Alteryx Platform

I used Alteryx Analytics individually for some research that I was doing for one of the data projects that I had. It has an intuitive workflow for data blending and analytics. It makes all the processes much faster compared to what it was before.

Unlike dealing with already cleansed and validated data sitting in data warehouses, when it comes to big volumes of unstructured 'dirty' data in non-standard formats which then need to be quickly cleansed for analysis is where Alteryx shines. By making use of easy-to-understand workflows, even not-so-technical users are able to leverage the built-in tools in order to quickly clean, process and output data in the required format without having to defer to a data engineering specialist. An example includes trying to process 100+ text files containing 10+ million key IDs separated by spaces, which if done manually via Microsoft Excel would have likely taken roughly half an hour to process each separate file, thus requiring potentially 50+ hours to complete. Instead in Alteryx uses a simple workflow which opens a text file, separates each key ID into a new row and discarding. The headers then repeat for all the text files in the directory taking half an hour to design the workflow. After this, it takes less than a minute to actually run and output a single file which can be then used by Microsoft PowerBI or Tableau to perform analysis and/or create an ad hoc dashboard.

Alteryx Analytics has been used by my organization on a very small scale as of now. It is being used by only me for now. It can be used to blend data easily without any hassles and to remove the complexity for predictive analysis for people without detailed knowledge about those things.

Alteryx is used in several departments including Data Science, Finance, Risk, Marketing, and Sales. It is used for everything from simple ETL to complex advanced analytics, including predictive modeling/ML/AI.

Alteryx is to my knowledge the most efficient tool for agile data preparation. I use it massively as a low-code yet elaborate-feature-rich piece of software to acquire, transform, cleanse and analyse data, generally big data, from various and heterogeneous sources as required for the corporate internal audit assignments which cover the full scope of business units and activities in the company I work with.