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Course: From 0 To 1:SQL And Databases - Heavy Lifting

From 0 To 1:SQL And Databases - Heavy Lifting

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About this Course

Prerequisites: No prerequisites are needed for the SQL commands and DBMS fundamentals. Basic knowledge of programming in Python would be helpful if you want to run the source code in the course-ending project.

Taught by Stanford-educated, ex-Googlers. This team has decades of practical experience in quant trading, analytics and e-commerce. 

Your bodyguard for when data gets too big, this course is strong but friendly, funny yet deep, animated yet thoughtful.

Let’s parse that.

Your bodyguard for when data gets too big: Most business folks (and quite a few engineers) use Excel as a basic tool of decision making and modeling, but when you can't fit the data you'd like into an Excel spreadsheet that you can easily open, its time to move to a database.

The course is strong but friendly: This course will help you move to a database without being intimidated by the new environment. Don't let anyone tell you that any dataset is too large or too complicated for you to understand (and people will try, most likely)

The course is funny yet deep: It goes really deep into the topics that folks often find hard to understand, such as joins, aggregate operators and interfacing with databases from a programming language. But it never takes itself too seriously:-)

The course is very visual : most of the techniques are explained with the help of animations to help you understand better.

This course is practical as well : Queries are explained in excruciating detail, indices are demystified, and potentially career-limiting traps (Drop, Alter) are marked with bright yellow tape markers so you can steer clear.

The course is also quirky. The examples are irreverent. Lots of little touches: repetition, zooming out so we remember the big picture, active learning with plenty of quizzes. There’s also a peppy soundtrack, and art - all shown by studies to improve cognition and recall.

What's Covered:

  • SQL In Great Depth
  • Database Fundamentals and Just Enough Theory
  • Practical Examples - Queries in MySQL and SQLite, and code in Python

Who is the target audience?

  • Yep! Data analysts who would like to really get down and dirty with the data
  • Yep! Business folks and executives looking to make their decision making more data-driven, and seeking the technical knowledge to do so.
  • Yep! Students of Computer Science and Computer Engineering looking to understand database concepts for the first time
  • Yep! Software engineers who need to understand and interface with databases from programming languages in their work
Basic knowledge
  • This course will cover generic (non-system-specific) SQL, but will also conduct exercises using 2 different database technologies: MySQL and SQLite. Installation and use of both these will be explained in-depth
What you will learn
  • Explore large datasets and uncover insights - going far beyond the Excel, deep into the data
  • Model and create a database for day-to-day use
  • Interface with databases from a programming language such as Python
  • Have the comfort and confidence needed to load data and use both GUI and a command line interface for database operations
  • Fully understand and leverage joins, subqueries, aggregates, indices, triggers, stored procedures and other major database concepts
Curriculum
Lectures quantity: 68
Common duration: 14:24:36
Introduction To Databases
  • Data Is A Big Deal  

    Life - and business - is becoming more and more data-driven, and data-intensive.

  • Why Do We Need A Database?  

    As the scale of your data grows, file systems (the most famous of which is - Excel!) struggle to keep up. Databases are carefully engineered to do the heavy lifting

  • MySQL - Installed and Introduced (Mac OS X)  

    MySQL is an open-source RDBMS, the most popular in the world by some measures. Acquired by Oracle, it still has a very powerful free Community Edition

  • Setting up MySQL and the Workbench (Mac OS X)  

    Setting up MySQL and the MySQL workbench can be a little daunting - never fear! We'll walk through it. (The Mac OS X version)

  • MySQL Server and Workbench installed (Windows)  

    Setting up MySQL and the MySQL workbench can be a little daunting - never fear! We'll walk through it. (The windows version)

  • Entities And Attributes - Things And Stuff Which Describe Them  

    Databases are like all computer systems - garbage in, garbage out. To make sure that what goes in makes sense, we need to model real-world entities and the relationships between them.

  • Identifying Entities Using Keys  

    What's a key? It is a set of defining attributes. Once you have the key, you have captured the essence of an entity, as it were.

  • The Entity Relationship (E-R) Model - Entities And Attributes  

    We dig deeper into the world of entities and relationships.

  • Relationships - What Connects Entities  

    Entities could be modeled even with flat files, but relationships can only be modelled in a database.

  • Cardinality Of Relationships  

    One-to-one, one-to-many or many-to-many? The nature of the relationships between entities determines how the corresponding data will be represented in a database

  • The Entity Relationship (E-R) Model - Relationships  

    We are almost ready to make the leap from modeling data to setting up a database. But first, let's delve a bit deeper into modelling relationships.

  • Mapping E-R Theory to the world of databases  

    All of that E-R model stuff we just learnt is really useful! Let's put it to work immediately, by figuring out how we can translate E-R models into database tables.

Going From Relations To Database Tables
  • Introducing The SELECT Statement  

    Select-From-Where will get you anywhere!

  • Introducing The SELECT Statement p2  

    Remember that columns in a database have types - these types govern how those columns can be used

  • Quotes and NULLS - Avoid The Gotchas  

    NULL is a special value - it implies that a value does not exist. Null is not TRUE or FALSE, its just NULL. Blank strings and zeroes are not null either

  • Simple Examples  

    Let's keep going - Select-From-Where will get you anywhere:-)

  • More Simple Examples  

    More Simple Examples

  • Using the Like Operator  

    LIKE and the % operator can make string matching so much easier

  • Between, In and Not In  

    Helpful operators - Between, In and Not In will simplify your queries (and your life!)

  • A Multi-Column Select  

    Remember that you can select any number of columns from any number of tables

  • Working with Dates (MySQL As Example)  

    Dates can be tricky because date handling is so different across database systems. Let's take MySQL as an example, and run through some of the common operations we'd perform with and on dates. Keep in mind that the syntax would be very different for a different DBMS though!

Creating Tables And Inserting Data Into Them
  • Creating Database, Use Database and Create Table  

    The circle of life of data begins with - creating a database, and creating an empty table within it

  • Column Subtleties: Null, Primary Key and Auto-Increment  

    Let's understand how a table can be created. In particular, NULLs, primary keys and auto-increment columns are commonly used, and really handy, so let's make sure we understand them

  • An Example - Sales Data  

    Examples of creating a table and inserting data

  • Insert Table - Examples  

    Examples of creating a table and inserting data

  • More Insert Table Examples  

    Examples of creating a table and inserting data

  • Referential Integrity Introduced  

    Referential Integrity (aka Foreign Key Constraints) are a really important concept in DBMS.

  • Creating a Database and Using It  

    Let's get our feet wet - create a database, use that database, create a simple table, and bulk load a file into that table

  • An Involved Bulk Loading Example  

    That first table was a bit simplistic - no constraints. Now let's do a more involved example, and harness the full power of the Bulk Uploader.

Back To Retrieving Data - More Advanced Queries Using Group By
  • Aggregation Operators Introduced  

    SUM, MAX, MIN, COUNT and AVG are aggregate operators - by definition they operate over a group of rows, rather than a single row

  • The Group By Clause  

    We discussed how aggregation operators need a range of queries to function on. What can that range be? It could be the entire table, but even more likely its some group of the rows in a table, defined by the GROUP-BY operator

  • More Group By Examples  

    Let's keep going with the GROUP-BY, and understand how it divvies up the data in a database

  • Order By  

    We can order the results of a query by one or more columns using the ORDER BY. Remember that relations are technically bags (i.e. multisets) which do not possess order - but this is a convenience taht DBMS make available

  • Having  

    Having is an operator that filters out groups based on a condition. Its like the WHERE clause but it operates on groups rather than individual rows

  • Limit  

    Use LIMIT to return only a specific number of rows from a query. Use this to peek into a large table without retrieving a gazillion rows

  • Count and Count Distinct  

    Count and count distinct are handy to find the number of rows, and the number of unique rows in a query result

Joins - Don't Let Them Intimidate You! They're All Fuzzy And Nice
  • Introduction To SQL Joins  

    The full power of databases emerges when we link tables - and Joins are the way to accomplish this

  • Cross Joins aka Cartesian Joins  

    Cross Joins are conceptually simple, which is great, because they are the underpinning of Inner Joins

  • Inner Joins  

    Inner Joins are your best friend. Understand them for what they are: cross joins with a filter condition.

  • Left Outer Joins  

    Outer Joins are really useful if used right. They are a little tricky though - understand how they work, and why you should not be surprised to see NULLs in the result of an outer join.

  • Right, Full Outer Joins, Natural Joins, Self Joins  

    Once we've understand Inner and Outer joins, Natural Joins are easy-peasey

Subqueries: Layering The Cake
  • Subqueries Introduced  


    What's a subquery? Its a query inside another. Outer and inner queries used together are very powerful.

  • Union, Union All, Intersect and Except.  

    The Set operations are easily extended to SQL, just remember that a relation is a bag, not a set (what's the difference? bags can contain duplicates, sets can't!)

  • Query-In-A-Query  

    Queries inside queries are really useful to modularize and simplify your queries

  • Inserting Via Subqueries  

    Inserting rows into a table 1 row at a time is painfully slow - never fear! You can run a query and directly pipe its output into a table

  • Use A Subquery To Populate A Table  

    Let's create a new table, this time using the Inner Join operator to seed it.

  • Outer Join And Inner Join: A Little Test  

    Let's create a table twice - once using Inner Join, and once using Outer Join. Guess what the difference is?

Constraints
  • Not NULL constraints  

    Any column can hold a NULL value, unless you specify a NOT NULL constraint. If you do, also use a default value if possible

  • Primary Keys  

    An Index is a quick way to query specific columns of a database. Indices make lookup very fast, but they slow down updates and deletes, so be sure to really understand them.

    Primary keys are always indexed for fast lookup.

  • Foreign Key Constraints  

    If for some reason you are unable to assign a primary key, at least have a foreign key

  • Deletes and Updates With Foreign Key Constraints  

    Updates and Deletes have a complicated interplay with the Foreign Key constraint. Understand on-cascade-delete and its cousins

  • Check Constraints  

    Check constraints are simple, and incredibly useful - and somehow underused. Use them!

Somewhat More Advanced Concepts
  • Indices  

    Always try to create tables with a primary key

  • Stored Procedures  

    Stored Procedures are to SQL what functions are to code. Learn how to define and call stored procedures

  • Triggers  

    Triggers are an advanced DBMS feature - conceptually really cool, also complicated!

  • Transactions  

    A transaction is a logical unit of work - the DBMS will ensure that each transaction satisfies 4 ACID properties: Atomicity, Consistency, Isolation and Durablility

  • Handle with Care: Update and Delete  

    The circle of life of data in a database does not stop with queries: Everything must change, including data

  • Handle with Care: Alter and Drop  

    Be really careful when you use the Alter and Drop commands. Incredibly powerful, and very simple - sometimes too simple, because that makes them so easy to use!

  • Views, Temporary Tables, and User Priviliges  

    Views can be thought of as virtual tables. Temporary tables are exactly what their name would suggest. Use them often!

Table Design: Theory And Practice
  • Practical Tips for Table Designs that you won't regret!  

    Designing good relational schemas starts off by figuring out the real world problem you want to map. Design each of your tables well, consider each column and what constraints it should and should not have. Remember choosing a primary key well is super important!

  • More Practical Design Tips  

    You know what you want to model, how do you figure how many tables you choose to store this information? Here are a few rules of thumb.

  • Normal Forms - Friends Once You Know Them  

    Normal forms are very inaccessible when you read them in theory, however they are great rules to get well-designed databased. Let's see what they mean in plain English-)

Putting It Together: Database Programming In Python
  • Interfacing with Databases from Python  

    How do programming languages interface with databases? Also, a step by step guide to building your own database of stock price movements over the last 2 years

  • SQLite works right out of the box  

    SQLite is available out of the box with Python, and is a handy and quick way to start working with databases with no setup or installation.

  • Build a database of Stock Movements - I  

    Code along as we build a database of stock movements. We'll download and unzip files with stock movements from the NSE website, insert the data into a database. We'll accept a ticker from a user and generate an excel sheet with a chart of its price movements for the last year.

  • Build a database of Stock Movements - II  

    Build a database of Stock Movements - II

  • Build a database of Stock Movements - III  

    Code along as we build a database of stock movements. We'll download and unzip files with stock movements from the NSE website, insert the data into a database. We'll accept a ticker from a user and generate an excel sheet with a chart of its price movements for the last year.

Appendix
  • [For Linux/Mac OS Shell Newbies] Path and other Environment Variables  

    If you are unfamiliar with softwares that require working with a shell/command line environment, this video will be helpful for you. It explains how to update the PATH environment variable, which is needed to set up most Linux/Mac shell based softwares. 

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