- Agile Data Science Tutorial
- Agile Data Science - Home
- Agile Data Science - Introduction
- Methodology Concepts
- Agile Data Science - Process
- Agile Tools & Installation
- Data Processing in Agile
- SQL versus NoSQL
- NoSQL & Dataflow programming
- Collecting & Displaying Records
- Data Visualization
- Data Enrichment
- Working with Reports
- Role of Predictions
- Extracting features with PySpark
- Building a Regression Model
- Deploying a predictive system
- Agile Data Science - SparkML
- Fixing Prediction Problem
- Improving Prediction Performance
- Creating better scene with agile & data science
- Implementation of Agile
- Agile Data Science Useful Resources
- Agile Data Science - Quick Guide
- Agile Data Science - Resources
- Agile Data Science - Discussion
Agile Tools and Installation
In this chapter, we will learn about the different Agile tools and their installation. The development stack of agile methodology includes the following set of components −
Events
An event is an occurrence that happens or is logged along with its features and timestamps.
An event can come in many forms like servers, sensors, financial transactions or actions, which our users take in our application. In this complete tutorial, we will use JSON files that will facilitate data exchange among different tools and languages.
Collectors
Collectors are event aggregators. They collect events in a systematic manner to store and aggregate bulky data queuing them for action by real time workers.
Distributed document
These documents include multinode (multiple nodes) which stores document in a specific format. We will focus on MongoDB in this tutorial.
Web application server
Web application server enables data as JSON through client through visualization, with minimal overhead. It means web application server helps to test and deploy the projects created with agile methodology.
Modern Browser
It enables modern browser or application to present data as an interactive tool for our users.
Local Environmental Setup
For managing data sets, we will focus on the Anaconda framework of python that includes tools for managing excel, csv and many more files. The dashboard of Anaconda framework once installed is as shown below. It is also called the “Anaconda Navigator” −
The navigator includes the “Jupyter framework” which is a notebook system that helps to manage datasets. Once you launch the framework, it will be hosted in the browser as mentioned below −
