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Dataiku vs SAS Visual Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Dataiku
Average Rating
8.0
Reviews Sentiment
7.2
Number of Reviews
10
Ranking in other categories
Data Science Platforms (7th)
SAS Visual Analytics
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
39
Ranking in other categories
Data Visualization (7th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Dataiku is designed for Data Science Platforms and holds a mindshare of 12.4%, up 7.9% compared to last year.
SAS Visual Analytics, on the other hand, focuses on Data Visualization, holds 4.7% mindshare, down 6.5% since last year.
Data Science Platforms
Data Visualization
 

Q&A Highlights

HE
Jun 07, 2023
 

Featured Reviews

RichardXu - PeerSpot reviewer
The platform organizes workflows visually and efficiently
One of the valuable features of Dataiku is the workflow capability. It allows us to organize a workflow efficiently. The platform has a visual interface, making it much easier for educated professionals to organize their work. This feature is useful because it simplifies tasks and eliminates the need for a data scientist. If you are knowledgeable about AI, you can directly write using primitive tools like Pantera flow, PyTorch, and Scikit-learn. However, Dataiku makes this process much easier.
Renato Vazamin - PeerSpot reviewer
Single environment for multiple phases saves us time, and has good visualizations
We had that solution installed previously in another solution, Selvaya, but I don't think we used it at the time. We are now using SAS Detect Investigation as a complementary solution, in which we have part of the process, use a gene, SAS collects information and identifies some business situations, and the business guys use Visual Analytics to explore the results of the process. We previously used the FICO platform, but we switched because FICO's pricing was not scalable. Bringing more data or workloads to the platform required a significant investment in order to scale. We needed to change because we have a lot of data to process every day. FICO was also a little more complicated than SAS Visual Analytics.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The most valuable feature is the set of visual data preparation tools."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"Data Science Studio's data science model is very useful."
"The solution is quite stable."
"I believe the return on investment looks positive."
"The advantage is that you can focus on machine learning while having access to what they call 'recipes.' These recipes allow me to preprocess and prepare data without writing any code."
"I rate the overall product as eight out of ten."
"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."
"It's quite easy to learn and to progress with SAS from an end-user perspective."
"It's a stable, reliable product."
"Simplifies report designs and quickly displays tables and graphs."
"Data handling is one of the best features of SAS Visual Analytics."
"The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced technologies such as machine learning and artificial intelligence. This helps with quality assurance processes."
"The visualization capabilities and the email functionality are most beneficial."
"Great for handling complex data models."
"The flexibility of the configuration is valuable to me."
 

Cons

"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"We still encounter some integration issues."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"I think it would help if Data Science Studio added some more features and improved the data model."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"One area for improvement is the need for more capabilities similar to those provided by NVIDIA for parallel machine learning training. We still encounter some integration issues."
"The solution should improve its graphics."
"Some capabilities are missing compared to Power BI, especially when working with spreadsheet types."
"SAS Visual Analytics could improve by making it more accessible for users outside the organization."
"The licensing ends up being more expensive than other options."
"The visualization should be better in SAS Visual Analytics. It is easy to use but when compared to other solutions it is lacking and the support is not very good."
"There are scalability issues. It depends on the data volume and number of end-users. VA requires a lot of hardware resources to move volumes of data."
"The deployment isn't smooth. Deploying Visual Analytics on the cloud takes a lot of work, or you can use some providers that give you SAS as a service. For example, there is a provider called SaasNow. They host SAS Visual Analytics and the license. You can buy the license and deploy it there without the hassle of installation because deploying the software isn't easy."
"Colours used on report objects"
 

Pricing and Cost Advice

"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."
"Pricing is pretty steep. Dataiku is also not that cheap."
"Licensing is simple."
"It's approximately $114,000 US dollars per year."
"The cost of the solution can be expensive. There is an additional cost for users."
"SAS Visual Analytics is expensive, as is the rest of the platform."
"The product is quite expensive."
"I work with the tool's free version...The tool's corporate version is very expensive and requires a monthly hire."
"$10,000 per annum for an enterprise license."
"The product is expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Educational Organization
15%
Manufacturing Company
9%
Computer Software Company
8%
Financial Services Firm
20%
Government
13%
Computer Software Company
10%
University
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What needs improvement with Dataiku Data Science Studio?
I need more experience in the sector, which is health. The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience.
What is your primary use case for Dataiku Data Science Studio?
I use that IQ since I am preparing cohorts for health investment research.
What do you like most about SAS Visual Analytics?
The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced technologies such as machine learning and artificial intelligence. This helps w...
What is your experience regarding pricing and costs for SAS Visual Analytics?
It's about an average of five. It's easy to scale, but it comes with cost.
What needs improvement with SAS Visual Analytics?
Some capabilities are missing compared to Power BI, especially when working with spreadsheet types. Furthermore, Excel is more customizable compared to SAS Visual Analytics, which can be quite rigi...
 

Also Known As

Dataiku DSS
SAS BI
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Staples, Ausgrid, Scotiabank, the Australian Institute of Health and Welfare, the Blue Cross and Blue Shield of North Carolina, Oklahoma Gas & Electric, Xcel Energy, and Triad Analytics Solutions.
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