This course introduces you to the concept of DataOps—its origins, components, real-life applications, and ways to implement it. WHAT YOU WILL LEARN - Understand the process to establish a repeatable process that delivers rigor and repeatability - Articulate the business value of any data sprint by capturing the KPI's the sprint will deliver - Understand how to enable the organization's business, development and operations to continuously design, deliver and validate new data demands
Agenda of the Dataops Training Course
Agenda ==================================================== DataOps Concept and Foundation The Problem with Datascience - The knowledge Gap - Lack of Support - Challenges of of Data Analytics Agile Collaboration for DataOps - DataOps Manifesto - DataOps Principles - Data Science Life-Cycle DevOps for DataOps - Development and Operations - Fast Flow from Continous Delivery - Reproducible Environments - Deployment Pipelines - Continous Integration - Automated Testing Deployment and Release Processes - Self-Service Deployments - Release Processes - DevOps Measurements - Review Processes - DevOps for Data Analytics - The Data Conflict - Data Pipeline Environments - Data Pipeline Orchestration - Data Pipeline Continous Integration DataOps Technology - Tools based on DataOps Values and Principles - DataOps Technology Ecosystem - The Assembly Line - Data Integration - Data Preparation - Stream Processing - Data Management - Reproducibility, Deployment, Orchestration, and Monitoring - Compute Infrastructure and Query Execution Engines - Data Storage - DataOps Platforms - Data Analytics Tools DataOps Tools Training - Models & Architecture - DataOps Concept and Foundation - Platform - Operating Systems - Centos/Ubuntu & VirtualBox & Vagrant - Platform - Cloud - AWS - Platform - Containers - Docker - Planning and Designing - Jira & Confulence - Programming Language - Python - Source Code Versioning - Git using Github - Container Orchestration - Kubernetes & Helm Introduction - Database - Mysql - Database - postgresql - Data Analystics Engine - Apache Spark - Reporting - Grafana - ETL Tools - Apache Kafka - Bigdata - Apache Hadoop - DataOps Integration - Jenkins - Big Data Tools for Visualization - Microsoft PowerBI - Big Data Tools for Visualization - Tableau
