Client Background

  • Client: A leading IT & Tech firm in Australia 
  • Industry Type: IT & Data Service
  • Products & Services: Data Analysis
  • Organization Size: 100+

The Problem

The  data was stored in Airtable, and we used its basic dashboards for visualizations embedded in our Noloco system. However, slow loading times affected performance. We needed an expert to migrate our data to MongoDB, recreate the dashboards, and ensure they load quickly within Noloco.

Our Solution

We migrated the data from Airtable to MongoDB Atlas, recreated the dashboards in MongoDB, and optimized them for fast loading. The new dashboards were embedded into Noloco, delivering a smoother and more responsive user experience.

Deliverables

Dashboard in MongoDB Atlas

Tech Stack

  • Tools used
  • MongoDB Atlas
  • Language/techniques used
  • MongoDB Aggregate Pipeline
  • Models used
  • No model is used
  • Skills used
  • MongoDB Atlas, Data Analysis
  • Databases used
  • MongoDB
  • Web Cloud Servers used
  • No Web Cloud Servers used

What are the technical Challenges Faced during Project Execution

One of the main technical challenges we faced during the project was creating calculated fields when some necessary fields were missing. This made it difficult to complete the dashboard, as the visualizations couldn’t be fully built using aggregate pipeline inside chart panel editing

How the Technical Challenges were Solved

We solved the technical challenge by creating new collections in MongoDB Atlas that included the required fields. These fields were calculated from existing data and then used to build the visualization cards in the dashboard.

Business Impact

The migration to MongoDB Atlas and the optimized dashboards significantly improved performance and reliability. By embedding the new dashboards into Noloco, users now experience faster load times and smoother interactions, leading to better productivity and decision-making.

Project Snapshots

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