Altair SLC vs. SAS Visual Analytics

For now coders, I would emphasize them to use drag and drop functionality. Otherwise, WPS Analytics is a robust tool for app development and data visualization that offers multiple languages such as SAS, SQL, R, and Python.

Incentivized

SAS Business Intelligence is more suited to organizations which are already using SAS as the primary software for their analytics needs. Learning curve is relatively shorter for teams already skilled in BASE SAS. For organizations already working with open source software like Julia and Python, it doesn't make much sense to use SAS BI.

Incentivized

• Data preparation and advanced analytics help us to gain insights on company data.
• Data sharing and distributing securely.
• Visualization of data with WPS Analytics saves time when making business decisions.

Incentivized

• SAS BI makes it very easy to create interactive dashboards even for someone who is not from an IT background. For some specific requirements, basic knowledge of SQL is good enough.
• A lot of functions have been predefined which makes it very convenient to create dashboards and reports. One doesn't need to be from an IT or a programming background to understand and create dashboards.
• It supports other programming languages like R and also has a seamless API integration with various data management platforms.

Incentivized

• SAS functionality has to lack.
• There's no online guideline, making it hard to solve problems.

Incentivized

• Business Objects should provide a more consistent mobile/desktop interface so operation between the two is seamless
• Business Objects needs to make it easier to query across disparate data sets such as Oracle to SQL to Mongo DB
• Our installation of Business Objects does not natively allow the export of XLSX documents, only XLS

Incentivized

There is no other product that can match SAS. There are some products that can compare to ETL but lack the analytics that SAS has. Others can perform a limited set of analytical procedures but lack the data processing that comes with SAS. Using thin client allows users to access data whenever they have an internet connection.

SAS BI is good for creating reports and dashboards and then sharing it with the users. It also has ability to manage access to the reports and dashboards but somehow with most of the world moving to open source languages R, Python and Julia, SAS BI feels to be archaic in terms of feature set and integrations it allow[s]. Also, comparing it with other Business Intelligence tools like Tableau and Microsoft BI, the functionality of SAS BI is very limited and doesn't justify the pricing.

Incentivized

When you call tech support, you are immediately routed to a person who can answer your question. Often they can answer on the spot. However, if they cannot, you are given a track number and then followed up with. There have been times when I have had multiple track numbers open and they will actually TRACK YOU DOWN to ensure that your problem has been resolved. Issues do not fall into black holes with SAS. They are also willing to do a WebEx with you to diagnose the problem by seeing your environment, which is always helpful.

To better understand the data I work with, I extensively use the data discovery and visualization tools available on my workstations, and I always go for the best. Unfortunately, some other tools does not offer any tutorials for the features, making it difficult and time-consuming to analyze data, mainly after it has been implemented. In addition to videos and articles, WPS Analytics provides comprehensive tutorials for each feature.

Incentivized

I have chosen SAS Visual Analytics because one of my colleagues suggests using the software for the same for our work. As earlier, we use to take a lot of time in analyzing the data but after using the SAS Visual Analytics software our work has improved and time has decreased. It's very helpful for us.

Incentivized

• Reduction in operational costs since no data scientists are involved.
• Time and effort have been reduced when analyzing data by using machine learning capabilities and natural language.
• We have reduced time to value by bridging data processing to taking actions gap.

Incentivized

• SAS Visual Analytics licensing cost should be reduced to enable users to use it in mass scale.
• More statistical and mathematical equations and theories should be converted into SAS functions for reusing.
• Because of enriched ETL and reporting capabilities SAS Visual Analytics is most preferred by business users.

Incentivized