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SQL-PLSQL-ETL-Bi Development

SQL :A programming language called structured query language (SQL) is used to store and process data in relational databases. Information is stored in tabular form in relational databases, where different data attributes and the various relationships between the data values are represented by rows and columns. Information can be stored, updated, removed, searched for, and retrieved from databases using SQL statements. Database performance can also be maintained and enhanced with its help.

Working of SQL

SQL is a declarative language, which means you specify what you want to do with the data, and the database system figures out how to do it. Here’s a simplified overview of how SQL works:

Query Creation: You write SQL queries to perform operations on the database. These operations can include SELECT (retrieving data), INSERT (adding data), UPDATE (modifying data), and DELETE (removing data), among others.

Query Parsing: When you execute an SQL query, the database system parses the query to understand what operation you want to perform and on which tables or data.

Query Optimization: The DBMS’s query optimizer generates an execution plan for the query, which outlines the most efficient way to retrieve or modify the data. The optimizer considers factors like indexes, available resources, and database statistics.

Query Execution: The execution plan is executed against the data in the database, and the results are returned to you. This may involve accessing and manipulating data in storage, applying filters, and performing various operations according to the SQL query.

Result Presentation: The final results are presented to you in a format that you can understand, typically as a table or a result set.


SQL Commands

The SQL commands help in creating and managing the database. The most common SQL commands which are highly used are mentioned below:

CREATE Command

This command helps in creating the new database, new table, table view, and other objects of the database.

UPDATE Command

This command helps in updating or changing the stored data in the database.

 

 

DELETE Command

This command helps in removing or erasing the saved records from the database tables. It erases single or multiple tuples from the tables of the database.

 

SELECT Command

This command helps in accessing the single or multiple rows from one or multiple tables of the database. We can also use this command with the WHERE clause.

 

 

DROP Command

This command helps in deleting the entire table, table view, and other objects from the database.

 

 

INSERT Command

This command helps in inserting the data or records into the database tables. We can easily insert the records in single as well as multiple rows of the table.

 

 

Benefits of SQL

SQL offers a number of benefits that contribute to its increasing popularity in the data science field. It is an ideal query language that enables users and data experts to interact with the database. The top features or advantages of structured query language are as follows:

1.No programming needed

For SQL to manage database systems, a small number of coding lines are needed. The database is easily accessed and maintained with the help of basic SQL syntactical rules. The SQL is easy to use thanks to these basic guidelines.

2. High-Speed Query Processing

SQL queries are a quick and effective way to retrieve a lot of data from the database. Data operations such as insertion, deletion, and updating are completed faster as well.

3. Standardized Language

SQL adheres to the well-established ISO and ANSI standards, providing a consistent platform for all of its users worldwide.

4. Portability

It is simple to use the structured query language on desktop computers, laptops, tablets, and even smartphones. Depending on the needs of the user, it can also be utilised with different applications.

5. Interactive language

The SQL language is easy enough for us to learn and comprehend. Since this language is straightforward query language, we can also use it to communicate with the database. In a matter of seconds, one can also use this language to get complex query answers.

 

PL/SQL

PL/SQL, which stands for “Procedural Language/Structured Query Language,” is a programming language that is used to interact with relational database management systems (RDBMS). 

PL/SQL is an extension of SQL (Structured Query Language) and is often used in conjunction with Oracle Database, although it can be found in other database systems as well.PL/SQL allows developers to create stored procedures, functions, triggers, packages, and other database objects that can be stored in the database and executed as needed. These database objects can contain SQL statements and procedural constructs, making it possible to perform complex data manipulation and business logic within the database itself.

Some key features and uses of PL/SQL include:

Procedural Constructs

Data Manipulation

Modularity

Transaction Control 

Error Handling

Triggers

Security

PL/SQL is widely used in enterprise applications to improve performance, maintain data integrity, and encapsulate business logic within the database. It is particularly popular in Oracle Database environments, but similar features and capabilities are available in other database systems, often with their own extensions to SQL for procedural programming

 

 
 

ETL

ETL stands for extract, transform, and load and is a traditionally accepted way for organizations to combine data from multiple systems into a single database, data store, data warehouse, or data lake. ETL can be used to aggregate data for analysis and decision-making, or it can be used to store legacy data, as is more common today. 


ETL TOOLS

ETL (Extract, Transform, Load) tools are used for extracting data from various sources, transforming it into the desired format, and loading it into a target data repository such as a data warehouse. There are numerous ETL tools available, ranging from open-source to commercial solutions. Here are some of the most popular types of ETL tools:



Open-Source ETL Tools:

Apache Nifi 

Talend Open Studio

Apache Camel

Kettle (Pentaho Data Integration)

Commercial ETL Tools:

Informatica PowerCenter

Microsoft SQL Server Integration Services (SSIS)

IBM InfoSphere DataStage

SAS Data Integration Studio

Cloud-Based ETL Tools:

AWS Glue

Google Cloud Dataflow

Microsoft Azure Data Factory

Specialized ETL Tools:

Talend for Big Data

HVR

Attunity

Self-Service ETL Tools:

Alteryx

Trifacta 

Tableau Prep 

Streaming ETL Tools:

Apache Kafka
Apache Flink
StreamSets
Data Migration ETL Tools:
AWS Database Migration Service (DMS)
Microsoft Azure Database Migration Service

 

The choice of ETL tool depends on the specific needs of an organization, including the complexity of data integration, the scale of data processing, and budget considerations. Some organizations may use a combination of tools to meet different ETL requirements within their data ecosystem.

Bi Development

Business Intelligence (BI) development is the process of creating and implementing software, systems, and strategies that enable organizations to gather, process, analyze, and visualize data to make informed business decisions. It involves a combination of data management, data analysis, and software development to provide insights into an organization’s operations, performance, and trends. The primary objectives of BI development are to turn raw data into meaningful information and support data-driven decision-making within the organization.


BI development often involves the use of specialized BI tools and platforms that offer user-friendly interfaces for creating reports and dashboards. These tools may leverage SQL and other query languages for data access and manipulation. BI developers work closely with data engineers, business analysts, and stakeholders to design and maintain an effective BI solution that empowers organizations to make data-driven decisions and gain a competitive edge.

TECHNOLOGIES:

Business Intelligence (BI) technologies encompass a wide range of tools, platforms, and techniques that enable organizations to gather, analyze, and visualize data to make informed decisions. These technologies are essential for turning raw data into actionable insights. Here are some key BI technologies :

Data Warehousing:                                        

ETL (Extract, Transform, Load)     

Data Integration

Data Modeling

BI Reporting and Visualization

Ad Hoc Query and Analysis

Data Analytics

Big Data Technologies

Data Governance and Metadata Management

Data Security and Access Control

Cloud BI Services

Machine Learning and AI

Data Streaming and Real-time Analytics

Data Virtualization

Self-Service BI

Job Roles

Database Administrator (DBA)

Database Developer

Database Testers

Data Scientist

ETL Developer

Database Migration Expert

Cloud Database Expert

Data Quality Analyst

Database Consultant

Data Warehouse Architect

SQL Developer

PL/SQL Developer

ETL Developer

SALARY

The average salary  ranges from  approximately from 13 Lakhs to ₹35 Lakhs Per Annum.

Course Highlights:

1- Suited for students, fresher’s, professionals, and corporate employees

2- Live online classes

3- 4-month program

4- Certificate of completion 

5- Decision Oriented Program of Analysis

6- Live Classes by highly experienced faculties

7- Hands-on experience with real-life case studies

 

Conclusion

In summary, SQL, PL/SQL, ETL, and BI development are interconnected components of a comprehensive data management and analysis ecosystem. SQL and PL/SQL handle data management and application development within the database, while ETL processes ensure data is appropriately prepared for analysis. Finally, BI development presents the data in a way that is understandable and actionable to business users. Together, they enable organizations to harness the power of their data for better decision-making and business insights. 

Proficiency in SQL, PL/SQL, ETL, and BI development is valuable in today’s data-driven world, and individuals with these skills are in high demand . Depending on your interests and career goals, you can pursue a career path   that aligns with your strengths and preferences within the broader data management and analysis domain.


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