Introduction
Welcome to the SQL and Python for Data Analysis and Database Development course! In this course, you will learn how to use SQL and Python to work with databases and analyze data. Databases are an essential part of modern computing, and they are used in everything from social media applications to e-commerce websites to scientific research.
Why database ?
Imagine you work for a large online retailer, and your company needs to manage thousands of products, customers, and orders every day. You could store this data in an Excel spreadsheet, but as your company grows, this becomes increasingly difficult and time-consuming. You might have dozens or even hundreds of spreadsheets, each containing different pieces of data, making it difficult to find the information you need quickly. In addition, spreadsheets are not ideal for handling large amounts of data, and they can become slow and unwieldy as the size of the dataset grows.
This is where databases come in. A database is an organized collection of data that is designed to be easy to access, manage, and update. With a database, you can store all your company's data in one place, making it easy to find the information you need quickly. Databases are also designed to handle large amounts of data efficiently, so you can work with massive datasets without running into performance issues.
Course goals :
In this course, we will be using the Structured Query Language (SQL) to work with databases and python. SQL is a powerful language that allows you to manipulate and analyze data stored in databases. We will also be using Python, specifically the SQLAlchemy library, to connect to databases, query data, and create tables. By the end of this course, you will have a solid understanding of SQL concepts and practical experience using SQL and Python to manipulate and analyze data.
Technical goals
Here are some main goals as a developer for mastering databases:
- Understanding data modeling: The ability to design and implement effective data models is crucial for building scalable and efficient databases. This includes knowledge of different types of databases, data structures, and normalization techniques.
- Proficiency in SQL: SQL (Structured Query Language) is the standard language used for querying, manipulating, and managing data in databases. As a developer, it is important to have a strong understanding of SQL and its various functions.
- Database administration skills: Database administration involves tasks such as installing, configuring, and maintaining databases. A developer who is proficient in database administration can optimize performance, troubleshoot issues, and ensure the security of their databases.
- Knowledge of database architecture: Understanding the architecture of databases and how they interact with other systems is essential for building and integrating applications with databases.
- Familiarity with database tools and frameworks: There are many tools and frameworks available to developers for working with databases, including ORMs (Object-Relational Mappers), and database management systems. Familiarity with these tools and frameworks can help developers work more efficiently and effectively with databases.
Let's get started 🥳