The Dataiku platform unifies all data work, from analytics to Generative AI. It can modernize enterprise analytics and accelerate time to insights with visual, cloud-based tooling for data preparation, visualization, and workflow automation.
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SAS Visual Analytics
Score 7.7 out of 10
Enterprise companies (1,001+ employees)
SAS Visual Analytics provides a complete platform for analytics visualization, enabling users to identify patterns and relationships in data that weren't initially evident. Interactive, self-service BI and reporting capabilities are combined with out-of-the-box advanced analytics so everyone can discover insights from any size and type of data, including text.
$0
Annual By Users: 5, 10, 20
Pricing
Dataiku
SAS Visual Analytics
Editions & Modules
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Business
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Enterprise
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SAS Visual Analytics for SAS Cloud
Annual By Users: 5, 10, 20
Offerings
Pricing Offerings
Dataiku
SAS Visual Analytics
Free Trial
Yes
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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SAS Visual Statistics and SAS Office Analytics are also available as add-ons.
Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.
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.
Provides the flexibility to the end user to slice and dice the data.
Anyone can make predictive models with the help of in-built algorithms without the need to write a single line of code or knowledge of what's under the hood of algorithms.
The feature to simply ask a question related to data and getting a response in form of text, chart or graph is amazing.
SAS is relatively expensive when compared to other BI tools and requires a large amount of upfront fee which becomes an issue for smaller organizations.
UI for the dashboards looks a little date in comparison to competitors like Tableau and Microstrategy.
Integration with other open source software like Python needs to be built in.
SAS really is the cutting edge in Business Intelligence. That is all they do! They are constantly coming out with new products, product upgrades, and their tech support is second to none. In addition, their support of Education has made our ability to acquire their product possible.
As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.
SAS BI is good for creating reports and dashboards and then sharing it with the users. It also has ability to manage access to the reports and dashboards but somehow with most of the world moving to open source languages R, Python and Julia, SAS BI feels to be archaic in terms of feature set and integrations it allow[s]. Also, comparing it with other Business Intelligence tools like Tableau and Microsoft BI, the functionality of SAS BI is very limited and doesn't justify the pricing.
The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.
When you call tech support, you are immediately routed to a person who can answer your question. Often they can answer on the spot. However, if they cannot, you are given a track number and then followed up with. There have been times when I have had multiple track numbers open and they will actually TRACK YOU DOWN to ensure that your problem has been resolved. Issues do not fall into black holes with SAS. They are also willing to do a WebEx with you to diagnose the problem by seeing your environment, which is always helpful.
Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.
I have used Crystal Reports, Jaspersoft and SQL Server Reporting Services (SSRS). I would recommended Business Intelligence over SSRS and Crystal Reports. SSRS is very SQL-centric and Crystal Reports is more of an end-user tool. I would recommend Jaspersoft over Business Intelligence for developing a seamless web-based reporting interface but I highly recommend Business Intelligence for end-user ad-hoc reporting.