SAS Advanced Analytics Reviews

We piloted SAS AA at my organization to see how well it compares with other free software tools such as RStudio and Anaconda. So far what we saw was very impressive especially with the visual display but was a little out of our price range. It would be useful in analyzing population health metrics combined with financial data.

Mostly suited for OLAP systems where analytics is performed on data, not for OLTP systems.

SAS Advanced Analytics excels with projects that have at least 3 parts. The first part is the ability to address and compare different modeling types. Suppose you are an analyst interested in predicting home prices or whether an individual will reapply for unemployment insurance. There are lots of model types that could work for these two situations. SAS Advanced Analytics makes it easy (although not as easy as SAS Enterprise Miner) to compare the performance of different modeling types, such as comparing support vector machines with random forest models. A second scenario that SAS Advanced Analytics does a good job at is making the analysis reproducible. By showing the lineage of analyses, another analyst is able to follow the work of the previous analyst. This is a huge advantage for individuals working in corporations or governments. The third area SAS Advanced Analytics is useful is in text analytics. The field is huge now, and I haven't come across a software that makes text analytics as easy as SAS Advanced Analytics.

SAS is useful where you have special coding skills available on a team for this language and thus makes it a very useful tool in visual analytics as well as forecasting and data mining. While the software costs are really high, there are tools that are open source which can be useful for medium level tasks.

Well suited for virtually any and all analytical needs for both large and small data needs. Combined with other SAS capabilities (e.g., data cleaning, manipulation and summary, graphics, visual analytics, data mining, and text mining, I have always found it well suited to provide the best solution for all analytical needs

Excellent for analytics of massive amounts of data and highly responsive dashboards. Less suited for traditional table like BI reporting.

SAS Analytics is best for preforming advanced analytics for personal exploration.

Key questions would center around what the user wants to do with SAS. For instance, before asking about SAS capabilities a user must be able to make sure SAS is compatible with their database setup or schema. After assessing the compatibility the user should ask if SAS has the ability to transform or manipulate the necessary data to get it into presentable form. It is really important that SAS demonstrates that it can add value to your data. Finally, after concluding that SAS is the right fit for how an organization wants to represent their data it is vital that the end user understand the limitations with SAS in regards to how their final product can be represented. Because SAS has many different modules and software a company can purchase the end user must find the most compatible package. For instance, if presenting data in Excel is a high priority the end user must be required to have the SAS MS Office Add-in that allows direct access to all of Microsoft's Office products. WIthout this, the end user may be limited in how they will be able to present information.

While SAS is great at what it does, the price is too high. The high cost issue is even worse if you want to do anything outside of the basic package. It's extra to link directly into databases, it's extra to get the module that allows you to do time series, etc. We were even charged a huge fee because we had one resource who lived in Canada. He was accessing the same US based server as everyone else on the team, the charge was solely because he was outside the US. Given the other options that are out there, it's increasingly difficult to justify such a high price point and antiquated pricing model.

SAS Advance Analytics is well suited for data that is visual. Data where you want to see multiple graphs and models are good for this software. However, if your data is more descriptive this may not be the best program. SAS is well suited for data where you need to make comparisons on the feasibility of two different programs. Data that can be compared is perfect for this software.

I will opt for ease of using it. SAS Enterprise Miner enables any individual to become proficient in advanced analytics.

SAS is well suited for a large company that analyses data every day and shares it with their users. For a small company, SAS Analytics maybe redundant and expensive.

It depends on how much knowledge my colleague has on data analytics and how much time he/she can devote himself/herself to learning a new software. If he/she is relatively new to data analysis and cannot spend a long time learning SAS coding. I would recommend him/her to use SPSS which has a very simple point and click interface. If he/she has data warehousing/SQL experience before and wants to dig deep into data, he/she probably is a good starter to learn data mining through SAS.