Agile Data Science Tutorial
Agile Data Science Useful Resources
Selected Reading
- Implementation of Agile
- Creating better scene with agile & data science
- Improving Prediction Performance
- Fixing Prediction Problem
- Agile Data Science - SparkML
- Deploying a predictive system
- Building a Regression Model
- Extracting features with PySpark
- Role of Predictions
- Working with Reports
- Data Enrichment
- Data Visualization
- Collecting & Displaying Records
- NoSQL & Dataflow programming
- SQL versus NoSQL
- Data Processing in Agile
- Agile Tools & Installation
- Agile Data Science - Process
- Methodology Concepts
- Agile Data Science - Introduction
- Agile Data Science - Home
Agile Data Science Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
Agile Tools & Installation
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 pke servers, sensors, financial transactions or actions, which our users take in our apppcation. In this complete tutorial, we will use JSON files that will faciptate 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 apppcation server
Web apppcation server enables data as JSON through cpent through visuapzation, with minimal overhead. It means web apppcation server helps to test and deploy the projects created with agile methodology.
Modern Browser
It enables modern browser or apppcation 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 −
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