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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Google Assistant for Developers
Score 8.5 out of 10
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Users can build custom conversational experiences using Google Assistant’s voice and visual APIs. Take users on journeys through a product, using Assistant’s natural language understanding (NLU) capabilities and developer tools.
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Pricing
Dataiku
Google Assistant for Developers
Editions & Modules
Discover
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Enterprise
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Offerings
Pricing Offerings
Dataiku
Google Assistant for Developers
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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More Pricing Information
Community Pulse
Dataiku
Google Assistant for Developers
Features
Dataiku
Google Assistant for Developers
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Dataiku
8.6
5 Ratings
3% above category average
Google Assistant for Developers
-
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
17% above category average
Google Assistant for Developers
-
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
15% above category average
Google Assistant for Developers
-
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
Google Assistant for Developers
-
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 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.
I'm in a Me vs. The World environment rather often. I can connect to my outer realm when heading to live meetings. Auditions, job assignments all via my assistant. I like having the ability to capture the moment and rewrite it as well. This is a primary driver for me. Sometimes branching out or when collaborating, I think I work a little harder in the moment than Google Assistant might but that is moreso my limitations and not the feature so much. I catch this scene when I'm in a group environment or at times having to create and respond to a larger scale event. Not a deal breaker for me however.
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 think newer, complementary ideas are a bit sharper than Google Assistant especially in a Q&A environment or when seeking some depth to a subject. That enhancement is to be expected I feel. And Google Assistant is not so self limiting so I don't have a lot of improvement needs because I use this for what I've become accustomed to and for the ability overall.
It is always important to do your best around hectic places, in bad tower signal areas or even if trying to do something new while using Google Assistant. Have patience in the setting. It pays off.
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
I feel this can be adjusted and after some trial and error you sort of start knowing what will work and how. And I have to say the overall impact becomes personal and we are all different. I'm small scale and as I've said, it works.
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.
I chose this because it was easier for me and can be accessed via mobile and laptop too because it enables cross device support because it helps in adding more depth to my life, and can help me save tons of time.