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