SAS Analytics - Detailed Review
E-Commerce Tools
SAS Analytics - Product Overview
Introduction to SAS Viya in the E-Commerce Tools AI-Driven Product Category
Primary Function
SAS Viya is a cloud-enabled, in-memory analytics engine that provides quick, accurate, and reliable analytical insights. It is designed to handle complex analytical challenges, including machine learning, deep learning, and artificial intelligence, making it a powerful tool for data-driven decision-making in various industries, including e-commerce.
Target Audience
SAS Viya caters to a diverse range of users across different industries and company sizes. This includes data scientists, business analysts, application developers, and domain experts in sectors such as finance, healthcare, retail, manufacturing, and government. It is suitable for both small businesses needing basic analytics and large enterprises requiring advanced solutions for complex data analysis and decision-making.
Key Features
Scalability and Flexibility
SAS Viya is elastic and scalable, allowing it to adapt to both private and public cloud environments. It can handle burst processing and scale computing capacity as needed, making it ideal for handling large volumes of data and complex analytical workloads.
Multi-Language Support
The platform supports programming in SAS as well as other languages like Python, R, Java, Lua, and Scala. This allows analytical professionals to use their preferred coding language, enhancing productivity and collaboration.
Integrated Environment
SAS Viya provides a single, centrally managed web-based environment that integrates data access, preparation, interactive exploration, statistics, forecasting, optimization, machine learning, and other advanced analytics activities. This unified environment reduces the need for multiple tools and streamlines the analytics life cycle.
Generative AI Integration
SAS Viya has been enhanced with generative AI capabilities, including the integration of large language models (LLMs) to accelerate efficiency and productivity. Features like Viya Copilot and SAS Data Maker help in tasks such as code generation, data cleaning, and synthetic data creation while ensuring data privacy and security.
Governance and Security
The platform offers centralized administration, activity tracking, and comprehensive governance features, including full versioning, authorship, lineage viewer, and change management. This ensures secure and governed analytics across the organization.
High-Performance Processing
SAS Viya features fast, distributed in-memory processing that can handle multiple users and complex analytical workloads. It ensures fault-tolerant processing, retaining high speed even in case of node failures.
By combining these features, SAS Viya enables organizations to solve analytics problems of any size or complexity, accelerate innovation, and make more precise decisions, all within a secure and scalable environment.
SAS Analytics - User Interface and Experience
User Interface of SAS Viya
The user interface of SAS Viya, which is the AI and analytics platform from SAS, is designed to be intuitive, user-friendly, and highly engaging, particularly for users in various roles such as data engineers, data scientists, MLOps engineers, and business analysts.Intuitive Visual Interfaces
SAS Viya features intuitive visual interfaces that make it easy for users to manage, model, and deploy data and AI projects. The platform offers a centralized hub where users can access all the tools they need, from data integration and preparation to model development and deployment. This visual approach helps in simplifying complex analytics tasks and makes the platform accessible to users of all skill levels.Low- and No-Code Options
One of the standout features of SAS Viya is its low- and no-code capabilities. This allows users, especially business analysts, to perform a significant portion of the data and AI life cycle tasks without extensive coding knowledge. For example, data engineers can use drag-and-drop tools to craft data pipelines, and data scientists can leverage prebuilt model templates to speed up their work.Automation and Efficiency
The platform is heavily automated, which enhances ease of use. Automated ETL processes save hours for data engineers, and built-in automation for data exploration and reporting accelerates tasks by up to 69 times for data scientists. This automation ensures that users can focus on higher-value tasks rather than getting bogged down in manual processes.User-Centric Design
SAS places a strong emphasis on user-centric design. The Filament Design System, used across SAS products, ensures that the interfaces are modern, high-quality, and intuitive. This design approach is based on extensive user research and feedback, which helps in creating experiences that meet the users’ goals and anticipate their future needs.Collaboration and Transparency
SAS Viya promotes collaboration through its centralized platform, allowing different teams to work together seamlessly. The platform provides transparent access to data, model lineage, and performance reports, which helps in maintaining data quality and model integrity. This transparency also aids in explaining work easily through natural language descriptions of visualizations and metrics.Overall User Experience
The overall user experience of SAS Viya is characterized by its ease of use, efficiency, and engagement. The platform is designed to simplify complex analytics tasks, making it accessible to a wide range of users. The combination of visual interfaces, low- and no-code options, and automation ensures that users can quickly generate insights and deploy models without significant technical hurdles. This results in a productive and engaging experience, allowing users to focus on deriving valuable insights from their data rather than struggling with the tools themselves. SAS Analytics - Key Features and Functionality
SAS Analytics Overview
SAS Analytics, particularly through its SAS Viya platform, offers a range of features and functionalities that are highly beneficial for e-commerce and other industries, especially when integrated with AI. Here are the main features and how they work:
Data Management
SAS Viya allows users to access and integrate data from virtually any source, regardless of size or complexity. This includes seamless read, write, and update access to data from various platforms. The platform simplifies data preparation with a suggestion engine and tracks data and model lineage, ensuring that any changes in data are reflected in the models that use it.
AI-Driven Automation
The platform includes comprehensive machine learning tools with automated feature engineering capabilities. These tools provide intelligent recommendations for optimizing and identifying the most effective models, making it easier for data scientists to generate trusted outcomes from their data. AI-driven automation supports end-to-end data mining and machine learning processes, accessible through both visual and programming interfaces for users of all skill levels.
Predictive Analytics
SAS Viya supports predictive analytics through various techniques such as ARIMA, UCM, and other models. For example, in e-commerce demand forecasting, SAS Forecast Studio can be configured to automate weekly forecasting for tens of thousands of products, taking into account factors like seasonality, price, and demand variability. This helps in creating accurate forecasts and identifying exception forecasts that need adjustment.
Location Analytics
By combining traditional data sources with location data, SAS Viya enables location analytics. This feature is crucial for e-commerce as it helps in analyzing data in a geographical context, identifying location-specific opportunities, and making data-driven decisions about regional store performance or customer behavior.
Augmented Analytics
Augmented analytics in SAS Viya automatically gives users suggestions and identifies related measures, helping to discover real stories hidden in the data quickly. This feature uses machine learning and natural language explanations to find, visualize, and narrate insights, making it easier to find why something happened and uncover hidden opportunities.
Generative AI Integration
SAS has integrated generative AI capabilities into its platform, particularly within the Customer Intelligence 360 marketing solution. This allows marketers to use large language models (LLMs) like ChatGPT to create marketing plans, build audience segments, and generate personalized text content. The integration is done via the SAS connector framework, ensuring safe and responsible use of generative AI.
Real-Time Analytics
SAS Viya includes real-time distributed database capabilities and event streaming analytics. This allows for the analysis of streaming data, uncovering hidden insights with AI, and making real-time, intelligent decisions. This is particularly useful in e-commerce for real-time inventory management, customer behavior analysis, and immediate response to market changes.
Model Deployment and Governance
The platform simplifies the creation and management of model collections, enabling users to easily embed models into operational systems and monitor their performance. It also includes model cards that provide governance details about AI applications, ensuring transparency and accountability in AI-driven decisions.
Collaboration and Accessibility
SAS Viya offers a centralized platform that enhances collaboration. It includes interactive reports and dashboards that can be shared via the web and mobile devices, allowing executives and front-line staff to interact with and collaborate on insights. The platform also supports integration with Microsoft productivity tools, making it easy to access and interact with reports within applications like Excel and Outlook.
These features collectively enable e-commerce businesses to make smarter, data-driven decisions, automate complex analytical tasks, and gain deep insights into their operations and customer behavior.
SAS Analytics - Performance and Accuracy
Performance
SAS Viya is highlighted for its exceptional performance across various aspects of data and AI analytics. Here are some key performance metrics:Speed
SAS Viya is noted for transforming raw data into trustworthy insights 4.6 times faster than other commercial and non-commercial platforms. It also trains AI models 30 times faster than open-source and commercial offerings, allowing models to move from the sandbox to production quickly.Scalability
The platform demonstrates consistent, scaled performance as CPU, memory capacity, and complexity grow. It continues to produce results in minutes where alternatives may run for hours or fail.Efficiency
SAS Viya reduces cloud operating costs by up to 86% compared to alternatives, largely due to its efficient data and AI life cycle management.Accuracy
The accuracy of SAS Viya is supported by several features:Advanced Analytics
The platform uses advanced analytics and predictive modeling to accurately identify patterns and correlations in data. This is particularly evident in its ability to detect hidden patterns indicating impending failures or performance degradation.Root-Cause Analysis
SAS Viya includes tools for superior root-cause analysis, such as explorative analysis, design of experiments, and cause-and-effect tools like Ishikawa diagrams. This helps in quickly and accurately identifying the root causes of issues.Model Optimization
The platform allows for transparent model tuning, ensuring that the most effective models are identified and optimized for use. This enhances the accuracy of predictions and decisions made from the data.Limitations and Areas for Improvement
While the sources do not specifically highlight limitations of SAS Viya in the e-commerce context, some general considerations can be inferred:Specialized Use Cases
There may be instances where specialized libraries outperform SAS Viya in specific tasks, although Viya generally outperforms other general-purpose libraries in most test cases.Data Quality and Integration
The effectiveness of SAS Viya depends on the quality and integration of the data it processes. Ensuring that data is well-integrated and of high quality is crucial for optimal performance and accuracy. In summary, SAS Viya demonstrates strong performance and accuracy in data and AI analytics, with capabilities that can be highly beneficial across various industries, including potentially e-commerce. However, the specific application and effectiveness in e-commerce tools would require more targeted evaluation. SAS Analytics - Pricing and Plans
SAS Viya Tiers
SAS Viya is offered in several tiers, each with a different set of features and capabilities:
SAS Viya
- This foundational offering includes features such as data access, preparation, and integration, data catalog, quality, and governance, in-database technologies, workload management, visualization and reporting, statistics, matrix programming, machine learning and deep learning, model deployment and management, forecasting, text analytics, and optimization.
SAS Viya Advanced
- This tier includes all the features from the SAS Viya tier, with additional advanced capabilities such as more extensive machine learning and deep learning tools, and enhanced model deployment and management.
SAS Viya Enterprise
- This is the most comprehensive tier, offering all the features from the previous tiers plus additional functionalities like event streaming analytics and intelligent decisioning.
SAS Viya Programming
- This option is more focused on programming and includes data access, preparation, and integration, workload management, visualization and reporting, statistics, matrix programming, machine learning and deep learning, and forecasting. It is geared more towards developers and programmers.
Pricing Model
The pricing model for SAS Viya is flexible and can be adapted to different needs:
- Pay-as-you-go: Available on Azure Marketplace, this model allows users to pay only for the resources they use, making it a cost-effective option.
- Enterprise Licensing: For larger organizations, SAS offers enterprise licensing agreements that can be customized based on the specific needs and scale of the organization.
Free Options
For students, educators, and independent learners, SAS provides free access to certain analytics tools:
- SAS OnDemand for Academics: Offers statistical analysis, data mining, and forecasting software with up to 5GB of data storage.
- SAS Viya for Learners: Provides an integrated suite of interactive visual interfaces for learning data science, including AI, text analytics, and machine learning.
Additional Considerations
While the website does not provide detailed pricing figures, it emphasizes the flexibility and scalability of the SAS Viya offerings. Users can choose the tier that best fits their needs, and the pay-as-you-go model on Azure Marketplace adds an element of cost control.
For precise pricing details, it is recommended to contact SAS directly or consult their sales team, as the pricing can vary based on the specific requirements and the scale of the organization.
SAS Analytics - Integration and Compatibility
SAS Analytics Overview
SAS Analytics, particularly through its SAS Viya platform, offers robust integration and compatibility features that make it a versatile tool for e-commerce and other business applications.
Integration with Other Tools
SAS Viya is designed to integrate seamlessly with a variety of tools and platforms. Here are some key integration points:
Open Source Technologies
SAS Viya supports the integration of open source technologies across the analytics lifecycle. This allows users to leverage models developed in different languages and frameworks, such as Python, R, and SQL, and deploy them in various environments, including cloud platforms like Azure.
MS Office Applications
SAS can be integrated with Microsoft Office applications like Outlook, Word, and Excel through SAS Integration Technologies. This facilitates smooth data exchange and reporting.
Other Business Tools
SAS can also integrate with various business tools, including those for e-commerce, analytics, team communication, accounting, and project management. While specific integrations like Slack, PayPal, Google Analytics, and QuickBooks are more commonly associated with other platforms, SAS’s flexibility through APIs and custom integrations makes such connections possible.
Cross-Platform Compatibility
SAS Viya and its associated tools are compatible with a range of platforms and devices:
Web Browsers
SAS Viya applications are supported on modern web browsers such as Apple Safari, Google Chrome, Microsoft Edge on Chromium, and Mozilla Firefox. These browsers need to run on 64-bit operating systems for optimal performance.
Mobile Devices
While some SAS user interfaces are not supported on mobile devices, the SAS Visual Analytics App is available on iOS, Android, and Windows 10 smartphones and tablets. This allows users to view and explore reports on their mobile devices.
Operating Systems
SAS Viya supports UNIX 64-bit and Windows 64-bit operating systems. For example, SAS Enterprise Guide works effectively on Windows 11, including devices with ARM architecture, as long as the hardware supports full Windows functionality.
Deployment and Execution
SAS Viya allows for flexible deployment and execution of analytics models. Users can deploy models to multiple destinations, execute analytics in batch, or use APIs for integration into business applications. This flexibility ensures that models can be put into production in a centralized and governed manner, meeting various scalability requirements.
Conclusion
In summary, SAS Analytics through SAS Viya offers extensive integration capabilities with various tools and platforms, along with broad compatibility across different operating systems and devices, making it a highly adaptable and useful solution for e-commerce and other business analytics needs.
SAS Analytics - Customer Support and Resources
Support Options for SAS Analytics
When using SAS Analytics, whether in the context of e-commerce or other applications, you have access to a comprehensive range of customer support options and additional resources. Here’s a breakdown of what you can expect:
Support Tiers
SAS offers three distinct tiers of support: Standard Support, Premium Support, and Elite Support. Each tier provides varying levels of service to meet different business needs.
- Standard Support: This tier includes phone or email support, where your questions and technical issues are addressed as quickly as possible by SAS experts. You also get access to extensive online resources, educational materials, and important software updates and hot fixes to keep your technology running smoothly.
- Premium Support: This tier includes all the benefits of Standard Support, plus additional features such as an Enhanced Support Service Level Agreement (SLA), a Technical Support Account Manager, premium support workshops, status reports and meetings, and access to a case dashboard. This level is ideal for businesses that require more personalized and proactive support.
Technical Support
For specific technical issues, you can contact SAS Technical Support through various channels:
- Phone: You can report critical problems by calling the provided phone numbers, which vary by region.
- Chat: There is a chat option available through the SAS website, allowing you to connect with technical support agents in real-time.
- Email: You can send an email to support@sas.com with detailed information about your problem, including product details, operating system, and any troubleshooting steps you’ve taken. This ensures quick and efficient service.
Additional Resources
SAS provides a wealth of resources to help you get the most out of their software:
- Customer Support Site: This site offers extensive resources, including educational materials, software updates, and hot fixes. It helps you advance your skills and get questions answered.
- Online Resources: SAS offers various online resources, such as documentation, tutorials, and community forums, to help you resolve issues and improve your use of the software.
- Workshops and Reports: For Premium Support users, there are additional resources like premium support workshops and regular status reports and meetings to ensure you’re well-supported and informed.
These support options and resources are designed to help you resolve issues quickly, enhance your skills, and ensure your SAS software is always up and running efficiently.
SAS Analytics - Pros and Cons
Advantages
Comprehensive Data Handling
SAS Analytics offers strong capabilities in managing and analyzing large, complex data sets, which is crucial for e-commerce businesses that deal with vast amounts of customer and transaction data.
Business Intelligence
SAS provides advanced business intelligence tools that help in analyzing historical, present, and predictive perspectives of business operations, enabling better decision-making.
Predictive Analytics
It utilizes statistical strategies to predict future trends and outcomes, which can be invaluable for forecasting demand, customer behavior, and market trends in e-commerce.
Efficient Data Integration and Processing
SAS Viya, for instance, offers rapid data integration, automated ETL processes, and the ability to handle large and complex data sets efficiently. This can save hours for data engineers and improve data quality.
User-Friendly Interfaces
SAS Viya provides low-code and no-code options, making it easier for business analysts to perform data exploration and reporting tasks without extensive technical knowledge.
Strong Support and Documentation
SAS is known for its comprehensive support and documentation, which can be a significant advantage for users who need reliable resources to troubleshoot and optimize their analytics processes.
Disadvantages
Cost
One of the significant drawbacks of SAS Analytics is its cost. The software requires licenses, and some advanced features, such as time series forecasting (SAS/ETS), are available only through additional modules, making it expensive.
Steep Learning Curve
SAS has a procedural language that can be more challenging to learn compared to other analytics tools like R. It often requires more lines of code and prior knowledge of statistical procedures.
Limited Customization and Flexibility
SAS is not as flexible as some open-source alternatives and provides limited customization options, which can be a hindrance for users who need specific tailored solutions.
Graphical Capabilities
SAS is less adept at creating complex graphical plots compared to R, which can be a disadvantage for users who need advanced data visualization.
Closed Source
The algorithms used in SAS are not open to the public, which restricts public research and customization. This is in contrast to open-source tools like R, which can be modified and extended by anyone.
Summary
While SAS Analytics offers powerful tools for data analysis and business intelligence, its high cost, steep learning curve, and limited flexibility are significant considerations for e-commerce businesses evaluating their analytics solutions.
SAS Analytics - Comparison with Competitors
Unique Features of SAS Viya
- Comprehensive Analytics Platform: SAS Viya is a cloud-native AI, analytics, and data management platform that integrates data exploration, visualization, model development, and deployment. It supports multiple types of machine learning models and operates in both public and private cloud environments, as well as on-premises.
- Scalability and Performance: SAS Viya is known for its performance and scalability, outperforming many general-purpose libraries in various test cases. It is designed to handle large-scale data and analytics workloads efficiently.
- Self-Service Analytics: SAS Visual Analytics, part of the SAS Viya ecosystem, offers self-service analytics capabilities, including automated forecasting, goal seeking, scenario analysis, and decision trees. This makes it accessible to users of various skill levels.
- Location Analytics: It allows combining traditional data sources with location data for geographical analysis, which can be particularly useful for eCommerce businesses looking to analyze customer behavior and market trends geographically.
- Augmented Analytics: SAS Visual Analytics includes augmented analytics that automatically suggest insights and identify related measures, helping users uncover hidden stories in their data quickly.
Alternatives and Comparisons
Customer Experience and Personalization
- Lyro AI Chatbot: While Lyro is excellent for automated customer support and engagement, it is more focused on chatbot interactions rather than comprehensive analytics. Lyro uses natural language processing to provide 24/7 customer support but lacks the broad analytical capabilities of SAS Viya.
- Nosto: Nosto is an AI-driven platform that creates personalized shopping experiences by analyzing customer behavior and preferences. However, it is more specialized in personalization and marketing automation rather than offering a full suite of analytical tools like SAS Viya.
Data Analytics and Visualization
- Google Analytics: Google Analytics is a powerful tool for tracking website traffic and behavior but does not offer the advanced machine learning and data management capabilities of SAS Viya. It is more suited for basic web analytics rather than deep data analysis.
- Tableau and Power BI: These tools are excellent for creating interactive dashboards and visualizations but may not match the scalability and performance of SAS Viya. They are more focused on data visualization rather than the end-to-end analytics lifecycle supported by SAS Viya.
AI-Driven Optimization
- Adobe Sensei: Adobe Sensei integrates with Adobe Commerce to provide AI-driven features such as personalized product recommendations and automated catalog management. While it offers strong AI capabilities, it is more integrated within the Adobe ecosystem and may not provide the same level of flexibility and scalability as SAS Viya.
- OptiMonk AI: OptiMonk AI enhances website engagement and conversion rates through personalization. It is highly effective for real-time visitor segmentation and targeted campaigns but does not offer the broad analytical and machine learning capabilities of SAS Viya.
Conclusion
SAS Viya stands out due to its comprehensive suite of analytics tools, scalability, and performance. While other tools like Lyro, Nosto, Adobe Sensei, and OptiMonk AI are excellent in their specific domains such as customer support, personalization, and marketing automation, they do not match the breadth and depth of analytical capabilities offered by SAS Viya. For eCommerce businesses needing a robust, cloud-native analytics platform that can handle complex data analysis and machine learning tasks, SAS Viya is a strong contender. SAS Analytics - Frequently Asked Questions
Frequently Asked Questions about SAS Analytics in E-Commerce and AI-driven Products
Q: What are the key features of SAS Visual Analytics for E-Commerce?
SAS Visual Analytics offers several key features that are beneficial for E-Commerce. These include interactive reporting, visual discovery, and self-service analytics, all within a single, powerful in-memory environment. It allows users to visually explore data, create and share smart visualizations and interactive reports, and perform advanced analytics such as automated forecasting and scenario analysis.Q: How does SAS Visual Analytics support location analytics in E-Commerce?
SAS Visual Analytics enables the combination of traditional data sources (like transactional, customer, and operational data) with location data. This allows for analysis in a geographical context, which can be crucial for understanding regional store performance, customer behavior, and other location-specific insights in E-Commerce.Q: What AI capabilities does SAS offer for E-Commerce analytics?
SAS has introduced several AI-driven features to enhance analytics efficiency. These include a generative AI assistant, prebuilt AI models, and synthetic data generation capabilities. Additionally, SAS is planning to add more generative AI features, such as using natural language to develop data flows, models, and dashboards, and improving data management with a focus on data quality.Q: How can SAS Visual Analytics be used for demand forecasting in E-Commerce?
SAS Forecast Studio, part of the SAS Visual Analytics suite, can be used for large-scale demand forecasting. For example, an e-commerce retailer can configure SAS Forecast Studio on a cloud-based server to automate weekly forecasting for tens of thousands of products. This involves pre-processing data, modeling demand patterns, and creating detailed accuracy reports to ensure accurate forecasts.Q: Can SAS Visual Analytics be accessed and used on mobile devices?
Yes, SAS Visual Analytics offers native mobile apps for iOS and Android. These apps allow users to view and interact with dynamic reports and dashboards on tablets and smartphones, making it convenient for E-Commerce professionals to access and analyze data on the go.Q: How does SAS support data governance and model management in AI-driven analytics?
SAS Viya, the flagship platform, includes features for data governance and model management. The SAS Model Manager is a dedicated ModelOps facility for AI and ML model governance and management. It helps users to quickly locate, classify, catalog, and secure data, and it tracks and monitors models to ensure compliance and reliability.Q: Can developers integrate third-party libraries with SAS Visual Analytics?
Yes, developers can add creative visualizations using third-party JavaScript libraries such as D3 and C3. SAS Visual Analytics supports open integration, allowing developers to leverage open source development resources and REST APIs to access SAS analytics, data, and services.Q: What languages are supported by SAS Visual Analytics?
SAS Visual Analytics supports a wide range of languages, including English, Spanish, French, German, Italian, and many others. This makes it accessible to users from various regions and helps in global E-Commerce operations.Q: How does SAS Visual Analytics facilitate data storytelling and embedding insights?
SAS Visual Analytics allows users to embed individual visual insights from reports, build interactive stories, or embed entire interactive reports or pages into custom web applications. This helps in publishing insights that scale with the flexibility of live data or embedded data snapshots, enhancing data storytelling in E-Commerce.Q: Is SAS Visual Analytics cloud-native and cloud-agnostic?
Yes, SAS Viya, the platform on which SAS Visual Analytics operates, is cloud-native and cloud-agnostic. This means users can consume SAS services in a manner that suits them, whether it is SAS-managed or self-managed, and on the cloud platform of their choice. SAS Analytics - Conclusion and Recommendation
Final Assessment of SAS Analytics in E-Commerce
SAS Analytics, particularly through its SAS Viya platform, offers a comprehensive and powerful suite of tools that can significantly benefit e-commerce businesses. Here’s a detailed assessment of who would benefit most from using SAS Analytics and an overall recommendation.
Key Benefits for E-Commerce
- Advanced Data Integration and Analysis: SAS Viya enables rapid data integration, effective model development, and deployment, which is crucial for e-commerce businesses dealing with large and complex data sets. This platform can transform raw data into trustworthy insights much faster than other platforms, which is a significant advantage.
- Predictive and Prescriptive Analytics: SAS Viya incorporates advanced predictive analytics capabilities, allowing e-commerce businesses to forecast future trends and behaviors based on historical data. This helps in making data-driven decisions about inventory management, pricing strategies, and product development.
- Improved Customer Insights: The platform provides tools for data exploration and reporting that can help e-commerce businesses understand customer behavior, preferences, and purchasing patterns. This can lead to personalized product recommendations, targeted marketing campaigns, and improved customer retention.
- Efficient Inventory Management: By analyzing data on past sales and customer demand, SAS Viya can help e-commerce businesses optimize their inventory levels, reducing the risk of stockouts and overstocking. This leads to significant cost savings and improved efficiency.
- Enhanced Security: SAS Analytics can also help in detecting fraudulent activity and preventing chargebacks by analyzing customer behavior and transactions, thereby increasing security and trust for customers.
Who Would Benefit Most
- Large E-Commerce Enterprises: Businesses with complex data needs and large volumes of data will find SAS Viya particularly beneficial. Its ability to handle large data sets, perform advanced statistical and machine learning tasks, and provide scalable performance makes it an ideal choice for large-scale operations.
- Data-Driven Decision Makers: E-commerce businesses that rely heavily on data-driven decisions will appreciate the advanced analytics and predictive capabilities of SAS Viya. This includes business analysts, data scientists, and MLOps engineers who can leverage the platform’s automation, visualizations, and model optimization features.
- Businesses Focused on Customer Experience: Companies aiming to improve their customer experience through personalized marketing, optimized website design, and streamlined checkout processes can benefit significantly from SAS Viya’s analytics and reporting tools.
Overall Recommendation
SAS Analytics, specifically SAS Viya, is a powerful tool for e-commerce businesses looking to leverage advanced analytics and AI to drive growth and efficiency. While it may be more expensive and less user-friendly compared to some other options, its advanced capabilities and customization options make it a valuable investment for businesses with complex data needs.
For those considering SAS Viya, it is essential to evaluate whether the benefits align with your business goals and budget. If you are looking for a platform that can handle large data sets, provide advanced predictive analytics, and offer significant scalability, then SAS Viya is definitely worth considering. However, smaller e-commerce businesses or those with simpler data needs might find other tools more suitable due to the cost and complexity of SAS Viya.