The Dataiku platform unifies data work from analytics to Generative AI. It supports enterprise analytics with visual, cloud-based tooling for data preparation, visualization, and workflow automation.
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OpenText Magellan
Score 9.0 out of 10
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OpenText Magellan Analytics Suite leverages a comprehensive set of data analytics software to identify patterns, relationships and trends through data visualizations and interactive dashboards.
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Pricing
Dataiku
OpenText Magellan
Editions & Modules
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Offerings
Pricing Offerings
Dataiku
OpenText Magellan
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Community Pulse
Dataiku
OpenText Magellan
Features
Dataiku
OpenText Magellan
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Dataiku
8.6
5 Ratings
3% above category average
OpenText Magellan
-
Ratings
Connect to Multiple Data Sources
8.05 Ratings
00 Ratings
Extend Existing Data Sources
10.04 Ratings
00 Ratings
Automatic Data Format Detection
10.05 Ratings
00 Ratings
MDM Integration
6.52 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Dataiku
10.0
5 Ratings
18% above category average
OpenText Magellan
-
Ratings
Visualization
10.05 Ratings
00 Ratings
Interactive Data Analysis
10.05 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Dataiku
9.5
5 Ratings
16% above category average
OpenText Magellan
-
Ratings
Interactive Data Cleaning and Enrichment
9.05 Ratings
00 Ratings
Data Transformations
9.05 Ratings
00 Ratings
Data Encryption
10.04 Ratings
00 Ratings
Built-in Processors
10.04 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Dataiku
8.5
5 Ratings
1% above category average
OpenText Magellan
-
Ratings
Multiple Model Development Languages and Tools
8.05 Ratings
00 Ratings
Automated Machine Learning
8.05 Ratings
00 Ratings
Single platform for multiple model development
8.05 Ratings
00 Ratings
Self-Service Model Delivery
10.04 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Dataiku
8.0
5 Ratings
6% below category average
OpenText Magellan
-
Ratings
Flexible Model Publishing Options
8.05 Ratings
00 Ratings
Security, Governance, and Cost Controls
8.05 Ratings
00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Dataiku
-
Ratings
OpenText Magellan
7.0
2 Ratings
15% below category average
Customizable dashboards
00 Ratings
7.02 Ratings
Report Formatting Templates
00 Ratings
7.01 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Dataiku
-
Ratings
OpenText Magellan
8.3
3 Ratings
4% above category average
Drill-down analysis
00 Ratings
8.03 Ratings
Formatting capabilities
00 Ratings
8.03 Ratings
Integration with R or other statistical packages
00 Ratings
9.01 Ratings
Report sharing and collaboration
00 Ratings
8.02 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Dataiku
-
Ratings
OpenText Magellan
8.3
2 Ratings
1% above category average
Publish to Web
00 Ratings
8.02 Ratings
Publish to PDF
00 Ratings
8.02 Ratings
Report Versioning
00 Ratings
9.02 Ratings
Report Delivery Scheduling
00 Ratings
8.02 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Dataiku is an awesome tool for data scientists. It really makes our lives easier. It is also really good for non technical users to see and follow along with the process. I do think that people can fall into the trap of using it without any knowledge at all because so much is automated, but I dont think that is the fault of Dataiku.
If you do not have a large budget and are a large organization, I would steer clear of Actuate. If you are looking to do very complex washboarding, I would not use them. Your developers have to be very skilled to work with this. Plan to bring in consultants if necessary to help your process. Adhoc reporting is weak. If your pricing is user based and you expand, this could be very expensive.
The integrated windows of frontend and backend in web applications make it cumbersome for the developer.
When dealing with multiple data flows, it becomes really confusing, though they have introduced a feature (Zones) to cater to this issue.
Bundling, exporting, and importing projects sometimes create issues related to code environment. If the code environment is not available, at least the schema of the flow we should be able to import should be.
I am no longer working for the company that was using Actuate but I believe they would continue to use it because the stitching costs would be to high. It would require a complete rewrite of the reports and the never version of Actuate (BIRT) even required an almost complete report rewrite
The user experience is very good. Everything feels intuitive and "flows" (sorry excuse the pun) so nicely, and the customization level is also appropriate to the tool. Even as a newer data scientist, it felt easy to use and the explanations/tutorials were very good. The documentation is also at a good level
It is quite intuitive to use. It is fit specifically for doing sentiment, emotion, and intention analysis as well as text classification and text summarization. I would have given 10 if it is fit for the purpose of doing image processing and analysis as well. There is a huge market to analyze video and image data.
The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.
Anaconda is mainly used by professional data scientists who have profound knowledge of Python coding, mainly used for building some new algorithm block or some optimization, then the module will be integrated into the Dataiku pipeline/workflow. While Dataiku can be used by even other kinds of users.
It is vastly superior to these in many ways, for complex reporting it is a much more sophisticated solution. Visualizations are very good. Javascript extensibility is very powerful, others don't support this or as well. Pentaho and MS are both OLAP oriented. Pentaho is moving more toward big data, which was not our primary focus. Others are stuck in the Crystal Reports Band metaphor.
Actuate can handle 50 to 60 sub reports inside a report very well.
Dynamically creating the datasource, chart, graph, reports are the main advantages. We can do any level of drilling, and can create a performance matrix dashboard efficiently.