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𝐒𝐨𝐦𝐞 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐭𝐨𝐩𝐢𝐜𝐬 𝐟𝐨𝐫 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐢𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰s:

𝑺𝑸𝑳:

1. Basic
• SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING
• Basic JOINS (INNER, LEFT, RIGHT, FULL)
• Creating and using simple databases and tables
• Understanding database normalization concepts
• Using aliases for table and column names

2. Intermediate

• Aggregate functions (COUNT, SUM, AVG, MAX, MIN)
• Subqueries and nested queries
• Common Table Expressions (WITH clause)
• CASE statements for conditional logic in queries
• Working with date and time functions

3. Advanced

• Advanced JOIN techniques (self-join, non-equi join)
• Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag)
• Optimization techniques for query performance
• Handling large datasets with partitioning and views
• Using stored procedures and user-defined functions for complex tasks

𝐄𝐱𝐜𝐞𝐥:

1. Basic
• Cell operations, basic formulas (SUMIFS, COUNTIFS, AVERAGEIFS, IF, AND, OR, NOT & Nested Functions etc.)
• Introduction to charts and basic data visualization
• Data sorting and filtering
• Conditional formatting
• Using named ranges and data validation

2. Intermediate

• Advanced formulas (V/XLOOKUP, INDEX-MATCH, nested IF)
• PivotTables and PivotCharts for summarizing data
• Data validation tools
• What-if analysis tools (Data Tables, Goal Seek)
• Advanced charting techniques (combo charts, secondary axes)

3. Advanced

• Array formulas and advanced functions
• Data Model & Power Pivot
• Advanced Filter
• Slicers and Timelines in Pivot Tables
• Dynamic charts and interactive dashboards
• Excel macros and VBA programming for automation

𝐏𝐨𝐰𝐞𝐫 𝐁𝐈:

1. Data Modeling
• Importing data from various sources
• Creating and managing relationships between different datasets
• Data modeling basics (star schema, snowflake schema)
• Dataflows and data preparation techniques

2. Data Transformation

• Using Power Query for data cleaning and transformation
• Advanced data shaping techniques
• Calculated columns and measures using DAX
• Power Query M language for custom transformations

3. Data Visualization and Reporting

• Creating interactive reports and dashboards
• Visualizations (bar, line, pie charts, maps)
• Publishing and sharing reports, scheduling data refreshes
• Advanced formatting and design options

🚀 My Google Interview Journey 🌟

Excited to share my Google interview experience for the Cloud Engineer, Web Applications Role! Here's a breakdown:

🔹 Application: Applied via LinkedIn Jobs with a strong resume.

🔹 Recruitment: A Google recruiter reached out, discussing the job description and gauging my expertise.

🔹 Preparation: After a screening round, I had 3 weeks to gear up for the next stages.

🔹 Rounds:

Technical Focus: Covered system design, DSA, and live coding.
Deep Dive: More technical rounds on DSA, system design, and infrastructure/APIs.
Leadership: Explored behavioral, leadership, and teamwork skills.
Database Design: Delved into schema design and SQL implementation.
🔹 Outcome: Received the result within 1-2 weeks post-final round.

The process took around 2-3 months but was worth it! 💼✨

Follow these tips for interview prep and share your success stories! #Google #InterviewTips #Google #faang #interview #ProblemSolving #algorithm #programming #coding #dsa #dsanotes #data

🚀 Exciting News! 🚀
https://youtu.be/lOl7InrTnHQ
My latest YouTube tutorial: "C# Project Tutorial: Restaurant Management System💻 with SQL Database | .NET Project". Dive into the world of C# programming as we explore the creation of a comprehensive Restaurant Management System integrated with SQL database using .NET technology.

🔍 In this tutorial, we'll cover:
✅ Setting up the project environment
✅ Designing the database schema
✅ Implementing CRUD operations
✅ Creating a user-friendly interface
✅ Enhancing functionality with C# programming

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👍 Don't forget to like the video, subscribe to my channel, and share it with your network to spread the knowledge! Let's code together and empower each other's growth! 🌟

❌❌ Avoid the Pitfalls of "Auto Shrink" in SQL Server! ❌❌

📢 Introduction: Database administrators, beware of the Auto Shrink option in SQL Server. While it may seem convenient, enabling it could lead to more headaches than solutions. Let's explore why it's best to think twice before flicking that switch.

🚫 Resource Drain: Enabling Auto Shrink means constant file resizing, hogging valuable I/O, CPU, and locking resources. Picture a server juggling tasks amidst a never-ending resizing dance. Not a pretty sight, huh?

🔗 Index Woes: Shrinking databases spells trouble for indexes, fragmenting them and slowing down queries. Think of it like a puzzle missing pieces—queries struggle to piece together the data efficiently.

📉 Performance Hit: Auto Shrink can slam the brakes on performance. Shrinking followed by data operations? Get ready for a slowdown. It's like hitting traffic after a quick detour.

🔒 Locking Chaos: The Auto Shrink task competes for resources, potentially disrupting regular operations. Balancing shrinking needs with daily tasks is key.

📌 Conclusion: Ditch Auto Shrink and opt for manual sizing instead. Keep your databases tidy and spacious, just like a well-organized closet. No unnecessary resizing clutter allowed! #SQLServer #DatabaseManagement #PerformanceTips #IndexFragmentation #ResourceManagement 🛠📊

❌ Avoid the Auto Shrink Trap in SQL Server! ❌

Here's why enabling auto shrink is a big no-no for your database:

🧩 Index Fragmentation: Auto shrink leads to fragmented indexes, hampering database performance.

💻 Resource Drain: Shrink operations gobble up IO and CPU resources, causing disk queues and timeouts.

🔄 File System Fragmentation: Shrinking and growing files repeatedly results in file-system fragmentation, slowing performance.

📈 Disk Fragmentation: Incremental growth and shrinkage lead to disk fragmentation, causing performance issues.

⏳ Server Slowdown: Shrinking is a heavy operation, slowing down your database server significantly.

🎲 Unpredictable: Auto shrink can kick in at any time, even during peak hours, making it unpredictable and potentially disruptive.

Avoid the auto shrink headache and keep your database running smoothly! #DatabaseManagement #PerformanceIssues #ResourceDrain 🛑💡

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Understanding Primary Constructors in C#

Objective:
Explore the concept of primary constructors in C# and understand their significance in simplifying class initialization.

Introduction:
C# 12 introduced primary constructors, a feature widely used in modern programming. They offer a streamlined approach to class initialization, making code cleaner and more efficient.

Why do we need them?
Traditionally, when injecting something into classes or records, we needed to introduce backing fields for internal use. This approach was almost the same:

Introduction of backing fields
Introduction of constructor
Initialization of the original field in the constructor
Use internally
The Role of Primary Constructors:
With primary constructors, achieving the same result is much simpler:

Declare the dependency in the primary constructor
Use internally
This results in a much simpler process, eliminating the need for additional fields and constructors.

Assignment Tasks:

Explore the concept of primary constructors in C#.
Implement primary constructors in a sample class or record.
Compare the simplicity of using primary constructors with traditional approaches.
Share your findings and insights.
Conclusion:
Primary constructors in C# offer a more elegant and concise way to initialize classes, simplifying code and enhancing readability. Embrace this feature to streamline your programming experience.

🚀 Have you tried using primary constructors in your code? Share your experience with us! 🔍

Understanding Primary Constructors in C#

Objective:
Explore the concept of primary constructors in C# and understand their significance in simplifying class initialization.

Introduction:
C# 12 introduced primary constructors, a feature widely used in modern programming. They offer a streamlined approach to class initialization, making code cleaner and more efficient.

Why do we need them?
Traditionally, when injecting something into classes or records, we needed to introduce backing fields for internal use. This approach was almost the same:

Introduction of backing fields
Introduction of constructor
Initialization of the original field in the constructor
Use internally
The Role of Primary Constructors:
With primary constructors, achieving the same result is much simpler:

Declare the dependency in the primary constructor
Use internally
This results in a much simpler process, eliminating the need for additional fields and constructors.

Share your experience with us! 🔍

---Banking System Database----------------
create database Bank
go

use bank
go

------------create branch table-------------
CREATE TABLE Branch
(
id INT primary key,
name VARCHAR(50) UNIQUE,
address VARCHAR(50)
)

CREATE TABLE Card
(
id INT PRIMARY KEY,
number varchar(50) unique,
expiration_date date,
is_blocked bit
)


CREATE TABLE Loan_type
(
id int primary key,
type varchar(10) unique,
description varchar(100),
base_amount decimal(10,3),
base_interest_rate decimal(10,3)
)



CREATE TABLE Customer
(
id int primary key,
branch_id int,
first_name varchar(50),
last_name varchar(50),
date_of_birth date,
gender char(1) check (gender in ('M','F','O')),
Foreign key (branch_id) references Branch(id) on update cascade on delete set null
)

CREATE TABLE Account
(
id int primary key,
customer_id int,
card_id int,
balance char(50),
foreign key (customer_id) references Customer(id) on update cascade on delete set null,
foreign key (card_id) references Card(id) on update cascade on delete set null
)

CREATE TABLE Loan
(
id int primary key,
account_id int,
loan_type_id int,
amount_paid decimal(10,3),
start_date date,
due_date date,
foreign key (account_id) references Account(id) on update cascade on delete set null,
foreign key(loan_type_id) references Loan_type(id) on update cascade on delete set null
)

CREATE TABLE [Transaction]
(
id int primary key,
account_id int,
[description] varchar(100),
amount decimal(10,3),
[date] date,
foreign key (account_id) references Account(id) on update cascade on delete set null
)


---Insert record into Branch table------

INSERT INTO Branch(id,name,address) VALUES(1,'Allahabad Bank','Allahabad')
INSERT INTO Branch(id,name,address) VALUES(2,'Bank of Baroda','Varanasi')
INSERT INTO Branch(id,name,address) VALUES(3,'Canara Bank','Kanpur')
INSERT INTO Branch(id,name,address) VALUES(4,'ICICI Bank','Noida')
INSERT INTO Branch(id,name,address) VALUES(5,'Kotak Bank','Delhi')

select * from Branch

--Insert record into Card table---
INSERT INTO Card (id, number, expiration_date, is_blocked) VALUES ('1', '1234567890123456', '2021-01-30', 1);
INSERT INTO Card (id, number, expiration_date, is_blocked) VALUES ('2', '1234567890123457', '2022-08-20', 1);
INSERT INTO Card (id, number, expiration_date, is_blocked) VALUES ('3', '1234567890123458', '2023-03-21', 1);
INSERT INTO Card (id, number, expiration_date, is_blocked) VALUES ('4', '1234567890123459', '2021-01-14', 0);
INSERT INTO Card (id, number, expiration_date, is_blocked) VALUES ('5', '1234567890123450', '2021-06-9', 1);

select * from Card

---Insert record into Loan_type---
INSERT INTO Loan_type (id, type, description, base_amount, base_interest_rate) VALUES (1, 'Mortgages', 'description1', 10000, 15);

INSERT INTO Loan_type (id, type, description, base_amount, base_interest_rate) VALUES (3, 'Appliance', 'description3', 3000, 25);
INSERT INTO Loan_type (id, type, description, base_amount, base_interest_rate) VALUES (4, 'Payday', 'description4', 1000, 50);
INSERT INTO Loan_type (id, type, description, base_amount, base_interest_rate) VALUES (5, 'Business', 'description5', 7000, 35);

select * from Loan_type


---Insert into Customer table----

INSERT INTO Customer (id, branch_id, first_name, last_name, date_of_birth, gender) VALUES (1, 1, 'Paul', 'Panaitescu', '1996-10-7', 'M');
INSERT INTO Customer (id, branch_id, first_name, last_name, date_of_birth, gender) VALUES (2, 3, 'Constantin', 'Tarau', '1998-09-15', 'M');
INSERT INTO Customer (id, branch_id, first_name, last_name, date_of_birth, gender) VALUES (3, 1, 'Marius', 'Munteanu', '1998-07-31', 'M');
INSERT INTO Customer (id, branch_id, first_name, last_name, date_of_birth, gender) VALUES (4, 2, 'Dragos', 'Mocanasu', '1998-12-31', 'F');
INSERT INTO Customer (id, branch_id, first_name, last_name, date_of_birth, gender) VALUES (5, 2, 'Daenerys', 'Targaryen', '1895-10-7', 'F');

select * from Customer

--- Insert into Account---
INSERT INTO Account (id, customer_id, card_id, balance) VALUES (1, 1, 1, '1000');
INSERT INTO Account (id, customer_id, card_id, balance) VALUES (2, 2, 2, '100');
INSERT INTO Account (id, customer_id, card_id, balance) VALUES (3, 3, 3, '200');
INSERT INTO Account (id, customer_id, card_id, balance) VALUES (4, 5, 4, '50000');
INSERT INTO Account (id, customer_id, card_id, balance) VALUES (5, 5, 5, '1000000');

select * from Account

---Insert record for Loan table---

INSERT INTO Loan (id, account_id, loan_type_id, amount_paid, start_date, due_date) VALUES (1, 1, 3, '0', '2020-05-18', '2023-05-18');
INSERT INTO Loan (id, account_id, loan_type_id, amount_paid, start_date, due_date) VALUES (2, 5, 1, '0', '2019-08-12', '2021-05-25');
INSERT INTO Loan (id, account_id, loan_type_id, amount_paid, start_date, due_date) VALUES (3, 4, 2, '100', '2019-05-13', '2024-05-14');
INSERT INTO Loan (id, account_id, loan_type_id, amount_paid, start_date, due_date) VALUES (4, 2, 5, '1000', '2018-05-25', '2021-05-21');
INSERT INTO Loan (id, account_id, loan_type_id, amount_paid, start_date, due_date) VALUES (5, 1, 4, '5000', '2020-05-20', '2023-05-07');
select * from Loan

---Insert record for Transaction table----

INSERT INTO [Transaction] (id, account_id, description, amount, date) VALUES (1, 1, 'description 100', 1000.90, '2020-05-18');
INSERT INTO [Transaction] (id, account_id, description, amount, date) VALUES (2, 2, 'description 200', 500.80, '2019-12-07');
INSERT INTO [Transaction] (id, account_id, description, amount, date) VALUES (3, 5, 'description 300', 100.90, '2018-06-30');
INSERT INTO [Transaction] (id, account_id, description, amount, date) VALUES (4, 5, 'description 400', 5060.7, '2020-01-24');
INSERT INTO [Transaction] (id, account_id, description, amount, date) VALUES (5, 5, 'description 500', 500.67, '2018-01-24');

select * from [Transaction]


-----------The End-----------

📊 Exciting news for aspiring Data Scientists! 🚀

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list of essential programming terms without the plugariasum, adorned with emojis:

Array: A data structure that stores a collection of elements of the same type in contiguous memory locations. 📚
Boolean: A data type that represents true or false values. 🔵🔴
Conditional Statement: A statement that executes different code based on a condition. ⚖️
Debugging: The process of identifying and fixing errors or bugs in a program. 🔍🐛
Exception: An event that occurs during the execution of a program that disrupts the normal flow of instructions. ⚠️
Function: A block of code that performs a specific task and can be called multiple times in a program. 🛠
GUI (Graphical User Interface): A visual way for users to interact with a computer program using graphical elements like windows, buttons, and menus. 💻
HTML (Hypertext Markup Language): The standard markup language used to create web pages. 🌐
Integer: A data type that represents whole numbers without any fractional part. 123
JSON (JavaScript Object Notation): A lightweight data interchange format commonly used for transmitting data between a server and a web application. 📝
Loop: A programming construct that allows repeating a block of code multiple times. 🔁
Method: A function that is associated with an object in object-oriented programming. 🎛
Null: A special value that represents the absence of a value. ⚪️
Object-Oriented Programming (OOP): A programming paradigm based on the concept of "objects" that encapsulate data and behavior. 🧱
Pointer: A variable that stores the memory address of another variable. 📌
Queue: A data structure that follows the First-In-First-Out (FIFO) principle. 🚶‍♂️🚶‍♀️
Recursion: A programming technique where a function calls itself to solve a problem. 🔄
String: A data type that represents a sequence of characters. 📝
Tuple: An ordered collection of elements, similar to an array but immutable. 📦
Variable: A named storage location in memory that holds a value. 📦
While Loop: A loop that repeatedly executes a block of code as long as a specified condition is true. 🔁
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Learn Apps Development
https://youtu.be/pIUmldMrRqs

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