Introduction to sql queries pdf

Lesson 4 - Sorting Data. SQL queries are defined and written to retrieve data in a certain order. This lesson is about designing SQL data tables for a database. Lesson 6 - Designing Data Rows. In this lesson, you will add data to your newly defined tables. In this lesson, you will continue writing JOIN statements that retrieve data result-sets from more than one table. Lesson 9 - Keeping the Database Up to Date. The quality of the data in the database depends on its integrity, including the concepts of data accuracy and consistency.

Lesson 10 - Aggregate Functions. In this lesson, you will examine the concept of aggregate functions and how they are used in query statements to examine multiple rows. Lesson 11 - SQL Views. SQL views are an important concept in database design and in using databases. Lesson 12 - Maximize Database Integrity and Performance.

Constraints are one way to maximize the integrity of the database and minimize the opportunity for user error. Macs are not compatible. Dual monitors are helpful but are not required. Software Requirements: PC: Windows 8 or later.

Microsoft Edge and Safari are also compatible. Adobe Acrobat Reader. Software must be installed and fully operational before the course begins. Student will install the required software in the course. Other: Email capabilities and access to a personal email account. Necessary rights local administrative rights to install programs on the computer.

Prerequisites: There are no prerequisites to take this course. Instructional Material Requirements: The instructional materials required for this course are included in enrollment and will be available online. Instructor Mava Wilson, Ph. A field is a column in a table that is designed to maintain specific information about every record in the table.

A record, also called a row, is each individual entry that exists in a table. For example, there are 91 records in the above Customers table.

A record is a horizontal entity in a table. A column is a vertical entity in a table that contains all information associated with a specific field in a table. We just launched W3Schools videos. SQL is best suited for this model of data storage. There are several tools available to manage, compare, administer and develop SQL databases. Different tools are built for different purposes, with their own sets of pros and cons. However, the underlying fabric is SQL. SQL has been around for a long time: the first SQL product available for public use was launched in —Oracle version 2— and Oracle remains one of the premier database systems today.

And the underlying concepts are the same since then, with a majority of SQL operations and commands involving four basic verbs: Select, Insert, Update and Delete. Also, SQL is generally whitespace-independent, which means that adding spaces within or between clauses will not matter.

Most SQL queries are standardized to seem like a question you direct towards a database object, which the said database object knows how to respond to. And since SQL, combined with the interpreter is so powerful that it has been adopted into many database products. Of course, there are other SQL products, not among the conventionally used tools and systems. Some are barebones SQL, while others have other features on top of them.

There are some exceptions, which may support only a part—not all—of the SQL standard. Therefore, when you start to specialize in a database product, you would need to learn those features, but a majority of what you do will revolve around what you learn in this book; the additional features will only act as the exterior coat.

In an industry where data is everything, data tools are among the must-haves. SQL is unquestionably on the list. Any data science professional will tell you, for example, how important SQL is.

In a survey of analytics, data mining and data science software, conducted in , SQL was placed third in the list of usage, after Python and the R language. SQL can work on varied systems and platforms. Therefore, knowing SQL is important for developers who deal with the data. Understanding SQL will take you a long way in creating fast, efficient software, which leverages the benefits of well-structured data.

It can be said, without a doubt, that SQL is the only transferrable skill that can find a place in the toolbox of any developer or database administrator. The SQL is standardized, and therefore, is useful across systems that deal with databases. Once you know SQL, all you would need is to adopt very minor syntax adjustments from one database system to another—the model remains the same, the fabric remains the same.

Let me start with data munging. Data munging, or wrangling, is the process of transforming data into various states based on what state would be better suited for a situation at hand. In other words, how you should change the representation of data to make it more understandable to an application or user.

For instance, when you use APIs to download content, or scrape a website or use an existing data set for prediction, how would you transform the data so it becomes a well-defined stream, that can be readily consumed by a certain data analysis tool? The primary issue with data munging is data duplication. A few wrong SQL joins during munging can potentially generate thousands of duplicate data. These may be because of SQL code or because of issues in the backend database. A quality assessment after every step of data munging is important to avoid these issues.

We see in the industry, that in general, very little time is spent in learning or practicing the skills required to manage SQL databases. This leads to a series of bad things, the biggest ones of which are:. Think of your data as the bricks you use to construct a building. Think of the SQL schema as the blueprint of your building. When you are constructing a simple structure of four walls, twelve feet in height and fifteen feet in width each, and no roof, you do not need much of a schematic.