Datameer vs. Tableau Prep

Datameer's workbooks include an intuitive GUI for maximum usability. Anyone with an analytical mind may easily compile data using the built-in worksheet capability without requiring much technological knowledge. Ad hoc reports may now be made and scheduled. In addition, I haven't had too much problem fixing things because I can get most of the answers I want there.

Incentivized

Tableau Prep is a very powerful tool when it comes to creating workflows to monitor each stage for data analysis and quality issues. Also, it is convenient to explore the data with the wealth of operators and checking work at each stage of the process. Also, some areas that would help is if there are more types of automation provided.

Incentivized

• It leverages scalability, flexibility and cost-effectiveness of hadoop to deliver an end-user focused analytic platform for big data without involvement of IT.
• It overcomes Hadoop`s complexity by providing GUI interface with pre-built functions across integration, analytics and data visualization .
• Excel feature is awesome for business users which is already provided by Datameer.
• Using datameer now user can do smart analytic using Decision Trees, Column dependency and recommendation.
• Recently HTML5 inclusion is making application to available on a wider range of devices, including the iPad and other mobile devices which does not support Flash.
• It can be used in premise or in a cloud computing environment.
• Wizard-based data integration designed for IT and business users to schedule and do transformation of large sets of structured, semi-structured and unstructured data without any knowledge of Hadoop ecosystem.

• Display the raw data coming in from the data warehouse
• Point out situations that might be erroneous
• Show the distribution of raw data figures

Incentivized

• Data visualization and graphics. Right now it's not very user friendly. Creating dashboards requires a lot of work that can be done by the application

Incentivized

• Use of Macros within Workflow (and more types of automation)
• Join Editor also giving a SQL Update Query
• More types of visuals

Incentivized

Employees with intermediate SQL and Hive knowledge can generate reports faster than using Datameer . It does have visualization tool but I don't think it is anything that cannot be accomplished by importing the data in Excel

It is a valuable tool for generating and cleaning files for multiple purposes.

Incentivized

Easy to use for most things, starts to require some planning as your projects get more complex.

It works well and is user friendly for the basics but needs more options for bring in data (using SQL queries for example) and export format options.

Incentivized

I have not really had to reach out for any kind of customer support for Tableau Prep, so I can't really say. However, the support that Tableau has given for their other products has been great, so I would assume it would be the same here. They are also constantly adding new features and providing software updates, and that is always a plus.

Incentivized

Live connections to cloud services (Google Sheets for example) and cloud hosted databases (cloud hosted SIS for example) for scheduled flows are not supported

Incentivized

I have compared Datameer with the tools listed above and it blows them out of the water. Datameer is much more user friendly than these tools and is also a lot more powerful. Once the Q1 release comes out with drill down capabilities on the infographics, Datameer will surpass Tableau and Spotfire in visualization.

Tableau Prep is covered in our license whereas Alteryx required additional fees and a separate license. Tableau Prep is similar to Tableau Desktop which a lot of our team is comfortable with so it wasn't difficult to get a feel for Tableau Prep. However, Alteryx would have been a totally new platform.

Incentivized

• Quick time to value. Transition from developer to learning Datameer is less than a day.
• Workspace is drag and drop, which makes it intuitive and easy to use.
• Speed of data transformations.
• Pulling data from various sources.
• Easy to schedule data pipelines.
• Tailor made for Snowflake and Redshift.
• Documentation is sometimes not updated quickly.
• Training videos are a bit long.

• Quicker data sets for online reports
• More efficient data cleaning Ad Hoc reports
• Costly if using data management to schedule data pull and cleaning (priced per viewer accounts not creator accounts)

Incentivized