91制片厂

What differentiates SAS Data Quality from other similar products?

The most challenging step in any analytics project is gathering data and transforming it so that it is business-ready. Sas data quality assisted us in profiling data, previewing and standardising it, and monitoring it in order to avoid data issues throughout the analytics phase.

What is your favorite aspect of this product?

I enjoy how the interface modifications allow users to perform more on one screen in a more effective manner. Viya handles tabs better than desktop SAS, and it's convenient that datasets don't need to be closed to be changed. There have also been other enhancements to the quality of life. You can save commonly used routines in snippets and transmit outputs in a number of formats and methods. These features were missing from the desktop version and help to modernise the SAS experience.

What do you dislike most about this product?

I didn't perceive any disadvantages to utilising SAS Viya, but I would prefer it if the software's creators made it available to a wider audience. I've been using SAS software for over 7 years, and they were the first to build such enterprise-level statistical analysis applications. However, when I changed professions in the same field, I noticed that few organisations were adopting SAS programmes.

What recommendations would you give to someone considering this product?

SAS allows me to finish all of my analyses in a reasonable period of time and in an organised manner without having to spend a lot of money on software. I appreciate how useful it is for mixture modelling.

What differentiates SAS Data Quality from other similar products?

SAS Data Quality differentiates itself through deep integration with the broader SAS ecosystem, offering advanced analytics, robust data governance, and industry-specific capabilities. It's built for enterprise-scale performance, supporting comprehensive data profiling, cleansing, matching, and monitoring across hybrid and cloud environments. This makes it a strong choice for organizations that need reliable, scalable, and intelligent data quality solutions.

What is your favorite aspect of this product?

My favorite aspect of SAS Data Quality is its seamless integration with advanced analytics and the broader SAS platform. This allows users not only to clean and manage data but also to directly leverage that improved data for powerful analytics, reporting, and AI-driven insights鈥攁ll within a unified environment. It turns data quality from a back-office task into a strategic enabler.

What do you dislike most about this product?

What鈥檚 most commonly criticized about SAS Data Quality is its **complexity and steep learning curve**, especially for new users or organizations without existing SAS expertise. Its powerful capabilities often require significant setup, customization, and training, which can slow down adoption and increase dependency on skilled resources. Additionally, licensing costs can be high compared to more lightweight or open-source alternatives.

What recommendations would you give to someone considering this product?

If you're considering SAS Data Quality, here are key recommendations: Assess your organization's SAS maturity: It's best suited for teams already using SAS tools or planning to invest in the broader SAS ecosystem. Plan for training and support: Due to its complexity, allocate time and budget for staff training or consider engaging SAS consultants. Start with a clear use case: Focus on a specific, high-impact data quality issue (e.g., customer de-duplication or address standardization) to demonstrate value early. Evaluate scalability needs

What differentiates SAS Data Quality from other similar products?

SAS Data Quality differentiates itself with its comprehensive data profiling, cleansing, and governance capabilities, backed by advanced analytics to ensure data accuracy and consistency.

What is your favorite aspect of this product?

SAS Data Quality's strong data cleansing and profiling capabilities, which guarantee excellent data accuracy and integrity, are my favorite feature.

What do you dislike most about this product?

Complex interface and steep learning curve.

What recommendations would you give to someone considering this product?

I recommend this product because of its strong data profiling and cleansing capabilities, I suggest SAS Data Quality; nevertheless, be ready for a challenging learning curve and an intricate UI.