Azure Data Factory Training at SQL School Training Institute
At SQL School we teach how to use Data Factory, a cloud data integration service, to compose data storage, movement, and processing services into automated data pipelines. There would be practical tutorials describing how to use different components or building blocks of data factory v2.
At the end of the course, students will be able to get started and build medium complex data driven pipelines in data factory independently and confidently.
Schedule : Feb 29th @ 8 AM India Time (weekend batch)
Kindly refer the below video on What is Power BI and it’s uses.
Power BI is a business analytics service by Microsoft. It is a cloud-based, elegant end-to-end business analytics tool that enables anyone to visualize, analyze, forecast any type of data with greater speed, efficiency, and understanding.
Power BI provides cloud-based BI services, known as “Power BI Services“, along with a desktop based interface, called “Power BI Desktop”. It offers data warehouse capabilities including data preparation, data discovery and interactive dashboards. Microsoft released an additional service called Power BI Embedded on its Azure cloud platform. One main differentiator of the product is the ability to load custom visualizations.
Power BI Desktop : The Windows-desktop-based application for PCs and desktops, primarily for designing and publishing reports to the Service.
Power BI Service : The SaaS (software as a service) based online service (formerly known as Power BI for Office 365, now referred to as PowerBI.com or simply Power BI).
Power BI Mobile Apps : The Power BI Mobile apps for Android and iOS devices, as well as for Windows phones and tablets.
Power BI Gateway : Gateways used to sync external data in and out of Power BI. In Enterprise mode, can also be used by Flows and PowerApps in Office 365.
Power BI Embedded : Power BI REST API can be used to build dashboards and reports into the custom applications that serves Power BI users, as well as non-Power BI users.
Power BI Report Server : An On-Premises Power BI Reporting solution for companies that won’t or can’t store data in the cloud-based Power BI Service.
Power BI Visuals Marketplace : A marketplace of custom visuals and R-powered visuals
If you wish to learn Power BI, please find the necessary details from below link : https://sqlschool.com/PowerBI-Online-Training.html
This Power BI Online Training includes EVERY detail of each Power BI Visual, Usage and Properties as per the latest versions.
This Power BI course includes On-premise and Cloud Data Access, REST API, Azure Stream and R Integration including Data Modelling and ETL Techniques with Basic to Advanced Power Query (M Language), DAX Language Functions, Power BI Dashboards, Streaming Datasets, App Workspace, Content Packs, Data Gateways, Alerts, Power BI Report Server Components, Power BI Mobile Reports, Excel Integration, Excel Analysis, KPIs for Big Data Analytics, Microsoft OneDrive, Google Big Query, DataFlow and ETL in Cloud are also a part of this Power BI Online Training course in addition to Mock Interviews, Resume Guidance, Concept wise Interview FAQs and ONE Real-time Project.
SQL stands for Structured Query Language. SQL is used to communicate with a database. According to ANSI (American National Standards Institute), it is the standard language for relational database management systems. It is used to perform operations on the data present in database.
SQL statements are used to perform tasks such as update data on a database, or retrieve data from a database.
Although most database systems use SQL, most of them also have their own additional proprietary extensions that are usually only used on their system.
However, the standard SQL commands such as “Select”, “Insert”, “Update”, “Delete”, “Create”, and “Drop” can be used to accomplish almost everything that one needs to do with a database.
SQL commands are divided into several different types, among them data manipulation language (DML) and data definition language (DDL) statements, transaction controls and security measures.
Some common relational database management systems that use SQL are: Oracle, Sybase, Microsoft SQL Server, Access, Ingres, etc.
The @@ROW COUNT variable returns the number of rows read by the last executed statement. If any statement does not return any rows, then value of @@ROWCOUNT variable is set to zero.
MSSQL @@ROWCOUNT VARIABLE SYNTAX
Using @@ implies that it is a global variable. Also @@ROWCOUNT returns the value of int type i.e. the maximum no of rows @@ ROWCOUNT can return is 231 (2,147,483,647). For returning rows greater than this limit, ROWCOUNT_BIG function is used.
The LIKE operator is used to list all rows in a table whose column values match a specified pattern. It is useful when you want to search rows to match a specific pattern, or when you do not know the entire value. For this purpose we use a wildcard character ‘%’.
For example: To select all the students whose name begins with ‘S’
SELECT first_name, last_name
WHERE first_name LIKE ‘S%’;
The output would be similar to:
The above select statement searches for all the rows where the first letter of the column first_name is ‘S’ and rest of the letters in the name can be any character.
SQL Server accepts Transact-SQL (which is an extended version of the SQL standard), so you could create the database by running the following SQL script.
CREATE DATABASE Music;
To do this, open a new query by clicking New Query in the toolbar and run an SQL CREATE DATABASE statement.
Just as you can specify certain properties when creating a database via the GUI, you can include those same properties when creating a database by script. Here’s an example of specifying settings for the data and log files.
USE master ;
CREATE DATABASE Music
( NAME = Music_dat,
FILENAME = ‘C:\Program Files\Microsoft SQL Server\MSSQL13.MSSQLSERVER\MSSQL\DATA\Music.mdf’,
SIZE = 10,
MAXSIZE = 50,
FILEGROWTH = 5 )
( NAME = Music_log,
FILENAME = ‘C:\Program Files\Microsoft SQL Server\MSSQL13.MSSQLSERVER\MSSQL\DATA\Music_log.ldf’,
SIZE = 5MB,
MAXSIZE = 25MB,
FILEGROWTH = 5MB ) ;
This topic shows how to use SQL Server Management Studio (SSMS) to connect to SQL Server 2017 on Linux. SSMS is a Windows application, so use SSMS when you have a Windows machine that can connect to a remote SQL Server instance on Linux.
After successfully connecting, you run a simple Transact-SQL (T-SQL) query to verify communication with the database.
Install the newest version of SQL Server Management Studio
When working with SQL Server, you should always use the most recent version of SQL Server Management Studio (SSMS). The latest version of SSMS is continually updated and optimized and currently works with SQL Server 2017 on Linux. To download and install the latest version, see Download SQL Server Management Studio. To stay up-to-date, the latest version of SSMS prompts you when there is a new version available to download.
Connect to SQL Server on Linux
The following steps show how to connect to SQL Server 2017 on Linux with SSMS.
Start SSMS by typing Microsoft SQL Server Management Studioin the Windows search box, and then click the desktop app.
In the Connect to Serverwindow, enter the following information (if SSMS is already running, click Connect > Database Engine to open the Connect to Server window):
The default is database engine; do not change this value.
Enter the name of the target Linux SQL Server machine or its IP address.
For SQL Server 2017 on Linux, use SQL Server Authentication.
Enter the name of a user with access to a database on the server (for example, the default SA account created during setup).
Enter the password for the specified user (for the SA account, you created this during setup).
After successfully connecting to your SQL Sever, Object Explorer opens and you can now access your database to perform administrative tasks or query data.
Run sample queries
After you connect to your server, you can connect to a database and run a sample query. If you are new to writing queries, see Writing Transact-SQL Statements.
In second normal form, all columns in the table rely on the primary key and the table has a singular purpose
There could be relationships between the columns… dependencies could lurk within these columns called transitive dependence.
Transitive dependence means that a value of a column/field within a table relies on a another column in that same table, but this is facilitated through another column between them.
A table is in third normal form when the following conditions are met:
It is in second normal form.
All nonprimary fields are dependent on the primary key.
Again, transitive dependence means dependence between columns of the same table. Think of ArtistNationality, Artist, and Artwork. The values for ArtistNationality and Artist depend on the Artwork; once you figure out the Artwork, you know the Artist/ArtistNationality. But ArtistNationality depends on the value from Artist: This is a transitive dependence.
In order to get to third normal form, we need to make sure all columns are only dependent upon the primary key. That means we have to get the country code out of the artist table. In the following example, we’ve added country name to the table to further highlight the issue with normalizing
It’s fine that the country code exists in the artist table, but having the country name breaks the 3rd normal form rule, since we can’t get the country name without the code; we can’t get the code without the artist ID. This is by nature the definition of transitive dependence.
Let’s look at some examples that will use the fictional music database as a subject.
we’ll create another table called countries, move the country code and country name to this table. Country code becomes the primary key in the countries table, but is retained in the artist table as a foreign key.