Data Analysis Resources TP Data Analytics . Power BI . Data Visualization

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Data Analysis Resources TP Data Analytics . Power BI . Data Visualization

May 5, 2026, 02:28 PM

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Data Analysis Resources TP Data Analytics . Power BI . Data Visualization

May 5, 2026, 02:28 PM

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Data Analysis Resources TP Data Analytics . Power BI . Data Visualization

May 5, 2026, 02:28 PM

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Data Analysis Resources TP Data Analytics . Power BI . Data Visualization

May 5, 2026, 02:28 PM

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Data Analysis Resources TP Data Analytics . Power BI . Data Visualization

May 5, 2026, 02:28 PM

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Data Analysis Resources TP Data Analytics . Power BI . Data Visualization

May 5, 2026, 02:28 PM

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Data Analysis Resources TP Data Analytics . Power BI . Data Visualization

May 5, 2026, 02:28 PM

Essential Excel Functions for Data Analysts 🚀

1️⃣ Basic Functions

SUM() – Adds a range of numbers. =SUM(A1:A10)

AVERAGE() – Calculates the average. =AVERAGE(A1:A10)

MIN() / MAX() – Finds the smallest/largest value. =MIN(A1:A10)

2️⃣ Logical Functions

IF() – Conditional logic. =IF(A1>50, "Pass", "Fail")

IFS() – Multiple conditions. =IFS(A1>90, "A", A1>80, "B", TRUE, "C")

AND() / OR() – Checks multiple conditions. =AND(A1>50, B1<100)

3️⃣ Text Functions

LEFT() / RIGHT() / MID() – Extract text from a string.

=LEFT(A1, 3) (First 3 characters)

=MID(A1, 3, 2) (2 characters from the 3rd position)

LEN() – Counts characters. =LEN(A1)

TRIM() – Removes extra spaces. =TRIM(A1)

UPPER() / LOWER() / PROPER() – Changes text case.

4️⃣ Lookup Functions

VLOOKUP() – Searches for a value in a column.

=VLOOKUP(1001, A2:B10, 2, FALSE)

HLOOKUP() – Searches in a row.

XLOOKUP() – Advanced lookup replacing VLOOKUP.

=XLOOKUP(1001, A2:A10, B2:B10, "Not Found")

5️⃣ Date & Time Functions

TODAY() – Returns the current date.

NOW() – Returns the current date and time.

YEAR(), MONTH(), DAY() – Extracts parts of a date.

DATEDIF() – Calculates the difference between two dates.

6️⃣ Data Cleaning Functions

REMOVE DUPLICATES – Found in the "Data" tab.

CLEAN() – Removes non-printable characters.

SUBSTITUTE() – Replaces text within a string.

=SUBSTITUTE(A1, "old", "new")

7️⃣ Advanced Functions

INDEX() & MATCH() – More flexible alternative to VLOOKUP.

TEXTJOIN() – Joins text with a delimiter.

UNIQUE() – Returns unique values from a range.

FILTER() – Filters data dynamically.

=FILTER(A2:B10, B2:B10>50)

8️⃣ Pivot Tables & Power Query

PIVOT TABLES – Summarizes data dynamically.

GETPIVOTDATA() – Extracts data from a Pivot Table.

POWER QUERY – Automates data cleaning & transformation.

You can find Free Excel Resources here:
Hope it helps :)

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Data Analysis Resources TP Data Analytics . Power BI . Data Visualization

May 5, 2026, 02:28 PM

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SQL Joins ✅

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Data Analysis Resources TP Data Analytics . Power BI . Data Visualization

May 5, 2026, 02:28 PM

Data Analyst Scenario based Question and Answers 👇👇

1. Scenario: Creating a Dynamic Sales Growth Report in Power BI
Approach:
Load Data: Import sales data and calendar tables.
Data Model: Establish a relationship between the sales and calendar tables.
Create Measures:
Current Sales: Current Sales = SUM(Sales[Amount]).
Previous Year Sales: Previous Year Sales = CALCULATE(SUM(Sales[Amount]), DATEADD(Calendar[Date], -1, YEAR)).
Sales Growth: Sales Growth = [Current Sales] - [Previous Year Sales].
Visualization:
Use Line Chart for trends.
Use Card Visual for displaying numeric growth values.
Slicers and Filters: Add slicers for selecting specific time periods.

2. Scenario: Identifying Top 5 Customers by Revenue in SQL
Approach:
Understand the Schema: Know the relevant tables and columns, e.g., Orders table with CustomerID and Revenue.
SQL Query:
SELECT TOP 5 CustomerID, SUM(Revenue) AS TotalRevenue
FROM Orders
GROUP BY CustomerID
ORDER BY TotalRevenue DESC;

3. Scenario: Creating a Monthly Sales Forecast in Power BI
Approach:
Load Historical Data: Import historical sales data.
Data Model: Ensure proper relationships.
Time Series Analysis:
Use built-in Power BI forecasting features.
Create measures for historical and forecasted sales.
Visualization:
Use a Line Chart to display historical and forecasted sales.
Adjust Forecast Parameters: Customize the forecast length and confidence intervals.

4. Scenario: Updating a SQL Table with New Data
Approach:
Understand the Schema: Identify the table and columns to be updated.
SQL Query:
UPDATE Employees
SET JobTitle = 'Senior Developer'
WHERE EmployeeID = 1234;

5. Scenario: Creating a Custom KPI in Power BI
Approach:
Define KPI: Identify the key performance indicators.
Create Measures:
Define the KPI measure using DAX.
Visualization:
Use KPI Visual or Card Visual.
Configure the target and actual values.
Conditional Formatting: Apply conditional formatting based on the KPI thresholds.

Data Analytics Resources
👇👇


Hope it helps :)

Data Analysis Resources TP Data Analytics . Power BI . Data Visualization

May 5, 2026, 02:28 PM

🔰 SQL Roadmap for Beginners 2025
├── 🗃 Introduction to Databases & SQL
├── 📄 SQL vs NoSQL (Just Basics)
├── 🧱 Database Concepts (Tables, Rows, Columns, Keys)
├── 🔍 Basic SQL Queries (SELECT, WHERE)
├── ✏️ Filtering & Sorting Data (ORDER BY, LIMIT)
├── 🔢 SQL Operators (IN, BETWEEN, LIKE, AND, OR)
├── 📊 Aggregate Functions (COUNT, SUM, AVG, MIN, MAX)
├── 👥 GROUP BY & HAVING Clauses
├── 🔗 SQL JOINS (INNER, LEFT, RIGHT, FULL, SELF)
├── 📦 Subqueries & Nested Queries
├── 🏷 Aliases & Case Statements
├── 🧾 Views & Indexes (Basics)
├── 🧠 Common Table Expressions (CTEs)
├── 🔄 Window Functions (ROW_NUMBER, RANK, PARTITION BY)
├── ⚙️ Data Manipulation (INSERT, UPDATE, DELETE)
├── 🧱 Data Definition (CREATE, ALTER, DROP)
├── 🔐 Constraints & Relationships (PK, FK, UNIQUE, CHECK)
├── 🧪 Real-world SQL Scenarios & Challenges

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