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.
N/A
Savant Labs
Score 4.8 out of 10
Enterprise companies (1,001+ employees)
Savant Labs (savantlabs.io) provides an Agentic Workflow Orchestration and analytics automation platform that automates complex data pipelines across enterprise finance, accounting, tax, and operational operations. Built as a no-code, governed data engine, the platform replaces manual spreadsheet processing, email chains, and legacy analytics scripting with repeatable, auditable workflows that process both structured ERP data and unstructured documents. Key…
$3,000
per year number of runs
Pricing
Dataiku
Savant Labs
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Pro
$3,000
per year number of runs
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Pricing Offerings
Dataiku
Savant Labs
Free Trial
Yes
Yes
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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Savant pricing is based on consumption - not per user or per seat, which can quickly become cost-prohibitive.
With unlimited users, everybody across your organization can use Savant tools.
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Community Pulse
Dataiku
Savant Labs
Considered Both Products
Dataiku
Verified User
Anonymous
Chose Dataiku
Dataiku was selected for me, but I am happy about that. I like Dataiku for the user experience, it feels less code-y and I like to demo things to non technical stakeholders because they can still follow along. When you open some other notebooks, you can see that peoples eyes …
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 …
Open source availability is a critical factor given licensing cost of other platforms and budget reasons. Secondly, the available features in the community version covers most of the use cases, thus making it comparable or even outdo commercial versions of other software. …
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 …
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.
if you need to automate reports pulling information directly from your data source Savant is the tool you need, it's very simple, easy to set up and also it's very reliable, we've never had a time where the service is down and that's something worth mentioning because making something easy to use and reliable is not easy.
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
Because it has made things much easier for us, sometimes the stake holders need the data in a certain way in a certain time and with Savant that's not a problem anymore, in fact we are able to customize a little bit more the emails and not send any if there is nothing to report on which is great.
The amazing part of Dataiku DSS is their customer service. Based on urgency and technical level, you get a reply from the Dataiku engineer when you raise a query. So far, my queries have been pretty complex to solve, so I have received solutions even from the CTO of the company as well, which is why I would describe their customer support as very good.
Dataiku was selected for me, but I am happy about that. I like Dataiku for the user experience, it feels less code-y and I like to demo things to non technical stakeholders because they can still follow along. When you open some other notebooks, you can see that peoples eyes start to glaze over