Learn about the three most essential statistical tests in data science — t-test, chi-square test, and ANOVA. Understand their use cases, assumptions, and real-world applications for better data-driven decisions. Introduction Statistical tests  are crucial instruments in data science  for data-driven decision-making. They assist in determining whether the patterns we observe in data are purely coincidental or significant. These tests give you a scientific basis for your conclu

Introduction In today’s data-driven world, the role of a Business Analyst (BA)  has evolved far beyond writing documents and gathering requirements. Modern organizations expect BAs to combine analytical thinking, technical fluency, and business acumen to drive measurable outcomes. Whether it’s improving a conversion funnel, automating a reporting process, or defining KPIs for new features — BAs are the bridge between strategy and execution. This “Top 50 Business Analyst Inter

Introduction This final section focuses on forecasting, applied business mathematics, and real-world problem-solving , where companies expect Business Analysts to use math and statistics to drive decisions. For roles offering ₹12 LPA and above, employers test not just formulas — but your ability to interpret numbers in business contexts like sales forecasting, ROI analysis, and KPI tracking. Each question below is designed to strengthen your logical thinking, improve your co

Introduction Once you understand descriptive statistics and probability, the next step in your analytical journey is learning how to test assumptions and model business relationships . That’s where hypothesis testing, regression, and forecasting  come in. In Part 2  of our series, we dive deep into the methods that Business Analysts use to validate ideas, uncover patterns, and make predictions . You’ll learn about null and alternative hypotheses, p-values, t-tests, ANOVA, reg

Introduction In today’s analytics-driven business world, financial understanding is no longer reserved just for accountants or investment bankers — it’s a must-have skill for Business Analysts  and Data Analysts . Whether you’re analyzing revenue trends, building dashboards for management, or evaluating business performance, knowing the language of finance helps you connect data with real business outcomes. At IOTA Academy , we believe that financial analysis is the backbone

Introduction Microsoft Excel and Google Sheets are two of the most essential tools for any Business Analyst. From data cleaning and organization to complex analysis and visualization, these tools form the foundation of analytical decision-making in every modern organization. Recruiters hiring for Business Analyst roles — especially at premium packages like 12 LPA — expect candidates to be proficient not only in using basic formulas but also in applying advanced functions, piv

In the world of business analytics, data is the foundation of every decision — and SQL remains the most essential skill for anyone aspiring to become a Business Analyst. Whether you’re working with structured databases like MySQL, SQL Server, or PostgreSQL , or unstructured systems like MongoDB , the ability to extract, clean, and analyze data efficiently is what differentiates a good analyst from a great one. This comprehensive guide — “Top 100 SQL, MySQL, SQL Server, Postgr

Learn how to use SQL Window Functions like ROW_NUMBER(), RANK(), LAG(), and SUM() OVER() to analyze data efficiently. Master SQL analytics and elevate your data skills. Introduction SQL is the cornerstone of data analysis and manipulation. While most users are familiar with SELECT, WHERE, and GROUP BY, few explore one of SQL’s most powerful and often underutilized features - Window Functions . If you've ever struggled to calculate rolling averages, rank items within groups, o

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