SAS Visual Analytics Reviews and Ratings

Use Cases and Deployment Scope

SAS Visual Analytics is used to keep the data in a presentable way which helps in finding any data in less span of time without wasting time.

The business problem we address is data found at the time when we need but it took too much time to find out accurate data at the moment which is now possible through the SAS Visual Analytics software. It provides accurate data within less span of time in a very systematic way.

Likelihood to Recommend

I was in a meeting with the client and there I have to show them some analytic data to them. But I was confused about how I will manage to show big data to clients with accuracy. But then the SAS Visual Analytics software helps me in presenting accurate data at the moment and it was very presentable and through that, I got the deal for that business.

Use Cases and Deployment Scope

SAS Business Intelligence is mainly used by the analytics teams across organizations in order to create interactive reports and dashboards. The employees are not dependent [on] clunky Excel reports and dashboard[s] anymore and are able to have access to reports, dashboards, and insights on the go with the help of mobile apps. Also, lot of features are inbuilt to do predictive analysis as well instead of just descriptive analysis.

Likelihood to Recommend

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.

Use Cases and Deployment Scope

SAS Business Intelligence provides a valuable and powerful way to allow our end-users to query our data on an ad-hoc basis. Business Intelligence allows us to present the data to our users with pre-defined joins and available data elements assisting the users in designing and executing queries without requiring additional technical assistance. This provides both a cost and time savings to our technical teams.

Likelihood to Recommend

<ul><li>Business Intelligence is excellent for ad-hoc query implementations. We are able to provide connections to numerous data sets through a consistent user interface</li><li>Business Intelligence is amazing for hiding the database implementation from users and presenting ONLY what you wish them to see</li><li>Business Intelligence is less for suited for a seamless integration into a web site as reports are generally presented through the BO report interface</li></ul>

Use Cases and Deployment Scope

I use SAS Visual Analytics to build reports for my coworkers. I build dashboards based on census data and website logs. The dashboards are all interactive and the user can choose themes or subsets. They do not have any software (except Office) for those analyses besides what I provide them and they are all happy with the results.

Likelihood to Recommend

Reporting to users who do not have access to specialized software Dashboards with a lot of interactivity, so users decide by themselves what characteristics they want to see. Integrates very well with other SAS products.

Use Cases and Deployment Scope

SAS Business Intelligence is being used primarily in our Research and Analytics departments to evaluate program changes that we might make going forward. It really is only used by a few departments by company employees who are considered subject matter experts. Other departments use the outputs that we generate to make their business decisions. Another major use is for math intensive tasks.

Likelihood to Recommend

SAS Business Intelligence is well suited for large corporations that have a demand for scalability and reliability to provide insights into the information that is often housed in their large systems.

Use Cases and Deployment Scope

Visual Analytics is being used for attrition analysis; we want to focus on why people leave and where. It's only used in a small department of merchant solutions.

Likelihood to Recommend

If you are a business looking for a visual appealing tool that is easy to use, look no further.

Use Cases and Deployment Scope

SAS BI is being used by Local and Central Analytics teams to generate custom insights for advertisers, vertical level insights and to create various predictive models. SAS BI is used mostly by the Analytics teams. Since we are in AdTech industry, we deal with billions of rows of digital impression data which is mined to make sense using SAS BI. SAS BI directly connects to Vertica (SQL Database) and help us summarize the data and gather some insights on how to optimize the campaigns.

Likelihood to Recommend

SAS BI is a great BI tool as it incorporates the advantage of SAS which is proven to be robust over the years. SAS BI is more suitable for a relatively larger organization which is looking for self-service BI tools where most of the users are not technically proficient. Also, since license fee is an on a higher end, smaller organizations will find it hard to afford SAS.

Use Cases and Deployment Scope

We use SAS Visual Analytics in visualising credit risk data for Regulatory reporting and Analysis. It has been very helpful in finding the gaps in data quality and understanding the data better from a business standpoint.

Likelihood to Recommend

It is well suited for companies which are already in SAS environment and have lot of data in SAS for Analytics. If you don't have any SAS products or expertise, this need not be the first SAS tool you should look at. Explore Tableau, PowerBI and assess based on "fit for purpose."

Use Cases and Deployment Scope

SAS Visual Analytics was used to identify data type, and for filtering data fields as per requirements. For me, it appeared like SPSS combined with R language. This interface is very helpful and made it easy for me to use the software. To get the desired result and output, it is very easy to relate. For regular R users, writing algorithms is very easy and visuals appear side by side.

Likelihood to Recommend

For the industry I was working it, it was very well suited. We conducted regular analytics of the number of orders completed a week. It gave us insight on how we grew week to week. While it was easy to work on quantifiable data, it was difficult to work on qualitative data. One suggestion I would add is that if SAS could provide options that would allow qualitative data to be quantified.

Use Cases and Deployment Scope

It is used by a single department. We use it to better analyze our medical data we receive to look for trends and benchmark area results and improvements. This is a new method for us, and we are still evaluating the need.

Likelihood to Recommend

Its best suited for a staff that already knows how to use it. If they don't, might look for a simpler solution.