw data, and extracting, warehousing and reporting for enterprise data analysis. With built-in tools for data integration and strong embedded analytics capabilities, users leverage its data visualization capabilities to create and share metric-specific dashboards and reports. Users who reviewed data management said that automated data warehouse creation was a strong feature of the platform, as well as its user-friendly interface. Many users who reviewed its functionality said that, equipped with a powerful ETL and efficient ODBC drivers for integration, the platform was flexible and scalable with a multitude of features for data discovery and analysis. Around 69% of users who reviewed ease of implementation said that deployment was easy with the integrated cloud platform, though some users said that the setup processes were unclear and they required in-house IT support for onboarding. On the flip side, users who mentioned performance said that the speed of data processing and data refresh was slow and this impacted report generation capabilities. Documentation was inconsistent and often incorrect, and the use of proprietary query language made the learning curve quite steep, many users who reviewed this feature said. Support turnaround times were woefully long, even extending up to several months as reported by a number of users. Some users who reviewed functionality said that the code was buggy and the platform stalled often when processing data for ad-hoc reporting. Many users complained that these bugs were not addressed for years, and new releases often impacted pre-existing features. Possibly because of its performance issues with large amounts of data, quite a few users rate it as a good BI tool for small and midsize companies that require less complex data analysis, rather than larger enterprises. In summary, Infor Birst is a BI ecosystem with a networked approach to data visualization and predictive analytics that eliminates data silos and serves as a single source of truth for enterprise data.

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