Pecan.ai vs. SAS Enterprise Guide

Pecan is something that few know and that I feel can represent a great utility for an entire company, to focus and prioritize all its products and services in favor of the right path, avoiding making mistakes and jumping directly to the solution of future problems before they happen. Pecan will allow you to always be one step ahead and improve your trading system quickly.

Incentivized

For writing out longer code creation for shaping data on complicated reports, the clean UI is helpful. If exploring data though, SAS Studio would be better suited given its easier interface for GUI graph building.

Incentivized

• One of the main important characteristics is its ease of use and the intuitive nature of the platform. It is possible to carry out analyzes quickly and efficiently without requiring user experience. This positive point really gives us what we need for our work: optimization and automation.
• The creation of reports and statistics allows us to fully visualize the analysis carried out, in order to develop our work and carry out the pertinent actions.
• Segmentation allows us to prioritize potential customers, more focused marketing campaigns, highlight our services with what our public is really interested in.

Incentivized

• It can load a huge amount of data as compared to R Studio and Excel.
• Data processing speed is very fast, millions of records are loaded into this software very easily and data manipulation is also very easy.
• Inbuilt Statistical functions and procedures make it very comfortable to use for non analytics professionals as well.

• I would like to see advance interactions with external databases to be able to kill ongoing queries from SAS. As of now, you can stop pretty much any ongoing process besides the one running on a remote database (killing SAS/EG doesn't stop the remote process)
• When creating prompts for programs, it would be nice to be able to have conditional prompts (based on the selection of other prompts). The prompts are clearly a recent feature and constantly under development but I wish it would be more powerful.
• More of a SAS metadata issue but when loading SAS/EG (first connection to the server), it takes a few seconds which feels like a long time. I really don't understand why the initialization of the session can take so long. Don't get me wrong, this has no real impact on productivity but that 10s delay just feels really like eternity when you want to run some code in a new session.

On account of current user experience and the organization-wide acceptance.

It's not all bad, but I don't believe that an enterprise purchase of SAS is worth the expense considering the widely available set of tools in the data analytics space at the moment. In my company, it's a good tool because others use it. Otherwise, I wouldn't purchase a new set of it because it doesn't have some of the better analytical functions in it.

Incentivized

Although I use SAS support for information on functions, these are SAS related and haven't really come across anything that is specifically for SAS EG.

Incentivized

I've not worked hands-on with the implementation team, but there were no escalations barring a few hiccups in the deployment due to change in requirement & adoption to our company's remote servers.

I particularly believe that CrossEngage has some features that Pecan does not offer, such as A/B Testing, however, we were looking for a good predictor and analyst and the truth is that Pecan does its job very well.

Incentivized

Python-based platforms like Pandas or Spark are very good too at displaying data and do exploratory analysis. I definitely prefer them to SAS EG. It's just too slow, and doesn't let you peek into the data very easily. Lots of clicking, and I'd rather just write some code, rather do clicking.

Incentivized

• Faster decision making, through powerful big data handling functionalities.
• Faster operations on daily basis, once the project tree is built, unskilled personnel can use it in their daily operation.
• Don’t need to choose SAS EG if you are not going to be handling big data. (such as over 1 million rows and 50 columns)
• You need skilled personnel to build the initial project tree.

Incentivized