SAS Viya vs 1010data

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Our analysts compared SAS Viya vs 1010data based on data from our 400+ point analysis of Big Data Analytics Tools, user reviews and our own crowdsourced data from our free software selection platform.

1010data Software Tool

Product Basics

SAS Viya is a cloud-based in-memory analytics engine that provides data visualization, reporting and analytics to businesses for actionable data insights. Powered by AI, it brings together visual analytics, visual statistics and data science for enterprises to achieve end-to-end self-service analytics. It uses a standardized code base with support for programming in R, Python, SAS, Java and Lua.

Deployable in the cloud, on-premises and hybrid environments, it integrates with a wide range of business applications through an agile, scalable architecture. The vendor offers an introductory 30-day free trial.

Pros
  • Comprehensive features
  • Powerful analytics capabilities
  • User-friendly interface
  • Scalable architecture
  • Strong support from SAS
Cons
  • Steep learning curve
  • Limited customization options
  • High cost of ownership
  • Potential vendor lock-in
  • Resource-intensive
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1010data is a market intelligence and enterprise analytics solution that helps track consumer insights and market trends. In addition to vendor-critical insights, it provides brand performance metrics to buy-side entities. Seamlessly embeddable, it can also function as a standalone private-label option. Data scientists and statisticians leverage its integration with R to view and query data tables.

It enables analytics development through its QuickApps framework. By tracking consumer spending trends and brand performance, it enables businesses to better position their products in the marketplace.
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$10,000 Annual
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$12,000/User, Annually
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Small
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Small
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Large
Windows
Mac
Linux
Android
Chromebook
Windows
Mac
Linux
Android
Chromebook
Cloud
On-Premise
Mobile
Cloud
On-Premise
Mobile

Product Assistance

Documentation
In Person
Live Online
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Documentation
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Live Online
Videos
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Email
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FAQ
Forum
Knowledge Base
24/7 Live Support
Email
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Knowledge Base
24/7 Live Support

Product Insights

  • Improve Decision-Making: Make informed business decisions by using historical and current proprietary information to derive analytical insights. Compute vast amounts of data faster and resolve complexities through parallel processing. Boost workflow efficiencies by deploying operational decisions that define real-time best actions at scale. 
  • Self-Service Analytics: Easily perform automated forecasting, goal-seeking and scenario analysis — no technical skills needed. Identify user sentiment through text analytics and incorporate geographical data for a complete picture of business metrics. 
  • Maximize ROI: Save time through built-in automation for data prep, feature engineering, algorithm selection and AI-powered data discovery. Innovate, rather than spending time on tedious data management and analytics tasks. 
  • Data Security: Ensure data encryption at rest and while moving across systems, in addition to auditing protocols. Connect to external data management systems like Oracle, Teradata, Facebook, Amazon and Esri seamlessly through Kerberos, SAML, OAuth and OpenID. 
  • Data Management: Import data by using an IDE or through REST APIs, and visualize and analyze it through self-service data prep. Join tables, apply functions and perform calculations, or drag-and-drop, pivot, and slice and dice to view desired metrics. 
  • Augmented Analytics: Identify relationships in data through automatically generated suggestions and guided analysis, and track anomalies and outliers. Tell data stories by generating easy-to-understand visuals and dashboard summaries in natural language. Derive meaningful insights for the future by creating what-if scenarios for forecasting and predictive analytics. 
  • Mobility: Access business reports on the go through a native mobile app that supports a variety of charts, graphs and tables. Configure app functionality per device for specific users to add and view reports, share links, add and view comments and view alerts. 
  • Scalable Architecture: Leverage its modular microservices architecture to scale as per business needs. Monitor and manage the health and configuration of individual microservices instances through the SAS Environment Manager. Deploys seamlessly to any type of environment, including the cloud, and runs on Cloud Foundry as a platform-as-a-service (PaaS). 
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  • Track Consumer Trends:  Discover how consumers search for and assess products before buying. Identify product affinities by segments and add value through basket analysis to expand the category assortment. Analyze customers based on geography and spending tiers to create targeted marketing strategies. 
  • Analyze Buyer Behavior:  Drive customer retention and higher loyalty by analyzing shopper lifecycles by retailer with geographical drill-down capabilities. Track the path-to-purchase customer experience and the buyer acquisition process. Monitor points of purchase — whether in-store or online, which stores were visited pre-purchase and the items considered before buying. 
  • Maximize ROI:  Assess shopping behavior at the category, brand, merchant and product levels. Analyze conversion rates and key metrics’ progression over time by new, lost and retained customers. Uncover churn rate figures by segment and spending capacity to drive remedial strategies. 
  • Track the Competition:  Track the product’s market position across hundreds of consumer goods categories. Identify disruptors from other brands on the market. Justify specific product category positioning with data on emerging competitors. Analyze merchandising strategies and promotional spend across merchants. 
  • Application Development:  Create end-to-end analytic applications directly atop proprietary granular data through its QuickApps framework and iterate when needed. Deploy them via desktop web, mobile devices or external applications with legacy governance parameters. 
  • Buy-Side Insights:  Inform buy-side investment decisions by tracking consumer spending, transactions and basket size of multiple brands. Analyze company performance by quarter, month, week and day. Get granular insights on sector trends, customer segments or geospatial consumer data, refreshed daily. 
  • Data Security:  Secure by design, it has a stateful architecture for privately allocated, separate user sessions. It is HIPAA compliant and SOC 2 Type II certified, with support for single sign-on via SAML 2.0 authentication. 
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  • Visualization and Reporting: Dig into data for in-depth analysis and view key business metrics through autonomous data exploration and manipulation. Create and customize interactive reports and charts to share with others across the organization for collaborative insight. Get suggestions on graphics best suited to display pertinent data through auto charting. 
  • Data Modeling: Analyze data with predictive models through regression, clustering and neural networks. Ensure version control by tracking data models from creation through usage by registering, validating and monitoring each version. Creates snapshots of model properties and files and retains them for the future. 
  • Visual Statistics: Build diverse scenarios simultaneously and refine them with what-if analyses to uncover insights through experimentation. Unifies all business tools, irrespective of the language they support, into a common visual analytics solution. 
  • Cloud Integrations: Develop low-code technologies by porting SAS open-source models into mobile and business applications through its cloud-native capability. Optimize analytics workloads on clouds like Microsoft Azure and ensure cost-efficient migration of analytics to the cloud through a workload management tool. 
  • ML-Based Insights: Get valuable insights from new data types by combining structured and unstructured data in integrated machine learning programs. Choose the desired ML algorithm from a range of options and easily find the optimal parameter settings. Use Python within Jupyter notebooks for deep learning functions like computer vision, natural language processing, forecasting and speech processing. 
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  • Cloud-Native: Built from the ground up to enable large-scale, multi-party data sharing and analytics in the cloud. 
  • Advanced Analytics: Derive meaningful data insights by creating advanced data models against complex data sets. Perform time-series analysis, statistical functions and machine learning through its functions library. 
  • Visualizations: Create charts, graphs, heat maps and more through its rich functions library and a visual expression builder. Leverage the power of analytics through integration with visualization tools like Tableau, Logi Analytics, Information Builders and Metric Insights. 
  • Reporting: Acquire business-critical insights through standardized reporting, consistent KPI monitoring and guided ad-hoc reporting. Gain confidence in data with full visibility into proprietary information and calculation lineage. Save data results locally or to a file system via FTP, or in a data table. Or, export it in CSV, PDF or Excel format. 
  • Data Management: Pull and blend disparate, complex data sets on-the-fly into an analysis-ready format. Assign role-based permissions for access to tables, rows and columns. Tracks usage activity through audit trails and logs that include the account information, IP address and tables accessed. 
  • Integrations: Run advanced data analytics via the R console through R1010. Easily access data tables and view them in Tableau with real-time integration, data discovery and SQL support. Create spreadsheets that access the 1010 data platform via its Excel add-in. 
  • Universal Calculation Library: Quickly answer data-based queries by analyzing complex datasets through centralized and standardized calculations. 
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Product Ranking

#41

among all
Big Data Analytics Tools

#44

among all
Big Data Analytics Tools

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Analyst Rating Summary

94
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96
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98
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Analyst Ratings for Functional Requirements Customize This Data Customize This Data

SAS Viya
1010data
+ Add Product + Add Product
Augmented Analytics Computer Vision And Internet Of Things (IoT) Dashboarding And Data Visualization Data Management Data Preparation Geospatial Visualizations And Analysis Machine Learning Mobile Capabilities Platform Capabilities Reporting 96 100 98 96 86 93 70 96 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 203 reviews
Good User Sentiment 25 reviews
85%
of users recommend this product

SAS Viya has a 'great' User Satisfaction Rating of 85% when considering 203 user reviews from 3 recognized software review sites.

78%
of users recommend this product

1010data has a 'good' User Satisfaction Rating of 78% when considering 25 user reviews from 2 recognized software review sites.

4.2 (157)
n/a
4.3 (33)
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4.7 (13)
4.0 (18)
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3.7 (7)

Awards

SelectHub research analysts have evaluated SAS Viya and concluded it deserves the award for the Best Overall Big Data Analytics Tools available today and earns best-in-class honors for Augmented Analytics and Computer Vision and Internet of Things (IoT).

Analysts' Pick Award
Augmented Analytics Award
Computer Vision and Internet of Things (IoT) Award

No awards.

Synopsis of User Ratings and Reviews

Ease of Use: All users who mention its interface say that it makes autonomous analysis and data modeling accessible to users of all skill levels.
Support: All users who review support say that representatives are responsive and helpful in resolving issues and queries.
Functionality: Around 71% of the users who comment on its feature set say that the software helps discover data insights through powerful visualizations and on-the-fly calculations.
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Robust Data Processing: Handles large volumes of structured and unstructured data efficiently, enabling comprehensive data analysis.
Scalable Architecture: Supports growing data volumes and user demands, ensuring seamless performance as your business expands.
Advanced Analytics Capabilities: Provides sophisticated machine learning algorithms and statistical techniques for in-depth data exploration and predictive modeling.
User-Friendly Interface: Intuitive dashboards and visualization tools simplify data analysis, making it accessible to users of all technical levels.
Data Security and Compliance: Adheres to industry standards and regulations, ensuring the protection and privacy of sensitive data.
Cost-Effective Solution: Offers flexible pricing models and cloud-based deployment options, reducing upfront investment and ongoing maintenance costs.
Excellent Customer Support: Provides dedicated technical support and documentation, ensuring smooth implementation and ongoing assistance.
Community and Resources: Fosters a vibrant user community and offers extensive resources, including tutorials, webinars, and case studies.
Integrations with Other Tools: Seamlessly connects with popular business intelligence and data visualization tools, enhancing data analysis capabilities.
Proven Track Record: Trusted by numerous businesses and organizations, delivering successful data-driven initiatives.
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Cost: All users who discuss its pricing say that the cost of acquisition is high.
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Complexity: Challenging to use for non-technical users, requiring specialized knowledge and skills.
Limited Customization: Pre-defined templates and limited flexibility, hindering the adaptation to specific business needs.
Data Quality Issues: Inconsistent data quality and lack of data validation tools, leading to unreliable insights.
Scalability Challenges: Struggles to handle large and complex datasets, resulting in performance issues and delayed analysis.
Vendor Lock-in: Proprietary technologies and limited data portability, restricting users from switching to alternative solutions.
Costly Licensing: Expensive licensing fees and hidden costs, making it unaffordable for some organizations.
Lack of Real-time Analysis: Inability to process and analyze data in real-time, hindering timely decision-making.
Insufficient Support: Limited technical support and documentation, leaving users struggling with implementation and troubleshooting.
Privacy Concerns: Concerns about data privacy and security, as tools often require access to sensitive information.
Steep Learning Curve: Extensive training and time investment required to master the tools, hindering adoption.
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SAS Viya is an AI-powered data management and visual analytics platform with a robust, scalable architecture. All users who reviewed data source connectivity said that it connects to multiple sources and integrates easily with business applications, giving a seamless user experience. With fast in-memory processing of big data sets, it leverages the power of R to enable visual statistics. All users who mentioned predictive analysis said that it enables automated forecasting through what-if scenarios, goal-seeking, text mining and decision trees. Citing ease of use, all users say that the platform is intuitive and enables easy data modeling and self-service visual analytics. All users who mentioned support said that they are responsive and knowledgeable. Around 71% of the users who comment on its functionality say that it is a robust, scalable and flexible platform that enables visualization and analysis of business data, though some users say visual statistics need improvement. On the flip side, all users who review its cost say that the tool is expensive. In summary, SAS Viya is an analytics tool that provides data management, visualization and AI-powered analytics to enterprises for improved decision making, though small organizations and startups might find it cost-prohibitive.

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1010data's user reviews over the past year paint a picture of a robust big data analytics tool with strengths in data visualization, ease of use, and customer support. Users have praised its intuitive interface, which allows even non-technical users to quickly create and share insights. Additionally, the tool's advanced visualization capabilities, such as interactive dashboards and customizable charts, have been highlighted as key differentiators, enabling users to explore and present data in a visually appealing and impactful manner. However, some users have expressed concerns regarding the tool's scalability and performance when handling extremely large datasets. Additionally, the lack of certain advanced features, such as real-time analytics and predictive modeling, has been noted as a weakness compared to more comprehensive analytics platforms. Nonetheless, 1010data remains a popular choice for businesses seeking a user-friendly and visually oriented tool for their data analytics needs, particularly for those with smaller to mid-sized datasets.

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