Process Data with Xplenty and Visualize it with

Process Data with Xplenty and Visualize it with

We concentrate on making data processing as fast and easy as possible. To complete the dataflow, Xplenty integrates with a plethora of services that can store, analyze, or visualize data. One of these services is, a popular service for data visualization. You can use Xplenty to process the data and then visualize the results in Here’s how.

Processing Data with Xplenty

In the example below, we used Xplenty to process public GitHub data and find the total commit sizes per day in June 2014.


Xplenty dataflow

  1. github_source — loads the relevant GitHub data from our public S3 directory

    cloud storage source

  2. filter_commits — filters only PushEvents (commits)


  3. select_fields — selects the commit size field while typecasting it to an integer and changes the date to a string format via the ToString(created_at,'yyyy-MM-dd') function


  4. sum_commit_size — calculates the total commit size per day


  5. output_redshift — saves the results to Redshift so they can be loaded in (here’s how to connect Xplenty to Redshift). Xplenty can also save the results as CSV files or to relational databases, which can all be integrated with

    amazon redshift destination

Visualizing Results with

Once the above job is executed on a cluster, the results will be stored in Redshift. To load this data in

  1. Log in to your account

  2. Go to “Settings” and “Data Sources” to connect a new data source and select “Amazon Redshift.” connect a new data source

  3. Enter all the relevant Redshift connection details and click “Connect.” connect a Redshift data source

  4. Start visualizing your data. connect a Redshift data source


Data can be easily processed with Xplenty and then visualized in We showed an example of how GitHub data can be aggregated and visualized, but we’re really curious to see what you would be able to do with your data.

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