AHEAD - Making Complex Data Analytics Simple Using the Dataiku Join Recipe

Options
alonzorworks
alonzorworks Dataiku DSS Core Designer, Dataiku DSS ML Practitioner, Dataiku DSS Adv Designer, Registered Posts: 1

Team members:

  • Alonzo Roberts, Associate Technical Consultant
  • Monmoy Moshin, Associate Technical Consultant

Country: United States

Organization: AHEAD

AHEAD builds platforms for digital business. By stitching together advances in Cloud, Automation, Operations, Security and DevOps, we help clients deliver on the promise of digital transformation.

Awards Categories:

  • Best Partner Acceleration Use Case

Business Challenge:

Using tools outside of Dataiku can be frustrating. We wanted to showcase how Dataiku can enable complex data analytics by making joins easy among other things.

See the demo here.

Business Solution:

This was a two person project. My coworker Monmoy joined the datasets in Dataiku (among other things). I built a web application in Streamlit using the data he processed. Now our company has a demo that can showcase the power of Dataiku to clients.

Business Area Enhanced: Analytics

Use Case Stage: In Progress

Value Generated:

It gives our sales team an interactive demo. This demo serves as a way to show our analytics prowess that can help solve our clients biggest conundrums. In this case, Dataiku facilitated that greatly.

Value Brought by Dataiku:

Dataiku helped join 8 real world datasets. These datasets were provided by a large Brazillian e-commerce website called Olist. Joining 8 datasets together in SQL, Pandas, or other means would be a Herculean task. With Dataiku it was pretty simple.

Setup Info
    Tags
      Help me…