Database vs Data Warehouse vs Data Lake | K21Academy

Summary

In this session, K1N Academy explores the growing demand for data-related jobs and the key concepts in data management. The session introduces essential terms like databases, data warehouses, and data lakes, explaining their differences and uses. It discusses structured vs. unstructured data and how these systems help manage vast amounts of information. Examples are provided for each term, highlighting tools such as SQL Server, Azure, and Google BigQuery. The session concludes with an invitation to a free master class, offering insights into data engineering careers, exam prep, and hands-on experience with Azure tools for certification.

Takeaways

• 😀 Data is rapidly growing and is expected to increase data-related job opportunities by 27.9% by 2026.
• 😀 Data can be categorized into two types: Structured Data (organized in rows and columns) and Unstructured Data (lacking a predefined structure).
• 😀 Structured data can be easily processed using SQL and is typically stored in databases like SQL Server, Oracle, and MySQL.
• 😀 Unstructured data, making up 80% of all data, includes emails, news, and multimedia files and requires more complex processing.
• 😀 A **database** is designed to store structured data, typically in tables, and is optimized for quick retrieval using SQL.
• 😀 A **data warehouse** is a specialized database optimized for analytics and reporting, allowing businesses to archive data for future analysis.
• 😀 ETL (Extract, Transform, Load) is the process of transferring data from a database to a data warehouse for reporting purposes.
• 😀 A **data lake** is a centralized repository that stores both structured and unstructured data, without requiring immediate processing.
• 😀 Data lakes are used heavily in fields like AI and machine learning, where large amounts of raw data can be stored and processed later.
• 😀 Popular tools for accessing data in a database include SQL queries, while tools like Power BI and Excel are often used for accessing data in data warehouses.
• 😀 K2N Academy offers a **free masterclass** to help learners get started with data engineering, including topics like the Microsoft Azure Data Engineer certification (DP-203).

Q & A

What is the main focus of the session?

The main focus of the session is to introduce and explain the concepts of databases, data warehouses, and data lakes, and how data is accessed in each of these environments.

What is the predicted growth rate in data-related jobs by 2026?

The survey predicts a 27.9% rise in data-related jobs by 2026.

What are the two main types of data discussed in the session?

The two main types of data discussed are structured data and unstructured data. Structured data has a defined schema and is organized in rows and columns, while unstructured data lacks a defined schema.

What is a database, and what are some examples?

A database is a structured collection of data organized in tables with rows and columns. Examples of databases include Microsoft SQL Server, Oracle Database, and MySQL.

Why can't databases be used for reporting purposes in some cases?

Databases are designed to track current business data. If data is deleted, connections between tables may be broken, making it difficult to run accurate reports. In such cases, a data warehouse is used to store archived data.

What is a data warehouse, and how does it differ from a regular database?

A data warehouse is a specialized type of database designed for analytics and reporting. Unlike regular databases, it stores historical data for analysis, even if records are deleted from the database. The process of transferring data to the warehouse is known as ETL (Extract, Transform, Load).

What is a data lake, and what types of data can it store?

A data lake is a centralized repository that stores both structured and unstructured data at any scale. It can store a variety of data types, including images, videos, and files, without requiring processing until needed for analysis.

What are the examples of platforms used to maintain data lakes?

Some platforms used to maintain data lakes include Amazon Web Services (AWS), Microsoft Azure, and Google BigQuery.

How can data from a database be accessed?

Data from a database can be accessed using SQL queries or forms built within the system.

What tools can be used to access data from a data warehouse?

Business intelligence tools such as Power BI and Excel are commonly used to access data from a data warehouse.

What is the purpose of the free masterclass mentioned in the session?

The free masterclass is designed to help learners understand the basics of data engineering and prepare for the Microsoft DP-203 certification exam. It provides insights into job opportunities, market trends, and the Azure Data Engineer role.