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Explore data lakes for storing large volumes of raw data. Learn to design and manage data lakes for scalable and flexible data storage.
Introduction to Data Lakes: Definition and purpose of Data Lakes. Distinction between Data Lakes and other data storage architectures (e.g., Data Warehouses). Components of a Data Lake: Understanding the essential components such as storage, processing, and metadata management.
15 lip 2024 · Explore the essence of data lakes in modern data architecture: scalable repositories storing diverse data types for agile analytics and innovation, transforming business insights across industries.
Data lakes allow you to store relational data like operational databases and data from line of business applications, and non-relational data like mobile apps, IoT devices, and social media. They also give you the ability to understand what data is in the lake through crawling, cataloging, and indexing of data.
This is an in-depth course designed to equip you with the knowledge and skills to harness the full potential of data lakes. Dive into the world of modern data management, understand the benefits and limitations of data lakes, and learn to leverage them for enhanced business intelligence.
Data lakes provide a robust strategy to capture, store, process, and derive value from this data. This course is your comprehensive guide to understanding, building, and managing a data lake.
A data lake is a centralized repository that allows you to store all of your structured and unstructured data at any scale. That means however much data you have, whether it is gigabytes or...
