Stored Procedure in SQL

This article I will give you some basic syntax about stored procedure in SQL.

Stored Procedure:

Stored Procedure is the prepared SQL codes that we can save, so the code can be reused over and over again.

It is suitable for some SQL queries we need to use frequently.

There are three kinds of stored procedure:

  1. No parameter
  2. One parameter
  3. multiple parameters

Stored Procedure (No parameter) Syntax

CREATE PROCEDURE procedure_name
AS
sql_statement
GO
EXEC procedure_name

Stored Procedure (One parameter) Syntax

CREATE PROCEDURE [dbo].[oneparameter]
@ProductCatergoryID int
AS
SELECT *FROM Production.ProductCategoryID
GO
EXEC oneparameter @ProductCatergoryID = '4'

Stored Procedure (multiparameter) Syntax

CREATE PROCEDURE [dbo].[multiparameter]
@ProductCategoryID int, @Name varchar(50)
AS
SELECT *FROM Production.ProductCategory pc
WHERE pc.ProductCategoryID = @ProductCategoryID and pc.Name = @Name
GO
EXEC multiparameter @ProductCategoryID = '4', @Name = 'Accessories'

I will record all knowledge I touch in my Business Intelligence journey.

Next blog will be around Data Warehouse.

If you are interested in or have any problems with Business Intelligence, feel free to contact me .

Or you can connect with me through my LinkedIn.

Business Intelligence Tutorial

This blog is Business Intelligence tutorial, which contains lots of definitions and terms.

There are three steps in Business Intelligence: Data collecting, Data Warehousing and Reporting.

Data Collecting:

  1. Structured: Standardized and easy for computers to read and query.
  2. Semistructured
  3. Unstructured: Not stored in rows and columns, so it can’t easily read by computers.

As we talked in previous blog, company data can be found in several locations, such as CRM programs, which is also shown in the picture below.

Data Warehouse:

Data warehouse uses a process (ETL, i.e., extract, transform and load) to standardize data, which allows it can be queried.

How does information get to a central location?

ETL———————>Data Warehouse

  1. Extract: unstructutred data is tagged with metadata to make it easier to find
  2. Transform: normalize data
  3. Load: tranfer data to central warehouse or data mart

Turning Data into Powerpoints (Business Intelligence Reporting)

  1. Data visualization: Graphic display of results
  2. Dashboard: Interfaces that represent specific analyses

If you are interested in or have any problems with Business Intelligence, feel free to contact me .

Or you can connect with me through my LinkedIn.

Some Cheat Sheets about Business Intelligence

There are several parts of my Business Intelligence journey.

So I write this blog for recording some cheat sheets.

Installation:

Firstly, some tools need to be installed on the laptop.

All of them are Microsoft softwares, so I prepare a surface laptop 2.

  1. SQL Server 2016 Developer Edition: Seclect the features we need to install, such as SQL Server Integration Services(SSIS), SQL Server Analysis Services(SSAS) and SQL Server Reporting Services(SSRS).
  2. SQL Server Management Studio(SSMS)
  3. SQL Server Data Tools(SSDT)
  4. Report Builder

What is Business Intelligence(BI)?

I have mentioned it in the previous blog. It is to transform raw data into meaningful information for analysis.

BI Process:

  1. Import data from different data sources
  2. Produce reports or graghs through SSIS, SSAS and SSRS
  3. Make business decisions

Some terms:

ETL: Extraction, Transformation and Loading

OLTP: Online Transaction Processing

Cube: Multi-dimensional data structure built using dimensions and facts, using MDX (Multi dimensional expression) language

SQL and Relational Database: which I have mentioned them in the previous blog

Primary Key: A single attribute or an unique id in a Relational Database

Foreign Key: A set of attributes that references a candidate key in a Relational Database

Some differences:

Traditional Normalized Database VS Data Warehouse: Formal one has no duplicate data but latter one has duplicate data for efficiency.

Null VS Blank(where clause): For null, the clause is where xxxxx is null; For blank, the clause is where xxxxx is ”

Delete VS truncate: truncate table xxxxx ->no rollback&faster; delete from xxxxx -> rollback

SQL Language:

Learning sources:

  1. w3schools.com
  2. SQL Server tutorial for beginner

Some common commands:

One table:

SELECT…FROM

WHERE CLAUSE

ORDER BY CLAUSE

Two tables:

Inner Join

Other Joins, e.g., LEFT OUTER JOIN

GROUP BY

If you are interested in or have any problems with Business Intellgence, feel free to contact me .

Or you can connect with me through my LinkedIn.

The Simplest Way to Install SQL Server 2017 on macOS

This article we will show how to install Microsoft SQL Server 2017 on macOS, as we talk it in previous blog.

Which method we use?

Prior to SQL Server 2017, if we want to install it on macOS, a virtual machine (like Parallels Desktop) is essential. Then we can install a Windows system in it and then we install and run SQL Server.

Luckily, from SQL Server 2017, we can choose to install SQL Server on Docker containers.

How to install SQL Server on Docker?

1 What is Docker?

Docker is a platform which can make softwares to run in it. It is called a container, which is an isolated environment.

2 Download and install Docker

If you haven’t installed Docker on your Mac, the next step is to install Docker.

Go to Docker page to download the .dmg file and then double click and install it according to the instructions.

3 Run Docker and increase the memory

Run Docker as you used to run other softwares and the next step is to increase the memory. This is because the default value of Docker memory is 2 GB but SQL needs at least 3.25 GB.

I recommend we set the memory value to 4 GB.

  1. Click Docker icon on top menu of your Mac
  2. Click Preferences
  3. Set Memory under Advanced to 4 GB.

Click Apply&Restart

4 Download Microsoft SQL Server 2017

The next step is to download SQL Server 2017 from Terminal, which is an easy way.

Copy and paste the command in Terminal of your Mac:

docker pull microsoft/mssql-server-linux

Through it, the latest version of MS Server SQL can be downloaded.

5 Run a Docker image

Copy, change and paste the command in Terminal of your Mac:

docker run -d --name xxxxxxx -e 'ACCEPT_EULA=Y' -e 'SA_PASSWORD=xxxx\xxxx' -p 1433:1433 microsoft/mssql-server-linux

We need to change the name and password as your own here.

This step is to run an instance of Docker image. A Docker image is a file, which is used to execute codes in a Docker container.

If you want to check, copy and paste the following command to see whether the Docker container is running:

docker ps

If it works, it will show like this:

6 Install the sql-cli command line tool

The next step is to install the sql-cli command line tool. It can allow you to run commands against your SQL Server instance.

Copy and paste the command in Terminal of your Mac:

npm install -g sql-cli

If an error happened and shows you do not have the permissions to access this file as the current user, just try add sudo in your command:

sudo npm install -g sql-cli

7 Connect to SQL Server

After sql-cli is installed, now we can connect to SQL Server using the mssql command.

mssql -u xxxxxxx -p xxxxxxx

Here xxxxxxx and xxxxxxx means your name and password.

Then you will see:


Now you’ve successfully connected to your instance of SQL Server.

Next blog we will continue our journey with SQL Server and Azure Data Studio. Maybe you will want to read more about Azure and Microsoft Learn in the previous blog.

If you are interested in or have any problems with Business Intelligence, feel free to contact me .

Or you can connect with me through my LinkedIn.

Welcome to SQL (SQL 101)

If you want to find a BI Analyst job in New Zealand, you may be not a master of Python, R, etc.

However, SQL knowledge is essential.

Here is a BI Analyst job advertisement on LinkedIn, which is a full-time role.

St John is also an accredited employer.

If you have a skill that is needed by a New Zealand accredited employer and they offer you full-time work when you are abroed, you may be able to get a Talent (Accredited Employer) Work Visa.

From the job description, we can find SQL knowledge is important.

What is SQL?

Firstly, I want to talk about Database(DB). We all know DB is a kind of software to store a large amount of data, mainly Relational DB.

Structured Query Language(SQL) is always linked with DB. SQL can be used to operate data, such as querying and updating.

The relationship between DB, data and SQL is like: DB is a plate, data is dishes on the plate and SQL is your fork.

Currently, most of the websites and Apps are based on SQL and DB.

There are several popular DB on the world, e.g., SQLite, MySQL, Postgres, Oracle and Microsoft SQL Server.

Among them, MSSQL Server is the most popular in New Zealand.

Luckily, all of them can support SQL although they have different characteristics.

It is like if you have the fork, you can operate dishes on different plates.

What is Relational DB?

A DB is composed of several tables (like tables in Excel) and tables are composed of rows and columns.

We can query and obtain some results from the DB through SQL language.

Maybe some people will be confused about: What is the difference between DB and Excel? Excel has already existed on the world, why SQL is created?

That is because DB = Tables + Relations between tables.

Tables in Excel can’t meet the data operating requirements in companies because of the complex relations between tables.

How to kick-start SQL?

After knowing the terms of SQL and Relational DB, the next step is to set up the environment with SQL Server, which we will talk in the next blog.

If you are interested in or have any problems with Business Intelligence, also feel free to contact me .

Or you can connect with me through my LinkedIn.