Dataiku vs. Hex.tech

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

Hex.tech is an excellent tool for a product intelligence or product analytics team that wants to enable widespread use of available data for decision-making. It requires some SQL experience in many cases but makes it possible to go far without complex querying skills.

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

• Powerful interactive notebook environment
• Balances the need of code and non-code users
• Provides free and easy sharing to viewers of analyses across the company
• Responds promptly to support requests and needs
• High quality native charting capabilities

Incentivized

• End product deployment.

Incentivized

• Limited support for R notebooks
• Limited sharing outside of the app (e.g., no slack integration)
• Some Python knowledge needed for highest levels of aggregations

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

Hex.tech is the easiest to use, most enjoyable experience, most powerful environment, and most cost scalable of all the above.

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

• Increased visibility into analyses with free membership tier across company
• Increased capacity for self-service analytics among R&D stakeholders (e.g., product managers)
• Improved productivity of data science team with ease of use

Incentivized