Category: College Passout Series
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Exploratory Data Analysis: Finding the Story in Your Data (Data Analyst Series, Part 10)
Exploratory data analysis is the poke-around phase where a clean table turns into a story. Learn to summarise, read distributions, spot outliers and find relationships before you report anything.
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Cleaning Messy Data: Missing Values, Duplicates and Inconsistent Labels (Data Analyst Series, Part 9)
Real exports arrive broken. Learn to profile a dataset and fix the five recurring problems, missing values, duplicates, inconsistent text, wrong types and outliers, in a repeatable order.
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SQL GROUP BY, Aggregations and Window Functions Explained (Data Analyst Series, Part 8)
Collapse many rows into one number with GROUP BY and the aggregate functions, filter groups with HAVING, then keep every row while ranking and running totals with window functions.
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SQL Joins: Combining Tables with INNER and LEFT JOIN (Data Analyst Series, Part 7)
Learn SQL joins the practical way. INNER JOIN keeps matches, LEFT JOIN keeps every row, and the ON versus WHERE trap that quietly drops the rows you need.
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SQL SELECT, WHERE and ORDER BY: Your First Queries (Data Analyst Series, Part 6)
Write your first real SQL queries. SELECT to choose columns, WHERE to filter rows, ORDER BY to sort and LIMIT to cap, all against a five-row sample table.
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How Data Is Stored: Tables, Types, CSV Files and Databases (Data Analyst Series, Part 5)
Tables, data types, CSV files and databases explained for beginners, so the SQL in the next parts reads like plain sentences instead of a puzzle.
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Spreadsheet Formulas and Pivot Tables That Do Real Work (Data Analyst Series, Part 4)
Two spreadsheet features do most of an analyst’s real work: conditional formulas like SUMIFS and pivot tables. Here is how to use both to answer a question in seconds instead of scrolling for an hour.
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How to Think in Data: Questions, Metrics and Hypotheses (Data Analyst Series, Part 3)
Analysis starts with a sharp question, not a spreadsheet. Here is how to turn a vague request into a clear question, the right metric, and a hypothesis the data can actually test.
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The Analyst Toolkit and a Skills Roadmap for Beginners (Data Analyst Series, Part 2)
The four tools a data analyst actually uses, spreadsheets, SQL, a BI tool, and Python, and the order to learn them in so you become employable in a few months.
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What a Data Analyst Really Does, vs Data Scientist and Data Engineer (Data Analyst Series, Part 1)
A plain, beginner-friendly breakdown of what a data analyst actually does day to day, how the job differs from data scientist and data engineer, and what the three roles pay.
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Customize Your Shell Environment: bashrc, Aliases, and PATH (Linux for Beginners, Part 23)
Your alias works in the terminal but not in cron because the shell reads different startup files depending on how it launched. Login vs non-login, .bashrc, aliases, PATH, and the prompt.
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Grow Storage With LVM Logical Volumes (Linux for Beginners, Part 22)
Fixed partitions are rigid; LVM puts a flexible layer between disks and filesystems so you can grow a full volume onto a new disk with no downtime. PVs, VGs, LVs, and snapshots.
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About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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