Dataiku vs. Displayr

I would recommend it because it's an amazing tool for different levels of users. From Business Analysts to Data Scientists to Managers, various employees can make use of this tool to make data-driven decisions. I'm not sure about where it would be less appropriate as I'm using it as Data Scientist and so far it pretty much caters to my need.

Incentivized

Displayr is perfectly suited for any insights or data people that understand the type of analysis they want to do, but don't know R code - or just want to get to results more quickly than coding themselves. It's probably not the best learning ground, if you've never done any quantitative analysis before, but then neither are traditional tools like SPSS or Q.

Incentivized

• Very intuitive and easy to use UI, making a lot of types of users can collaborate with each other easily, by visualizing the same workflow.
• Many building blocks can be reused immediately, avoid a lot of non-standard boiler plate implementation.
• Data pre-analysis and feature engineering assistance increase the productivity as well as the efficiency of data scientists.
• Many data connectors support wide range of data storage, from SQL, TeraData, Hadoop Hive, etc.
• Support from research till final MaaS solution deployment.

Incentivized

• The intuitive interface and menus make it easy to quickly learn Displayr and find the types of data transformation or analysis that we're looking to do.
• The support level from Displayr's team is FIRST CLASS. Where othe platforms force you to an FAQ or AI chat bot, Displayr's team will jump in first hand, into our data, or on a live call, and help us run a new type of analysis or troubleshoot a problem.
• The ability to work collaboratively, asynchronously and remotely, on the same data set and report is a really huge plus for us.
• The in-built options for multivariate analysis cover 99.9% of anything we have - or will - ever need to run.

Incentivized

• Its community support is very limited at the moment
• Complex to integrate with automation tools such as Blue Prism

Incentivized

• The new "glow-up" on the interface has helped make it a bit easier on the eye, but there are some features of working in the "three pane" browser that are a bit frustrating: especially having to 'rearrange' when resizing the window to look at another app simultaneously.
• Such a small point, but being able to drag and move multiple elements in a table (eg drag two rows to the top) SIMULTANEOUSLY would help a bunch.
• I don't think we take advantage of all the visualisation capabilities in Displayr, and perhaps an AI 'recommendation' engine that sees the data I'm working with and prompts either a specific visualisation, or additional analysis option I might use, would be great.

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

It's really quite intuitive, but the visual interface could be made a bit more easy to use (window/pane rescaling etc) and I think there could be more 'proactive prompts' to suggest features we're underutilising.

Incentivized

The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.

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

SPSS (the last version I looked at) still requires much more underlying knowledge and coding ability to get where we want to be. That's not where we add value, so the speed and simplicity with which Displayr allows us to get the data analysis done, and move onto developing insight and delivering value is why I chose Displayr.

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

• I think Displayr is quite expensive, but has the biggest impact on our P&L of any of our subscriptions, because it has unlocked our ability to deliver bigger, more complex analytic projects for clients - and hence grow our topline.
• The ability to scale the license between years has also been a god-send as our team has gone up or down to deliver the level of quant work available to us.
• There's also a bottom line efficiency driven by some of the speed of analysis that Displayr enables.

Incentivized