Dataiku is a French startup and its product, DSS, is a challenger to market incumbents and features some visual tools to assist in building workflows.
N/A
Tableau Prep
Score 8.5 out of 10
N/A
Tableau Prep enables users to get to the analysis phase faster by helping them quickly combine, shape, and clean their data. According to the vendor, a direct and visual experience helps provide users with a deeper understanding of their data, smart features make data preparation simple, and integration with the Tableau analytical workflow allows for faster speed to insight. Tableau Prep allows users to connect to data on-premises or in the cloud, whether it’s a database or a…
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 your data sets are coming in without much stewardship then Tableau Prep can help to clean the data before you start trying to create visualizations for your end users. You will save a lot of time this way - rather than seeing problems once you are creating dashboards. If you don't have large data sets or your data is relatively simple, then Tableau Prep may not be needed.
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.
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.
I have not really had to reach out for any kind of customer support for Tableau Prep, so I can't really say. However, the support that Tableau has given for their other products has been great, so I would assume it would be the same here. They are also constantly adding new features and providing software updates, and that is always a plus.
Live connections to cloud services (Google Sheets for example) and cloud hosted databases (cloud hosted SIS for example) for scheduled flows are not supported
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.
Before Prep, we had to do all the data joining and connecting in a Tableau Workbook. Not only did this cause workbooks connected with live data to run frustratingly slowly, a new connection and set-up had to be established every time a new workbook as created, even if you were working with the same data. The extracts produced by Prep allow several workbooks to be working from the same data set-up without any additional work, saving time and stress.
