Welcome to the Building Web GIS Apps with Java Spring Boot MVC and Leaflet course. We'll be building a Full-stack MVC style Web Application using the Java Spring Tool suite. The purpose of this course and many more to follow, is to learn to create geospatial analytics and convert it into a functional application.
In our use case we will be working with residential water consumption data and we will be applying data processing techniques to extract transform and load the data into our spatial database. Once we have processed and cleaned the data, we will use it as a data source for building our Java Spring Boot Web Map Application.
Some skills that you can expect to derive after completing the course are the following:
● You will learn how to build a Spatial Database using Postgresql and PostGIS.
● You will learn how to create charts with Chart.js.
● You will learn to build Web Maps with Leaflet.js.
● You will learn how to build REST API Endpoints.
● You will learn how to build Web Applications using the Java Spring Boot MVC framework.
WHAT YOU WILL LEARN
● Be able to create a Full-stack web GIS application from scratch
● Building Full-stack Java Spring Boot MVC Apps
● Building a Java Spring Boot REST API
● PostGIS for Java and Windows
WHO THIS COURSE IS FOR
● Beginner and advanced developers
● The curious mind
2. Setup and Installations
3. Building a Java Spring Boot MVC Application
4. Writing the Back-End Code
5. Building the Java Spring REST API Service
6. Building the Front-End Using Thymleaf and Leaflet.js
7. Project Sources Code
Edwin Bomela is a Big Data Engineer and Consultant, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. He is currently a consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce.