Data Analytics & AI | SQL Interviews | Power BI Resources
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๐Ÿ”“Explore the fascinating world of Data Analytics & Artificial Intelligence

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๐—™๐—ฟ๐—ฒ๐—ฒ ๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ & ๐—Ÿ๐—ถ๐—ป๐—ธ๐—ฒ๐—ฑ๐—œ๐—ป ๐—”๐—œ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐˜๐—ผ ๐—Ÿ๐—ฎ๐—ป๐—ฑ ๐—ง๐—ผ๐—ฝ ๐—๐—ผ๐—ฏ๐˜€ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ๐Ÿ˜

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๐Ÿฑ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐˜๐—ผ ๐—ฆ๐—ธ๐˜†๐—ฟ๐—ผ๐—ฐ๐—ธ๐—ฒ๐˜ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—–๐—ฎ๐—ฟ๐—ฒ๐—ฒ๐—ฟ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ๐Ÿ˜

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1.Define RDBMS.

Answer: Relational Database Management System(RDBMS) is based on a relational model of data that is stored in databases in separate tables and they are related to the use of a common column. Data can be accessed easily from the relational database using Structured Query Language (SQL).

2.Define DML Compiler.

Answer: DML compiler translates DML statements in a query language into a low-level instruction and the generated instruction can be understood by Query Evaluation Engine.

3.Explain the terms โ€˜Recordโ€™, โ€˜Fieldโ€™ and โ€˜Tableโ€™ in terms of database.

Answer:

Record: Record is a collection of values or fields of a specific entity. For Example, An employee, Salary account, etc.

Field: A field refers to an area within a record that is reserved for specific data. For Example, Employee ID.

Table: Table is the collection of records of specific types. For Example, the Employee table is a collection of records related to all the employees.

4.Define the relationship between โ€˜Viewโ€™ and โ€˜Data Independenceโ€™.

Answer: View is a virtual table that does not have its data on its own rather the data is defined from one or more underlying base tables.

Views account for logical data independence as the growth and restructuring of base tables are not reflected in views.
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SQL (Structured Query Language) is a standard programming language used to manage and manipulate relational databases. Here are some key concepts to understand the basics of SQL:

1. Database: A database is a structured collection of data organized in tables, which consist of rows and columns.

2. Table: A table is a collection of related data organized in rows and columns. Each row represents a record, and each column represents a specific attribute or field.

3. Query: A SQL query is a request for data or information from a database. Queries are used to retrieve, insert, update, or delete data in a database.

4. CRUD Operations: CRUD stands for Create, Read, Update, and Delete. These are the basic operations performed on data in a database using SQL:
   - Create (INSERT): Adds new records to a table.
   - Read (SELECT): Retrieves data from one or more tables.
   - Update (UPDATE): Modifies existing records in a table.
   - Delete (DELETE): Removes records from a table.

5. Data Types: SQL supports various data types to define the type of data that can be stored in each column of a table, such as integer, text, date, and decimal.

6. Constraints: Constraints are rules enforced on data columns to ensure data integrity and consistency. Common constraints include:
   - Primary Key: Uniquely identifies each record in a table.
   - Foreign Key: Establishes a relationship between two tables.
   - Unique: Ensures that all values in a column are unique.
   - Not Null: Specifies that a column cannot contain NULL values.

7. Joins: Joins are used to combine rows from two or more tables based on a related column between them. Common types of joins include INNER JOIN, LEFT JOIN (or LEFT OUTER JOIN), RIGHT JOIN (or RIGHT OUTER JOIN), and FULL JOIN (or FULL OUTER JOIN).

8. Aggregate Functions: SQL provides aggregate functions to perform calculations on sets of values. Common aggregate functions include SUM, AVG, COUNT, MIN, and MAX.

9. Group By: The GROUP BY clause is used to group rows that have the same values into summary rows. It is often used with aggregate functions to perform calculations on grouped data.

10. Order By: The ORDER BY clause is used to sort the result set of a query based on one or more columns in ascending or descending order.

Understanding these basic concepts of SQL will help you write queries to interact with databases effectively. Practice writing SQL queries and experimenting with different commands to become proficient in using SQL for database management and manipulation.
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๐Ÿฒ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐˜๐—ผ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐—™๐˜‚๐˜๐˜‚๐—ฟ๐—ฒ-๐—ฃ๐—ฟ๐—ผ๐—ผ๐—ณ ๐—ฆ๐—ธ๐—ถ๐—น๐—น๐˜€ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ๐Ÿ˜

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1. What are the different subsets of SQL?

Data Definition Language (DDL) โ€“ It allows you to perform various operations on the database such as CREATE, ALTER, and DELETE objects.
Data Manipulation Language(DML) โ€“ It allows you to access and manipulate data. It helps you to insert, update, delete and retrieve data from the database.
Data Control Language(DCL) โ€“ It allows you to control access to the database. Example โ€“ Grant, Revoke access permissions.

2. List the different types of relationships in SQL.

There are different types of relations in the database:
One-to-One โ€“ This is a connection between two tables in which each record in one table corresponds to the maximum of one record in the other.
One-to-Many and Many-to-One โ€“ This is the most frequent connection, in which a record in one table is linked to several records in another.
Many-to-Many โ€“ This is used when defining a relationship that requires several instances on each sides.
Self-Referencing Relationships โ€“ When a table has to declare a connection with itself, this is the method to employ.

3. What is a Stored Procedure?

A stored procedure is a subroutine available to applications that access a relational database management system (RDBMS). Such procedures are stored in the database data dictionary. The sole disadvantage of stored procedure is that it can be executed nowhere except in the database and occupies more memory in the database server.

4. What is Pattern Matching in SQL?

SQL pattern matching provides for pattern search in data if you have no clue as to what that word should be. This kind of SQL query uses wildcards to match a string pattern, rather than writing the exact word. The LIKE operator is used in conjunction with SQL Wildcards to fetch the required information.
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๐—•๐—ผ๐—ผ๐˜€๐˜ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐——๐—ฎ๐˜๐—ฎ ๐—ฃ๐—ฟ๐—ผ๐—ฑ๐˜‚๐—ฐ๐˜๐—ถ๐˜ƒ๐—ถ๐˜๐˜† ๐˜„๐—ถ๐˜๐—ต ๐—ง๐—ต๐—ถ๐˜€ ๐—”๐—œ ๐—ง๐—ผ๐—ผ๐—น ๐—˜๐˜ƒ๐—ฒ๐—ฟ๐˜† ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜€๐˜ ๐—ก๐—ฒ๐—ฒ๐—ฑ๐˜€ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ!๐Ÿ˜

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Starting your journey as a data analyst is an amazing start for your career. As you progress, you might find new areas that pique your interest:

โ€ข Data Science: If you enjoy diving deep into statistics, predictive modeling, and machine learning, this could be your next challenge.

โ€ข Data Engineering: If building and optimizing data pipelines excites you, this might be the path for you.

โ€ข Business Analysis: If you're passionate about translating data into strategic business insights, consider transitioning to a business analyst role.

But remember, even if you stick with data analysis, there's always room for growth, especially with the evolving landscape of AI.

No matter where your path leads, the key is to start now.
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๐—™๐—ฟ๐—ฒ๐—ฒ ๐—ข๐—ฟ๐—ฎ๐—ฐ๐—น๐—ฒ ๐—”๐—œ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐˜๐—ผ ๐—•๐—ผ๐—ผ๐˜€๐˜ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—–๐—ฎ๐—ฟ๐—ฒ๐—ฒ๐—ฟ๐Ÿ˜

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Complete Roadmap to learn Power BI ๐Ÿ‘‡๐Ÿ‘‡

Step 1: Power BI Basics
1. Understand the Power BI ecosystem, including Power BI Desktop and Power BI Service.
2. Learn to import data from different sources (Excel, SQL Server, CSV, etc.).
3. Explore Power Query Editor for data transformation and cleaning.
4. Practice creating basic visualizations like bar charts, line charts, and pie charts.

Step 2: Intermediate Power BI
1. Dive deeper into data modeling concepts such as relationships, calculated columns, and
measures.
2. Learn about DAX (Data Analysis Expressions) for advanced calculations and
aggregations.
3. Explore Power BI visuals and custom visuals for enhanced data visualization.
4. Practice creating interactive dashboards and reports with slicers, filters, and drill-down
features.

Step 3: Advanced Power BI
1. Master advanced data modeling techniques like role-playing dimensions and
many-to-many relationships.
2. Learn about Power BI Service features such as workspaces, datasets, and dataflows.
3. Explore Power BI administration and security settings.
4. Practice optimizing performance and refreshing data in Power BI reports.

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