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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
8.2
Reviews Sentiment
7.1
Number of Reviews
12
Ranking in other categories
Data Science Platforms (6th)
SAS Visual Analytics
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
40
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 12.8%, up 8.4% compared to last year.
SAS Visual Analytics, on the other hand, focuses on Data Visualization, holds 4.2% mindshare, down 6.0% 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

"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."
"The solution is quite stable."
"Data Science Studio's data science model is very useful."
"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 believe the return on investment looks positive."
"Our clients can easily drag and drop components and use them on the spot."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"Great for handling complex data models."
"Visual Analytics is very easy to use. I use Visual Analytics for all the typical use cases except text mining. I used it to analyze data and monitor statistics, not text mining. I also use it for data visualization as well as creating interactive dashboards and infographics."
"The alert generation feature also helps in sending out ad hoc messages to the business users if business thresholds have been crossed."
"The technical support services are good."
"The product is stable, reliable, and scalable."
"It's relatively simple to create basic dashboards and reports."
"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 speed to display charts and react to users' choices is great."
 

Cons

"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"The ability to have charts right from the explorer would be an improvement."
"The license is very expensive."
"Some capabilities are missing compared to Power BI, especially when working with spreadsheet types."
"In Brazil, there are few documents, courses, and other resources for studying and implementing the tool."
"In terms of configuration, I would like to see AI capabilities since many applications are now integrating AI."
"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."
"The reason we haven't rolled it out across the board is due to the fact that the licensing is so expensive."
"SAS Visual Analytics could improve by making it more accessible for users outside the organization."
"There are certain shortcomings in the tool's support services, making it an area where improvements are required."
 

Pricing and Cost Advice

"Pricing is pretty steep. Dataiku is also not that cheap."
"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."
"It's approximately $114,000 US dollars per year."
"The cost of the solution can be expensive. There is an additional cost for users."
"Visual Analytics is expensive for a small company like mine. You also need to deploy it on a server or cloud, so you pay for the license as well as the cost of the cloud or the server that you will deploy on."
"Licensing is simple."
"I work with the tool's free version...The tool's corporate version is very expensive and requires a monthly hire."
"SAS Visual Analytics is expensive, as is the rest of the platform."
"The product is expensive."
"The product is quite expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Educational Organization
12%
Manufacturing Company
9%
Computer Software Company
9%
Financial Services Firm
21%
Government
12%
Computer Software Company
10%
University
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?
I find the pricing of Dataiku quite affordable for our customers, as they are usually large companies. However, it is a pricey solution and I primarily recommend it to bigger companies.
What needs improvement with Dataiku Data Science Studio?
There is room for improvement in terms of allowing for more code-based features. I would love for Dataiku to allow more flexibility with code-based components and provide the possibility to extend ...
What is your primary use case for Dataiku Data Science Studio?
My company sells licenses for both Dataiku and Alteryx, and we have clients who use them. I engage with several companies in telecommunications, retail, and energy to assess how our clients are uti...
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?
In terms of configuration, I would like to see AI capabilities since many applications are now integrating AI. It may be that our current subscription does not include AI-enabled features, but I wo...
 

Comparisons

 

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.
Find out what your peers are saying about Databricks, Knime, Amazon Web Services (AWS) and others in Data Science Platforms. Updated: March 2025.
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