Category: VMware & Cloud
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Presenting Data Analysis to Stakeholders Without Losing the Room (Data Analyst Series, Part 19)
An analyst spent eleven of her fifteen minutes explaining how she cleaned the table, and her recommendation died in the room. This part covers the order, the one sentence and the appendix that get analysis acted on.
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A/B Testing and Experiments Explained Simply (Data Analyst Series, Part 18)
A team shipped a new checkout button, saw a 9 percent lift on day two, and rolled it out. Six weeks later the number was worse than before. This part shows how experiments actually work, and how to stop reading noise as a win.
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Metrics and KPIs: How to Define What Actually Matters (Data Analyst Series, Part 17)
Three dashboards, three different numbers for active users, and all three were right. This part shows you how to define a metric so it means one thing, and how to tell a real KPI from a number that just looks busy.
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Plotting in Python with Matplotlib for Data Analysts (Data Analyst Series, Part 16)
Turn a pandas summary into a chart. Draw a bar, a line and a scatter with Matplotlib, label them, and save them to share, using the same sales data from Part 15.
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Pandas Essentials for Data Analysts: DataFrames, Filtering and Group By (Data Analyst Series, Part 15)
The Python library that reads a file too big for a spreadsheet and answers in a line. A beginner walkthrough of DataFrames, filtering, groupby and missing data in pandas 3.0.
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Your First Dashboard in Power BI or Looker Studio (Data Analyst Series, Part 14)
A plain, beginner walkthrough of building your first dashboard in Looker Studio and Power BI, from connecting data to wiring filters, plus which tool to start with and why.
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Choosing the Right Chart and Avoiding the Ones That Mislead (Data Analyst Series, Part 13)
The chart you pick decides what people believe. Here is how to match bar, line, pie and scatter to your question, and how to spot the truncated axis and dual-axis tricks before they reach your slide.
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Correlation vs Causation: The Traps Between Two Columns (Data Analyst Series, Part 12)
Two columns move together on a chart and someone declares one drives the other. Here is how to tell correlation from causation, spot the confounder, and avoid Simpson’s paradox before it reaches your slide deck.
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Statistics a Data Analyst Actually Uses (Data Analyst Series, Part 11)
The working statistics an analyst uses daily: mean versus median, the standard deviation, the normal curve and its 68, 95, 99.7 rule, percentiles, and the sampling ideas behind margins of error and significance.
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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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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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