SQL Server Tutorial : Intermediate SQL Server

Want to learn more? Take the full course at https://learn.datacamp.com/courses/intermediate-t-sql at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Welcome to this DataCamp course on Developing SQL for Data Science. My name is Ginger Grant and I will be your instructor for this course. I have been working with Transact SQL, commonly known as T-SQL, the version of SQL used in SQL Server for over 10 years and I have been recognized by Microsoft as a Data Platform MVP and a Certified Trainer. As president of the data analytics consultancy, Desert Isle Group, I provide training and develop solutions using SQL and other tools to help clients find meaning from their data. In this course we are going to use SQL to analyze data for exploratory data analysis. In the first chapter, we will looking at summary information, commonly used in other languages like R and Python. In Chapter 2 we are going to look at some SQL Functions useful for manipulating data by using math and date functions. Chapter 3 contains techniques for modifying the data, and lastly in Chapter 4 TSQL windowing functions. Data Scientists spend a lot of time analyzing and aggregating data by generating summary statistics such as the mean, minimum and maximum values of columns. If your data exists in a database, the fastest way to generate summary statistics is by using SQL. In the videos of this chapter, we will run queries on the EconomicIndicators table. The data displays by country several interesting statistics like Gross Domestic Product or GDP and Internet Use. A sample of the table is included here which includes different integers, text, floats. You can calculate common summary stats such as the minimum, maximum, and average of each column by using the MIN, MAX, and AVG functions, respectively. As you can see on the slide, you need to pass the column name to the relevant functions to calculate the summary statistics. Note that all