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Dataiku vs TIBCO Data Science comparison

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Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

IBM SPSS Statistics
Sponsored
Ranking in Data Science Platforms
10th
Average Rating
8.0
Number of Reviews
37
Ranking in other categories
Data Mining (3rd)
Dataiku
Ranking in Data Science Platforms
7th
Average Rating
8.0
Number of Reviews
8
Ranking in other categories
No ranking in other categories
TIBCO Data Science
Ranking in Data Science Platforms
25th
Average Rating
7.6
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. The mindshare of Dataiku is 11.5%, up from 7.5% compared to the previous year. The mindshare of TIBCO Data Science is 0.6%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

AbakarAhmat - PeerSpot reviewer
Sep 21, 2023
Enhancing survey analysis that provides valued insightfulness
I use it to analyze questionnaire surveys related to a product, solution, or application, such as open data services, which I provide to consumers and end-users. These surveys contain evaluation assessments, and I use SPSS to analyze the responses The most valuable feature is its robust…
Sabrine Bendimerad - PeerSpot reviewer
Jun 11, 2024
Saves a lot of time because I can quickly handle all the data preparation tasks and concentrate on building my machine learning algorithms
One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated. While it was theoretically possible to use GitHub with Dataiku, in practice, it was difficult to manage our code effectively and push it from Dataiku to GitHub. Another limitation was its ability to handle different types of data. While Dataiku is powerful for working with structured data, like regular or geospatial data, it struggled with more complex data types such as text and image. In addition to the challenges with GitHub integration, the limited support for diverse data types was another feature lacking at that time.
VS
Dec 9, 2019
A straightforward initial setup and good reporting but needs better documentation
It would be ideal if it could be put onto the NMP where you can make more of an analysis. Right now, people don't have enough time to go through the report and make an analysis. It should provide the information of what is on the report into some kind of a dialogue form. Then, a person can ask certain questions and it could interactively give the required report. In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues. If you are doing certain operations of RDBMS, you suffer in terms of the latency of the data. That can be improved upon. Users should be able to cross tables of the web pages they are developing on Spotfire and this needs to be really easy and convenient. Right now, you need to do a lot of tweaks. The solution should be more user-friendly and require fewer tweaks, extensions, and workarounds.

Quotes from Members

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

Pros

"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"The SPSS interface is very accessible and user-friendly. It's really easy to get information in it. I've shared it with experts and beginners, and everyone can navigate it."
"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."
"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."
"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."
"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."
"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."
"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."
"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 most valuable feature is the set of visual data preparation tools."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."
"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."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"We like the way we can drill down into each report to get back data on each project. From the portfolio level, I can see what is happening on it. That is a really important feature. I can look at indirect costs, for example, which are hitting each CIO portfolio. It's good to be able to see actual resources in terms of time as well as cost."
"The idea that you don't have to generate reports each day but they are sent automatically is great."
"The most valuable feature is the ease of setting up visualizations."
"The most valuable feature is the performance."
 

Cons

"The technical support should be improved."
"The statistics should be more self-explanatory with detailed automated reports."
"It could allow adding color to data models to make them easier to interpret."
"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."
"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"Better documentation on how to use macros."
"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"The ability to have charts right from the explorer would be an improvement."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"I think it would help if Data Science Studio added some more features and improved the data model."
"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."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"I would like the visualization for the map of countries to be more easily configurable."
"Additional templates would help to get things moving more quickly in terms of getting the reports out."
"The scripting for customization could be improved."
"In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues."
 

Pricing and Cost Advice

"The price of IBM SPSS Statistics could improve."
"More affordable training for new staff members."
"The price of this solution is a little bit high, which was a problem for my company."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
"It's quite expensive, but they do a special deal for universities."
"I rate the tool's pricing a five out of ten."
"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"We think that IBM SPSS is expensive for this function."
"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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
University
10%
Computer Software Company
9%
Manufacturing Company
8%
Financial Services Firm
18%
Educational Organization
16%
Manufacturing Company
9%
Computer Software Company
8%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about IBM SPSS Statistics?
The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
While the pricing of the product may be higher, the accompanying service and features justify the investment. However...
What needs improvement with IBM SPSS Statistics?
In some cases, the product takes time to load a large dataset. They could improve this particular area.
What needs improvement with Dataiku Data Science Studio?
One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integratin...
What is your primary use case for Dataiku Data Science Studio?
We use the solution for data science and machine learning.
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Also Known As

SPSS Statistics
Dataiku DSS
Alpine Data Chorus
 

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Overview

 

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Havas Media, Tipping Point Community, eviCore
Find out what your peers are saying about Dataiku vs. TIBCO Data Science and other solutions. Updated: October 2024.
814,649 professionals have used our research since 2012.