Dataiku vs. Datameer

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.

Incentivized

Datameer's workbooks include an intuitive GUI for maximum usability. Anyone with an analytical mind may easily compile data using the built-in worksheet capability without requiring much technological knowledge. Ad hoc reports may now be made and scheduled. In addition, I haven't had too much problem fixing things because I can get most of the answers I want there.

Incentivized

• Low-code platform.
• Open source version includes most valuable modules.
• User friendly documentation.

Incentivized

• It leverages scalability, flexibility and cost-effectiveness of hadoop to deliver an end-user focused analytic platform for big data without involvement of IT.
• It overcomes Hadoop`s complexity by providing GUI interface with pre-built functions across integration, analytics and data visualization .
• Excel feature is awesome for business users which is already provided by Datameer.
• Using datameer now user can do smart analytic using Decision Trees, Column dependency and recommendation.
• Recently HTML5 inclusion is making application to available on a wider range of devices, including the iPad and other mobile devices which does not support Flash.
• It can be used in premise or in a cloud computing environment.
• Wizard-based data integration designed for IT and business users to schedule and do transformation of large sets of structured, semi-structured and unstructured data without any knowledge of Hadoop ecosystem.

• The visualization feature of flow still has a lot room to improve, when the flow is complex.
• The "non-coding" template/building block for deep learning lack of many important configurable parameters.
• Lack of the unified way to allow applying the "design pattern" on the Python codes (if we want to develop our own module or building blocks.

Incentivized

• Data visualization and graphics. Right now it's not very user friendly. Creating dashboards requires a lot of work that can be done by the application

Incentivized

Employees with intermediate SQL and Hive knowledge can generate reports faster than using Datameer . It does have visualization tool but I don't think it is anything that cannot be accomplished by importing the data in Excel

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

Incentivized

Easy to use for most things, starts to require some planning as your projects get more complex.

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.

Incentivized

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

Incentivized

I have compared Datameer with the tools listed above and it blows them out of the water. Datameer is much more user friendly than these tools and is also a lot more powerful. Once the Q1 release comes out with drill down capabilities on the infographics, Datameer will surpass Tableau and Spotfire in visualization.

• So far it has had a positive impact. Multiple departments are coming to us with their business problems.
• I can't specifically say about ROI as I'm a developer, though I have heard this solution is economical compared to other AI/ML enterprise tools.
• By using this tool, my client has let go of software that was used earlier, and we have created a simpler framework to replace that software.

Incentivized

• Quick time to value. Transition from developer to learning Datameer is less than a day.
• Workspace is drag and drop, which makes it intuitive and easy to use.
• Speed of data transformations.
• Pulling data from various sources.
• Easy to schedule data pipelines.
• Tailor made for Snowflake and Redshift.
• Documentation is sometimes not updated quickly.
• Training videos are a bit long.