Introduction to Hadoop basics in 30 mins
- Database basic concepts
Please note that this is NOT a full course but a single module of the full-length course, and intended to cover very basic fundamental concepts for absolute beginners so that they can speed up with Azure Synapse SQL Data Warehouse course.
This module is NOT GOOD for you if:
You are already experienced in this technology
You are looking for an intermediate or advance concepts
You are looking for practical examples or demo
This module is GOOD for you if:
You want to understand the basic fundamental concepts of this technology.
This is a free module to help others. If you are not in the intended audience, I request you to please feel free to unenroll.
Where I can find a full-length course?
Please look at the bonus lecture in the end.
What will students learn in this course?
Hadoop basic concepts (Crash course to speed up with Azure HDInsight)
If you are not comfortable in English, please do not take course, captions are not good enough to understand course.
Database and BI developers
Anyone who wants to start learning Big Data
Basic Database concepts
Course In Detail
Data Warehouse Crash Course
In this module, you will learn, what was shortcomings of our traditional Monolithic systems.
you will learn how Distributed system is different from Monolithic systems
you will learn about Hadoop fundamental understanding and how it is different from RDBMS
you will learn 3 main building blocks or components of Hadoop, like the HDFS or Hadoop Distributed File System, the MapReduce programming model for processing and the resource negotiator YARN for cluster management.
Microsoft SQL Server, Azure SQL Server, Azure SQL Data Warehouse, Data Factory, Data Lake, Azure Storage, Azure Synapse Analytics Service, PolyBase, Azure monitoring, Azure Security, Data Warehouse, SSIS
Who this course is for:
- Database Developer
- College Students
- Anyone interested to learn Basic Hadoop concept
- 00:27Is this course good for me? Set expectation
- 01:02Hadoop Overview
- 04:35Why we need distribute computing?
- 06:08Two ways to build system
- 06:25Introducing Hadoop
- 04:20Hadoop vs RDBMS
- 00:37Hadoop Summary
13 years of extensive professional experience with expertise in Microsoft Database and Business Intelligence Solutions, Advanced Analytics, Reporting and Azure cloud computing technologies
- DP-200: Implementing an Azure Data Solution
- DP-201: Designing an Azure Data Solution
- Microsoft Certified Technology specialist (MCTS) – SQL Server Database development
- Information Technology Infrastructure Library (ITIL V3) Certified
Azure : Data Lake, Data Factory, Synapse Analytics (DW), PolyBase, Stream Analytics & Storage
Big Data Tech : HDInsgiht, Databricks, CosmosDB, Hadoop, Spark, PySpark, Hive, Sqoop
Database versions : Microsoft SQL Server 2005-2016, NoSQL
Languages : T-SQL, USQL, Python, MDX, DAX, PySpark
BI Tools : SSRS, SSIS, SSAS, Power BI
I have been messing around with data for more than a decade now, I love to work on Database internals, performance tuning, and optimization, Database design, modeling, and implementation especially using Microsoft SQL Server and Azure database and analytics technologies.
As a developer and architect, I have worked closely with customers, users, and colleagues to support business solutions across a variety of industries including healthcare, insurance, finance, and government ranging from small companies to fortune 500 companies. These experiences provided opportunities to see varied implementations, troubleshoot performance-related problems, give guidance on design, and provide consultation on optimization, availability, and recoverability.
I helped in End to End Implementations of many database projects, providing team leadership and project management, requirements gathering, specification documentation, functional/technical design, Data modeling & solution architecture.
Outside of the technical world, I love yoga and meditation. I am a student of ancient yogic text Bhagavad Gita and love to discuss and practice philosophical teachings.