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Providing predictive analytics for livestock industry Big Data for a cattle-breeding concern Case Study MACHINE LEARNING BIG DATA PYTHON DATA VISUALIZATION

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Page 1: Big Data for a cattle-breeding concern - IT Svit · Case Info Technology stack: PostgreSQL, ML in AWS, Python, Flask, Jupyter Notebook, Chart.js Services: Cloud infrastructure design

Providing predictive analyticsfor livestock industry

Big Data for a cattle-breeding

concern

Case Study

MACHINE LEARNING

BIG DATA PYTHONDATA VISUALIZATION

Page 2: Big Data for a cattle-breeding concern - IT Svit · Case Info Technology stack: PostgreSQL, ML in AWS, Python, Flask, Jupyter Notebook, Chart.js Services: Cloud infrastructure design

Case Info

Technology stack: PostgreSQL, ML in AWS, Python, Flask, Jupyter Notebook, Chart.js

Services: Cloud infrastructure design and development, Big Data solutions,Web Development, Python development, Data visualization, Data normalization

Partnership period: September - December 2017

Team size: 2 people

Team location: Kharkiv, Ukraine

Industry: Livestock breeding concern

Location: United Kingdom

Expertise delivered: AWS cloud administration, Machine Learning, DevOps services,Big Data architecture, Python development, Data science, Data visualization

Page 3: Big Data for a cattle-breeding concern - IT Svit · Case Info Technology stack: PostgreSQL, ML in AWS, Python, Flask, Jupyter Notebook, Chart.js Services: Cloud infrastructure design

Client’s goals

IT Svit had a customer from the United Kingdom, a stock-breeding concern specializing at breeding pigs. The customer had a centralized reporting system in place, which allowed the farmers to report the farm operational parameters like:

The main goal was to increase the business profitability and reduce the losses due to livestock diseases. It was composed of several parts:

Normalization of the existing data set (some users wrote the medication titles in capital letters and some in plain text, etc.)

Creating and training a Machine Learning model to track the effectiveness of the meds

Developing a dashboard for data visualization and turning the data analysis results into clearly understandable graphs

The quantity of livestock

The numbers of animals gotten ill

Symptoms of the disease

Types of medication administered

How many animals recuperated or perished after treatment

Increasing the accuracy of meds administration

by 85%

Increasing the cattle-breedingprofitability by 37%

Reducing the livestockmortality by 80%

Page 4: Big Data for a cattle-breeding concern - IT Svit · Case Info Technology stack: PostgreSQL, ML in AWS, Python, Flask, Jupyter Notebook, Chart.js Services: Cloud infrastructure design

Project requirements

Development of a Big Data solution for processing the data inputted by the farmers and delivering actionable business insights based on it

Improvement of the efficiency of treatment by decreasing the time needed by the vets to assess the situation when the stock becomes ill

A configurable and simple dashboard enabling the users to visualize the data in the form of linear graphs and compare multiple graphs with each other

The customer wanted us to provide the following services:

Project resultsAfter we trained the Machine Learning (ML) algorithm based on the historical data, the system delivered the following benefits:

Diagnosys of the disease based on the symptoms

Recommendations for treatment at once

Prescriptive analytics helped the customer to reduce the time between identifying the disease and applying the treatment

Significantly higher percentages of recuperated livestock (approx 40% more)

Increased business profitability

Machine Learningmodel

DataVisualization

Cattle-breedingconcern

CloudInfrastructure

Page 5: Big Data for a cattle-breeding concern - IT Svit · Case Info Technology stack: PostgreSQL, ML in AWS, Python, Flask, Jupyter Notebook, Chart.js Services: Cloud infrastructure design

Challenges resolved

IT Svit team applied our experience with developing Big Data solutions and solved all the challenges:

We wrote a data normalization tool in Python to ensure the uniformity of data

We used Python and JupyteR Notebook to make statistical analysis and highlight patterns

The underlying cloud infrastructure was deployed in AWS and we used the AWS Machine Learning service in the process of training the model

The data was stored in the cloud using the PostgreSQL database and Amazon RDS

We used Flask and Chart.js to enable the data visualization and created a flexible dashboard for viewing the graphs. The users can compare any pair of parameters as needed

We wanted IT Svit to improve our existing system and allow the users to identify the diseases easier and help the vetsadminister the meds faster. We got a Big Data solutionpowered by a Machine Learning algorithm, which is often able to identify the disease at once, based on the symptoms, and advise the doctors on the course of actions, based on thehistorical records. I am more than satisfied with the results of our partnership with IT Svit

Alex, the managing directorof the cattle-breeding concern

Page 6: Big Data for a cattle-breeding concern - IT Svit · Case Info Technology stack: PostgreSQL, ML in AWS, Python, Flask, Jupyter Notebook, Chart.js Services: Cloud infrastructure design

For more than 12 years IT Svit helps the companies worldwide innovate and overcome their challenges. We have completed more than 600 projects, delivered successful projects for 6 Fortune 500 companies, helped 16 startups secure the investment and develop awesome MVPs. Our team of 50+ specialists provides services that earn 4.9 out of 5 customer satisfaction on Clutch.co.

IT Svit specializes in DevOps services, Big Data technology, Machine Learning, bespoke Blockchain platforms, full-cycle services for startups, web development and QA.

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