Dataiku vs. Oracle Machine Learning

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

OAC doesn't require software to be installed since it is browser based. This allows for easier deployment since a local client software is not required to be installed for each user. OAC can be used for the casual light user who mainly consumes data to the power user who can created sophisticated dashboard with advanced analytics. OAC is not meant to replace Essbase reporting.

Incentivized

• The intuitiveness of this tool is very good.
• Click or Code - If you are a coder, you can code. If you are a manager, you can wrangle with data with visuals
• The way you can control things, the set of APIs gives a lot of flexibility to a developer.

Incentivized

• Analyzing heaps of data dumped into the machine learning tool.
• Giving the researcher an insight on which direction to proceed in order to get the desired results.
• Can help perform a functional analysis before doing a deep dive.

Incentivized

• End product deployment.

Incentivized

• As mentioned by others the formatting of reports constantly has issues
• Once your initial contract terms are up be prepared for a significant increase
• Pricing needs to be inline with what other competitors are offering

Incentivized

As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.

Incentivized

The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.

Incentivized

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 flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.

Incentivized

Sorry this product was not selected by me, but was a legacy install that was upgraded. I see the value in the product, however, I was not involved in the selection process.

Incentivized

• Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration.
• Platform also ease tracking of data processing workflow, unlike Excel.
• Build-in data visualizations covers many use cases with minimal customization; time saver.

Incentivized

• Our ROI has been great since we have been able to get a birdseye view of our business operations.
• Shows your areas within your company that needs attention and improvements.
• Oracle has had a positive impact on all of our business objectives since it provides a clear view of your business operations.

Incentivized