Qlik > Case Studies > The Business Case for Buy Vs. Build in Rapid Prototyping Environments

The Business Case for Buy Vs. Build in Rapid Prototyping Environments

Qlik Logo
Company Size
11-200
Region
  • America
Country
  • United States
Product
  • mesur.io
  • Qlik Sense
Tech Stack
  • Data Analytics
  • Data Visualization
  • Machine Learning
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Customer Satisfaction
  • Productivity Improvements
Technology Category
  • Analytics & Modeling - Data-as-a-Service
  • Analytics & Modeling - Machine Learning
  • Analytics & Modeling - Real Time Analytics
Applicable Industries
  • Agriculture
Applicable Functions
  • Product Research & Development
  • Quality Assurance
Use Cases
  • Farm Monitoring & Precision Farming
  • Predictive Maintenance
  • Real-Time Location System (RTLS)
Services
  • Data Science Services
  • Software Design & Engineering Services
About The Customer
The customer in this case study is mesur.io, a company that was founded to solve the problem of collecting, analyzing, and presenting meaningful data for small and mid-sized farms. The founder of mesur.io had experience in marine science and had worked on a project tracking animals and environmental conditions. He realized that there was a need for a solution that could provide actionable insights from the data collected from the soil. The founder had also worked on analytics startups and had solved hard math and architecture problems for large scale enterprises. When he moved closer to his aging father-in-law and bought a farm, he realized that the data problem was still very much alive. He wanted to monitor the soil on his new land, but the agricultural monitoring equipment available in the market did not provide actionable insights for smaller farms.
The Challenge
The challenge faced by mesur.io was to create a platform that could collect, analyze, and present meaningful data for small and mid-sized farms. The agricultural monitoring equipment available in the market was primarily designed for large-scale agriculture and did not provide actionable insights for smaller farms. The founder of mesur.io wanted to create a solution that was affordable and easy to use for the majority of farms worldwide. The solution needed to provide real-time data on soil conditions and offer recommendations based on historical trends. The challenge was to create a user interface that could present the data in a meaningful way and provide real insights rather than just displaying graphs.
The Solution
The solution was to use Qlik Sense, a data analytics and visualization platform. Qlik Sense was chosen because it was built like a regular SDK for working with data and it made it easy for users to see the connections within their data. The platform was designed with a user-first approach, focusing on the needs of the users who were primarily golf course superintendents and small farm operators. The platform was designed to automatically handle all the key data points and provide a visualization dashboard that provided real insights. The use of Qlik Sense shortened the development time and time to market by at least six months. The platform was also designed to handle real-time data in conjunction with historical data and link all the data points together. This allowed users to filter down to the selected area and get actionable insights.
Operational Impact
  • The use of Qlik Sense allowed mesur.io to create a user interface that provided real insights rather than just displaying graphs.
  • The platform was designed with a user-first approach, focusing on the needs of the users who were primarily golf course superintendents and small farm operators.
  • The platform was designed to automatically handle all the key data points and provide a visualization dashboard that provided real insights.
  • The use of Qlik Sense shortened the development time and time to market by at least six months.
  • The platform was also designed to handle real-time data in conjunction with historical data and link all the data points together. This allowed users to filter down to the selected area and get actionable insights.
Quantitative Benefit
  • Shortened development time and time to market by at least six months.

Case Study missing?

Start adding your own!

Register with your work email and create a new case study profile for your business.

Add New Record

Related Case Studies.

Contact us

Let's talk!
* Required
* Required
* Required
* Invalid email address
By submitting this form, you agree that IoT ONE may contact you with insights and marketing messaging.
No thanks, I don't want to receive any marketing emails from IoT ONE.
Submit

Thank you for your message!
We will contact you soon.