Journey To Data Lakes - Building Modern Data Architectures

Let's Harness the Potential of Big Data

What you'll learn

Understand the concept of a data lake: Gain a comprehensive understanding of what a data lake is, its purpose, and its benefits in modern data architecture.

Learn the core components of a data lake: Explore the essential components and building blocks of a data lake.

Explore different data lake architectures: Understand various architectural patterns and approaches for designing and implementing data lakes.

Master data ingestion techniques: Learn different methods and tools for ingesting data into a data lake, including batch processing, real-time streaming

Understand data storage and organization: Learn how to store and organize different types of data within a data lake, including structured, semi-structured,etc

data processing and analytics: Acquire the skills to process and analyze data stored in a data lake.

Implement data governance and security: Understand the importance of data governance in a data lake environment and learn to establish data governance practices

Requirements

Basic understanding of data concepts: Familiarity with fundamental data concepts such as databases, data structures, and data processing will provide a strong foundation for learning about data lakes.

Knowledge of data storage and processing:

Experience with SQL: Proficiency in SQL (Structured Query Language) is valuable as it is often used for querying and manipulating data in data lakes.

Familiarity with data formats

Description

The "Introduction to Data Lakes: Building Modern Data Architectures" course is designed to demystify the concept of data lakes and empower learners to harness their potential in managing and analyzing big data. Participants will gain a deep understanding of the fundamental principles, components, and best practices for implementing data lakes in a modern data ecosystem.Throughout the course, learners will explore the foundational concepts of data lakes, including the benefits they offer in terms of data storage, processing, and analytics. They will delve into the essential components of data lakes, such as data ingestion, data storage, data processing, and data governance, learning how these elements work together to create a robust data architecture.Participants will discover the different architectural patterns and design considerations for data lakes, enabling them to make informed decisions when implementing data lakes in their organizations. They will also learn the various techniques for data ingestion, including batch processing, real-time streaming, and event-based approaches, ensuring they have the skills to efficiently load data into the data lake.The course will cover data storage and organization strategies within a data lake, including file formats, partitioning, and metadata management. Participants will gain understanding of data processing and analytics techniques specific to data lakes, exploring tools and languages used for data transformations, querying, and advanced analytics.Moreover, learners will delve into data governance and security practices in a data lake environment, understanding how to establish access controls, ensure data quality, and implement data lifecycle management. They will explore the integration of data lakes with other data platforms, such as data warehouses and analytical platforms, to create a comprehensive data solution.By the end of this course, participants will have a solid foundation in data lakes and the skills to design and build modern data architectures. Armed with this knowledge, learners will be equipped to leverage data lakes to store, process, and analyze vast amounts of data, enabling them to derive valuable insights and make data-driven decisions.Whether you are a data engineer, data analyst, or IT manager, this course will empower you to leverage data lakes effectively and unlock the potential of your organization's data. Join us on this learning journey and embark on your path to becoming a data architecture expert.

Overview

Section 1: Introduction to Data Lakes

Lecture 1 Data Beyond the buzz

Lecture 2 Structured Data

Lecture 3 Unstructured Data

Lecture 4 Where Unstructured data stored

Lecture 5 Semi Structured Data

Lecture 6 What is Big Data?

Lecture 7 Use Cases

Lecture 8 Big Data - Volume

Lecture 9 Big Data - Velocity

Lecture 10 Big Data - Veracity

Lecture 11 Big Data - Variety

Lecture 12 Big Data - Value

Lecture 13 How Big Data Analytics works ?

Section 2: Module 2

Lecture 14 What is data lake?

Lecture 15 Historical Perspective of Data

Lecture 16 Key Benefits of Data lake

Lecture 17 What are data stores Types

Lecture 18 Data Lake - Historical aspects , benefits and features

Lecture 19 Datalake vs dataWarehouse

Lecture 20 Different File Types – Data Lake

Section 3: Module 3 - Data lake architecture Introduction

Lecture 21 Data lake architecture Introduction

Lecture 22 Azure Data lake Architecture - Ingestion

Lecture 23 Data Lake Architecture -Data Storage Layer

Lecture 24 Data Lake Architecture -Data Processing

Lecture 25 Data lake Architecture - Data Processing - Data Partitioning

Lecture 26 Data lake Architecture - Data Processing - Data Caching

Lecture 27 Data lake Architecture - Data Processing - Data Workflow Management

Lecture 28 Data lake Architecture - Governance & Security

Data Engineers: Data engineers who are responsible for designing, building, and maintaining data infrastructure will find this course valuable. It will help them understand the concepts and best practices for implementing and managing data lakes.,Data Architects: Data architects involved in designing data solutions and data integration strategies can benefit from this course. It will provide them with insights into incorporating data lakes into their architectural plans.,Data Analysts: Data analysts seeking to work with large volumes of data, perform advanced analytics, and derive insights will find this course useful. It will help them understand how to leverage data lakes for data exploration, analysis, and reporting.,Data Scientists: Data scientists interested in utilizing big data and machine learning techniques can gain valuable knowledge from this course. It will cover data lake integration with tools like Apache Spark and provide insights into leveraging data lakes for machine learning projects.,Business Intelligence Professionals: Professionals working in the business intelligence domain can benefit from this course as it covers data lake integration with analytical platforms, enabling them to explore and analyze data efficiently.,IT Managers and Decision Makers: IT managers and decision makers responsible for data strategy and infrastructure planning can gain insights into the benefits, considerations, and implementation of data lakes through this course. It will enable them to make informed decisions regarding data lake adoption within their organizations.,Database Administrators: Database administrators interested in understanding how data lakes complement traditional data storage and processing technologies will find this course helpful. It will provide insights into integrating and managing data lakes alongside existing databases.,Technology Enthusiasts and Learners: Individuals with a keen interest in data management, big data technologies, and cloud computing can take this course to expand their knowledge and explore the concepts and capabilities of data lakes.