Chartio (discontinued) vs. Dataiku

Chartio is a great tool for building presentable dashboards. It can export, you can add read-only access, and it has permissions levels by dashboard for users. There are other data analysis tools that help to analyze the data, but few allow for such a nice presentation

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.

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• Direct linkage to our databases. Abstracts away the visualization layer so we can focus on the data and the queries.
• Host of graphs and tools that permits all types of data visualizations.
• Haven't quite used this yet, but there is a new embedding feature that will be very helpful so that we can embed the charts into a company central dash.

• 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.

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• There is not a last full month date range option. You can still get the range that you need, but the dashboards will have to be manually updated to exclusively display one whole month.
• When building a chart, the area which displays your tables and fields is finite. You can't adjust the size to make it easier to see. They do allow a mouse-over to see the entire name of your table/field, but I would prefer to adjust the width.
• Once you modify a query in the Custom Query tab, there doesn't seem to be a way to go back to using the U.I.

• End product deployment.

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Great customer support: You will receive an answer by email usually within 20-30 minutes. Not only that but our CSMs for Chartio go out of their way to help, they have even created charts for some of the less experienced users that wanted an example to work from. We have had nothing but great experiences with this team.

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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.

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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.

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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)

Chartio so far has been the easiest BI tool to setup and has also been the most affordable. There are some other, great, BI tools out there but they were a bit to heavy handed for what we needed. Also - despite the high cost per user in Chartio, the other tools were still more expensive.

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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.

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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.

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