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)
A relational database (RDB) is a collective set of multiple data sets organized by tables, records and columns. RDBs establish a well-defined relationship between database tables. Tables communicate and share information, which facilitates data searchability, organization and reporting.
RDBs use Structured Query Language (SQL), which is a standard user application that provides an easy programming interface for database interaction.
Relational databases are based on the relational model, an intuitive, straightforward way of representing data in tables. In a relational database, each row in the table is a record with a unique ID called the key. The columns of the table hold attributes of the data, and each record usually has a value for each attribute, making it easy to establish the relationships among data points.
Benefits of Relational Databases:
Commitment and Atomicity
Stored Procedures and Relational Databases
Database Locking and Concurrency
Relational Database Terms
Below are the unique terms and specific definitions that will help you understand what a RDB can do and how it works:
Row : A set of data constituting a single item.
For example, the data for a single employee (e.g. first name, last name, employee ID, hire date, work location, etc.) of a company would be displayed in a row. A row can also be called a record, an entity, or a tuple.
Column: Labels for elements of rows. A column gives context to the information contained in rows. For an employee database, the column headers could be the items listed above for employees. A column is also known as an attribute or a field.
Table: A group of rows that match the parameters set up for the table. The data in a table must all be related. An employee database may have separate tables for active employees, retired employees, and former employees. A table is also known as a relation or base revelar.
View: A set of data based on a query via the RDBMS; also known as result set or derived revelar.
Domain: The set of possible values for a given column. For example, the phone number and ZIP code columns would be numbers, while first and last names would be limited to letters.
Constraint: A narrowing of a domain. For example, the domain of the work location on a employee record would be alphanumeric, but it could be restricted to a predefined list rather than being a free-form field. The phone number field would be constrained to 10 digits.
Primary key: The unique identifier of a row in a table.
Foreign key: The unique identifier of a row in another table.
Distributed Database: A database that stores data in multiple locations, rather than on a single hard drive or server.
TYPES OF DATABASE RELATIONSHIPS
The power of a relational database is in the links and relations. By connecting rows in different tables through the use of primary and foreign keys, you can create views, reports, and other slices of information to serve your organization. There are three primary types of database relationships:
One-to-One: One row in one table is connected to one and only one row in another table. For example, a Social Security number is linked to a single employee.
One-to-Many: One row in one table is connected to zero, one, or more than one rows in another table. For example, one work location can be linked to many employees.
Many-to-Many: Zero, one, or many rows in one table are linked to zero, one, or many rows in another table. For example, multiple employees can be assigned to multiple projects.
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.
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 is available in various editions. This chapter lists the multiple editions with its features.
Enterprise − This is the top-end edition with a full feature set.
Standard − This has less features than Enterprise, when there is no requirement of advanced features.
Workgroup − This is suitable for remote offices of a larger company.
Web − This is designed for web applications.
Developer − This is similar to Enterprise, but licensed to only one user for development, testing and demo. It can be easily upgraded to Enterprise without reinstallation.
Express − This is free entry level database. It can utilize only 1 CPU and 1 GB memory, the maximum size of the database is 10 GB.
Compact − This is free embedded database for mobile application development. The maximum size of the database is 4 GB.
Datacenter − The major change in new SQL Server 2008 R2 is Datacenter Edition. The Datacenter edition has no memory limitation and offers support for more than 25 instances.
Business Intelligence − Business Intelligence Edition is a new introduction in SQL Server 2012. This edition includes all the features in the Standard edition and support for advanced BI features such as Power View and PowerPivot, but it lacks support for advanced availability features like AlwaysOn Availability Groups and other online operations.
Enterprise Evaluation − The SQL Server Evaluation Edition is a great way to get a fully functional and free instance of SQL Server for learning and developing solutions. This edition has a built-in expiry of 6 months from the time that you install it.
This SQL Server tutorial explains how to use the WHERE clause in SQL Server (Transact-SQL) with syntax and examples.
The SQL Server (Transact-SQL) WHERE clause is used to filter the results from a SELECT, INSERT, UPDATE, or DELETE statement.
Parameters or Arguments
conditions : The conditions that must be met for records to be selected.
SELECT * FROM employees WHERE first_name = ‘Jane’;
In this SQL Server WHERE clause example, we’ve used the WHERE clause to filter our results from the employees table. The SELECT statement above would return all rows from the employees table where the first_name is ‘Jane’. Because the * is used in the SELECT, all fields from the employees table would appear in the result set.
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.