

Alteryx and SAS Data Management compete in the data management tools category. Alteryx appears to have an upper hand with its user-friendly interface and flexibility, making it accessible for non-technical users, whereas SAS is favored for its robust features in data governance and standardization, suiting complex enterprise needs.
Features: Alteryx is equipped with data blending, geospatial analytics, and machine learning tools that enhance automation and data analysis precision. SAS Data Management is recognized for its data governance features, data standardization, and transformation capabilities, ensuring data integrity and quality across enterprises.
Room for Improvement: Alteryx needs to expand its database connectors and improve its visualization capabilities and scheduling features. SAS Data Management should enhance its integration with external applications and simplify data sharing processes to improve user experience and efficiency.
Ease of Deployment and Customer Service: Alteryx offers flexible deployment options including on-premises, cloud, and hybrid setups, which cater to diverse infrastructure needs. SAS Data Management primarily operates on-premises, posing a limitation in flexibility. Alteryx benefits from an active community for user support, while SAS is noted for comprehensive documentation and reliable service.
Pricing and ROI: Alteryx is often costly for small to medium-sized businesses, but it is considered cost-effective due to reduced development time and increased productivity. SAS Data Management is also seen as expensive but offers a strong ROI with its extensive features, valuable in large and complex data environments. Both tools provide significant business value but aren't typically budget-friendly, with detailed pricing information not explicitly provided.
Tasks that earlier took hours in Excel or SQL are now completed in minutes.
From a time-saving perspective, we saved 60 to 75 percent of the human workforce needed and eliminated other disparate ETL tools, ultimately saving us over 600,000 dollars.
Alteryx helps familiarize managers with artificial intelligence-driven possibilities.
Reliable data plus less human intervention and less error result in a strong return on investment.
Customer support from Alteryx has been amazing.
they do have a website for resolving doubts and accessing helpful resources, including various tools and filters.
I contacted customer support once or twice, and they were quick to respond.
The support for SAS in Brazil is not the best one, but the support in Sweden is really good, as they visit the company and work to solve the issues.
Alteryx is scalable for most enterprise analytics and data preparation workloads.
Suggestions for improvements in Alteryx include areas for increasing efficiency, particularly in processing telemetry data, which involves dealing with large volumes of unstructured data.
Alteryx is scalable, and I would give it eight out of ten.
I didn't need to reach out to Alteryx for support because available documents usually provide enough information to resolve issues.
I have not encountered any lagging, crashing, or instability in the system during these three months of usage.
Alteryx is a reliable tool, but it is also very heavy, requiring good laptop configurations, a minimum of 8GB RAM, and a recent processor such as i10.
The tool could include more native connectors, such as for global ERPs, instead of requiring additional fees for these connections.
The support structure changed; initially, we received great support, however, it later became less reliable due to licensing issues and a tiered support system.
The additional features that Alteryx needs to work on to make it more competitive include better collaboration and easier integration through API.
There is significant room for improvement, especially with regard to using a hybrid approach that involves both CAS and persistent storage.
SAS Data Management can be improved in terms of the learning curve.
The price is very high, with licensing typically starting around five thousand dollars plus user per year.
We found excellent use cases for automation through Alteryx, which provided the means to reduce operational costs and streamline the build of ETL pipelines without extensive coding.
Alteryx is more cost-effective compared to Informatica licenses, offering savings.
From my experience, SAS Data Management is an expensive tool.
Alteryx not only represents data but also supports decision-making by suggesting the next steps.
Analysts who do not have any coding experience can still work on the transformation and preparation of data, which is quite useful.
Alteryx includes built-in tools such as drive time analysis and linear regression, which are much harder to achieve in standard BI tools such as Power BI or Tableau.
SAS Data Management stands out because of its data standardization, transformation, and verification capabilities.
The best features I appreciate about SAS Data Management tool are that it's easy to create the flows and schedule data, and the tables are not too big, making it easy to control the ETL process, including user access which is also easy to manage in SAS.
SAS Data Management's best feature is first, data reliability because SAS Data Management is a very trusted platform.
| Product | Mindshare (%) |
|---|---|
| Alteryx One | 1.2% |
| SAS Data Management | 1.2% |
| Other | 97.6% |


| Company Size | Count |
|---|---|
| Small Business | 46 |
| Midsize Enterprise | 20 |
| Large Enterprise | 73 |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 2 |
| Large Enterprise | 8 |
Alteryx enhances efficiency by automating data preparation and transformation through a user-friendly drag-and-drop interface, catering to non-technical users and business professionals. It supports data blending, predictive analytics, and diverse data integration capabilities.
Alteryx streamlines data manipulation and complex transformations, benefiting industries such as finance and marketing with its ability to connect to multiple data sources and automate workflows. The platform supports analytics and machine learning model building, reducing manual efforts in ETL processes. Despite its capabilities, improvements are needed in database connectivity, pricing flexibility, and cloud service integration. Users desire enhancements in reporting features, visualization, and technical support to optimize its full potential. Machine learning and predictive analytics features require advancements to improve user experience and broaden accessibility through better connectors and reduced licensing costs.
What are Alteryx's key features?
What benefits and ROI should be looked for in reviews?
In finance and marketing, organizations leverage Alteryx to automate data tasks, connect diverse sources, and generate analytics models and dashboards efficiently. Its no-code approach aids in rapid data preparation, cleansing, and analysis, empowering business users to engage in predictive and prescriptive analytics effectively.
SAS Data Management provides data integration, governance, and robust reporting tools. It connects to diverse data sources, ensuring quality management and enabling data analysis for technical and non-technical users.
SAS Data Management features flexible data flow creation, scheduling, and ETL control. It enhances data integration and metadata management with tools that support data standardization. Users benefit from its importing and exporting capabilities, connecting to multiple sources. It facilitates improved data quality management and offers a flexible language for diverse needs. Data visualization capabilities further support decision-making across industries, automating reports and data warehouses.
What are the key features of SAS Data Management?SAS Data Management helps industries like finance integrate diverse data sources for analytics and reporting. It is used for tasks such as financial reporting, credit risk analysis, and data cleansing. Through user-driven automation, it aids in aligning data warehouses and generating insightful visual outputs, making it ideal for analyzing structured data from sources like Excel and CSV files.
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