41 lines
2.6 KiB
Markdown
41 lines
2.6 KiB
Markdown
# Data Analytics
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## What is Data Analytics?
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Data Analytics is the process of examining raw data to uncover patterns, correlations, trends, and insights that can support better decision-making. It involves collecting, cleaning, processing, and interpreting data using statistical, programming, and visualization techniques.
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## Why is Data Analytics Used?
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- To make data-driven decisions.
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- To identify patterns and predict future trends.
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- To improve efficiency and reduce costs.
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- To understand customer behavior and enhance experiences.
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- To detect risks or fraud in business operations.
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- To support strategic planning with evidence-based insights.
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## Role and Responsibilities of a Data Analyst
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- **Data Collection** - Gather data from multiple sources (databases, APIs, spreadsheets, etc.).
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- **Data Cleaning & Preparation** – Handle missing values, remove duplicates, standardize formats.
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- **Exploratory Data Analysis (EDA)** – Find patterns, trends, and relationships.
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- **Data Visualization** – Present insights via dashboards, charts, and graphs.
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- **Reporting & Communication** – Share findings with stakeholders in business-friendly language.
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- **Statistical & Predictive Analysis** – Use models to forecast and simulate scenarios.
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- **Collaboration** – Work with business, data engineers, and data scientists to improve systems.
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## Tools Required for Data Analytics
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Here’s a categorized list with official download links and why they’re used:
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### 1. [Python](https://www.python.org/downloads/)
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**Uses:** Widely used for data analysis, machine learning, and automation with powerful libraries like Pandas, NumPy, Matplotlib, and Scikit-learn.
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### 2. [Excel (with Power Query & Power Pivot)](https://www.microsoft.com/en-us/microsoft-365/excel)
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**Uses:** Essential for data manipulation, cleaning, and reporting. Power Query enables data extraction and transformation, while Power Pivot helps with data modeling and analysis.
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### 3. [Tableau (Public Edition)](https://public.tableau.com/en-us/s/download)
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**Uses:** Provides intuitive drag-and-drop dashboards for data visualization and storytelling, making insights easy to understand.
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### 4. [Power BI (Desktop)](https://www.microsoft.com/en-us/download/details.aspx?id=58494)
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**Uses:** Microsoft’s business intelligence tool, great for interactive dashboards and integrates seamlessly with Excel and databases.
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### 5. [MySQL (Community Server)](https://dev.mysql.com/downloads/mysql/)
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**Uses:** A popular open-source relational database for storing, managing, and querying structured data efficiently.
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