Google Data Analytics - Prepare Data For Exploration

Google Data Analytics Certificate Review of the Third Course: Prepare Data For Exploration

The course will provide you with a broader understanding of data collection, data structures, data types, and the generation of data. You'll engage in hands-on practices with SQL in a real data warehouse, specifically BigQuery.

Key points covered in this course include:

1. Basics of extracting, filtering, and sorting data from databases/warehouses. Assignments will involve both spreadsheets and SQL.

2. Enhanced comprehension of different data types, formats, and considerations regarding bias in data.

3. Exploration of data ethics and data privacy.
   

The course structure effectively presents important and valuable insights into data. Understanding how data is collected, evaluate data quality, and interpreting metadata are crucial for future learnings. You will also understand better what is metadata, that describes various aspects of the data, such as its source, format, and context. Building a solid foundation in data is the starting point for meaningful analysis. It will help you to make informed decisions, uncover patterns, and extract valuable insights.

Hands-on practices play an important role in this course. You'll have access to BigQuery, and the exercises will be done with real public data. Before diving into the practices, you'll receive a brief introduction to relational databases and SQL, including concepts like foreign and primary keys. SQL proficiency is a key skill for retrieving, filtering, and manipulating data from databases. Essential skill, especially for aspiring data analysts seeking their first real job. These exercises provide valuable and practically the best and maybe only way to acquire this new skill.

So, go ahead and continue on your learning journey. Relational database contains tables that can be connected with common keys. SELECT courseid, course_name, est_time

FROM Google_Data_Analytics

WHERE courseid = 3 OR course_name = 'Prepare Data For Exploration';

| courseid | course_name | est_time |

| 3 | Prepare Data For Exploration | 25 hours |