Dataiku vs. Roambi (discontinued)

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

I would recommend Roambi for its ease-of-use and quick deployment. It is very visually rich and eye-catching, and I believe it is best suited for presenting business & finance dashboard to C-level management and sales representatives in the field. Because it can be accessed on the iPhone or iPad, it is very mobile and the Apple touch interfaces are nearly flawless. If an organization needs to really dig deep into their data, I would look elsewhere, as Roambi has certain limitations.

• 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

• Very intuitive user interface that exploits the touch capabilities of tablets and smartphones very well.
• Offline capability - extremely helpful for sales people that can not always be online.
• Integration with existing BI solutions - almost all of our clients have already a BI Infrastructure. Roambi integrates very well.

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

Incentivized

• The system that performs the rendering of data to the front-end can be improved to intelligently read the back end data template or at least the layout. Inserting new rows/columns of data completely messes up the rendering on the front end and the process of re-selecting information to ensure proper rendering is a very tedious one.
• Also, Roambi should have the capability to analyse information in formats other than excel such as word, ppts and/or pdfs. I found the lack of this capability a major hurdle because each time I had to export information into excel to render into a template.

The only reason we would not renew is if there is something out there that is less expensive that is cross-platform for mobile devices. Our clients are no longer exclusively using iOS, so in order to keep their business, we need to change with them.

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

VERY easy to use. Only limited by how the graphs and data is initially set up.

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

Comparing the mobile capabilities of both products - as of course, Tibco Spotfire is a complete solution whereas Roambi focuses on mobility. While some would argue that the ten View (template) limitation of Roambi works in favor of competitors, we have found this to be untrue. Users quickly get used to this native interfaces, which are found across the templates. Additionally, the ten available Views cover 99% of the types of reports or insights you'd ever need. If this is not the case, are you sure you are asking the right questions?

• 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

• positive ROI
• and any analytical tool needs more historical data for accurate analysis, in that case, roambi 's part is as a presenter can't influence the ROI exactly..
• overall objective its a value addition for sap based data analytics and others as well.
• for CIO or analytics people good tool to convince their business users and executives.

Incentivized