Chartio (discontinued) vs. Dataiku

This product is well suited for end users that don't want to get too in depth with reporting. The interface is simple and the default filter options are sufficient for a general report.
Example: Total Sum of Net Sales for all products sold in X State between dates X and X. If the need is for a more complex query, then there is the Custom Query option. This would be something that an administrator would have to police as having users writing their own queries could get really messy really fast.
I suppose the key questions to ask would be:
Do you need a product that will... display all relevant charts/reports in one consistent place? ... be simple for an end user to navigate? ...be web-based and remotely accessed?

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

• Constantly updating: many of the BI tools we looked at were slow to iterate on their product. This was a main selling point for us.
• Ease of Use: We have many users that are new to BIs tools and database management in general. BI software as a whole has a pretty steep learning curve for most people, but Chartio does a good job of making things easier all around.
• Database Support: It seems as though every department insists on storing their information using different databases. Chartio had support for everyone one we needed which was very helpful.

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 sharing is descent but is a bit lacking. You can embed charts but they're not as nice as when displayed on Chartio dashboards.
• The pricing model is very competitive, but just to offer embedding puts you in a very high tier.
• They need a better pricing model for adding users. User licensing is a bit expensive.

Incentivized

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

Incentivized

It has become a core part of the business in terms of identifying the health of our network. If we grow and there are certain things that might not fit well with Chartio (e.g. we'd want to store snapshots of every single day's dash instead of seeing realtime data), it might make sense to move some of the data analysis tool in-house if resources are available.

I really like using Chartio. I use it on a daily basis for pulling data from different sources and combining data (the explore tab was a great idea for this use). I think I would give it 8/10 because there needs to be more documentation or maybe blog posts about things people are doing with it. I only have my own ideas about what to do /how to graph things. I know there are some articles, but it would be awesome to have a section on the neat dashboards people are building or how they show data in different ways. Another complaint is how much time it takes to load. I know our databases aren't set up precisely for Chartio and I have been creating data stores. But the data stores have so many more limitations that adds a whole new layer of frustration. Love the product, keep up the good work and the fast fixes.

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 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

I use self learning materials. Pretty helpful. I find myself having to go back to the "drilldown" instructions though, and have a hard time finding hidden variables on a dashboard, so perhaps there is room for intuitive improvements (or maybe I'm just being lazy)

Again, Chartio provides the best multi-user presentation ability for us. Other tools are great for slicing and dicing the data, but at the end, you still have to spend time trying to find a way to present it. Chartio has that built in.

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

Chartio has worked well as our datawarehouse has rapidly expanded, and the usability/performance hasn't seemed to have suffered. What we haven't yet realized is additional savings from additional users. We have some dashboard needs for users who truly just view of a few charts, and the licensing structure hasn't yet been structured in a way that would support that type of approach...having 50 "core" licenses, and then potentially several hundred view only licenses for partners that would use the application infrequently.

• 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