Using SQL to Retrieve and Analyze Data Quickly and Efficiently
20-21 & 27-28 April 2022 | 2PM - 5PM
This course is designed for people who want to answer business questions with data. We will be using Bigquery and SQL (Structured Query Language) as our primary data warehouse to access and analyze the data stored in the database.
SQL is a powerful tool and is easy to get started with. It also helps you generate compelling reports. It is used by big and small companies alike to tackle challenging analytics problems and answer questions to improve business processes, operations and sales ROI.
3 Hours per Session
Introduction to relational databases
Introduction to BigQuery
Introduction to SQL
Data importing to GBQ
Basic SELECT statement, ORDER BY, LIMIT
Table Variables and Set Operators
Subqueries in WHERE clause
The JOIN Family of Operators
GROUP BY and analytics functions
WINDOW, NITLE function
SQL Project - Build Customer Analytics Records showing customer profiles used in Customer Segmentation and Predictive Modelling (eg: demographics, purchasing behavior and custom segmentation).
Example dataset includes basic customer profiles, point-of-sale data, & inventory data from an e-commerce store.
Understand various data models used in analytics and Bigquery data warehouse.
Understand why relational databases are useful and what you can do with them.
Use SQL effectively to create customer analytic records (CARS) analyses on customer profile and transactional data
from e-commerce settings.
Benefits of Attending
Get a solid introduction to analytics and
data-driven decision making.
Learn to retrieve large amounts of records
from a database quickly and efficiently.
Gain a good understanding and practical experience using SQL to analyze data.
Have experience analyzing big data sets that traditionally would be difficult to analyze using MS Excel and other similar tools.
You should also attend if you are asking these questions:
How do I easily explore and extract insights from my data?
Who Should Attend
I have too many rows and columns in my Excel sheets, causing it to crash on me.
People who need to conduct basic data analysis and presentation from these departments:
IT, Marketing, Product Marketing, Product Development, Digital Marketing, CRM, Finance, HR, Business Development, Data Analyst, Sales, etc.
How can I work more effectively?
How do I make my data analysis reproducible?
How do I use data-driven presentations to convince stakeholders?