Dataiku vs. Tableau Public

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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Tableau public is the best platform to build dashboards for your personal profile and share with recruiters. It's always good to keep ourselves updated on the latest features, create sample dashboards and save them to a personal profile. Tableau public is free and doesn't need any subscription. anyone can create an account and start building reports.

• 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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• Data visualization: lots of different options, including bar, scatter, pie, waterfall charts to explore relationships between variables, and to present findings/trends to different teams
• Integrates readily with limited, though different data sources: TXT, CSV, TDE, Access
• Exports reports for review of different dashboards: client-ready/team-ready, with a clean and tidy presentation in PDF format (or hardcopy)

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• End product deployment.

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• Tableau Public (both Desktop and Server) like their "for a fee" counterparts offer very easy to learn and use tools to transform data into pictures and gain insights into your data. Most organizations report a reduction in development time of 10x vs. other similar tools, due to the intuitive user interface. That said, with Tableau Public, published workbooks are "disconnected" from the underlying data sources and require periodic updates when the data changes. Users are limited to 1 Gb of storage space per user ID and password as well.
• I would like to see better options for public sharing of visualizations and data from within the "for a fee" products as more and more organizations are moving in the direction of data sharing with partners and their communities.

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It's free, right? I'll keep using the free version. So the real question to ask is this? Will I pay $999 for the Personal version or $1,999 for the Professional? Yikes! That is a big stretch. I'm not sure about that. The product comparison chart is at: http://www.tableausoftware.com/public/comparison

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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Tableau public is a great training tool to understand the basics of Tableau before buying it. A great tool to extend Excel's visualization and to publish data for others. Not useful for anything you need secure. No ability to access databases. Static information only.

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 have not yet required to contact support as the documentation and help i found online has always worked so far

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I found it sufficient, and fast. I could easily "kick the tires" with Tableau on my data so I got up and running fast.

Start at the end and work backward. Identify the business case / issue and questions the end users have, then identify the data needed, and where to get it.

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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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Google Charts/Drive is sufficient for simpler data sets, but it does not integrate with other web platforms and the visualization does not look as professional. I'm not aware of any other competitors that offer the same package as Microsoft.

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• 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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• Tableau Public visualizations have helped drive traffic to our content and sites
• The lack of cost means it's easy to demonstrate our experience to attract paying clients

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