DataAnalyticscourse

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  Here is your task Before any predictive modeling can take place, it’s crucial to ensure that the dataset you’re working with is complete, accurate, and free of inconsistencies.  In this task, you will conduct an  EDA on Geldium’s dataset  to help Tata iQ’s analytics team and Geldium’s decision-makers understand the current state of their data. Your analysis will shape how the company refines its delinquency risk model and improves its intervention strategies. Here are the steps: Step 1: Review the dataset and identify key insights Before predictive modeling can begin, it’s essential to understand the dataset’s structure and assess its quality. In this first step, you'll  examine Geldium’s dataset  to spot any issues and identify early risk indicators. What to do: Open the dataset and review the key columns. Use the  Dataset Description Guide  to understand what each variable represents. Use a GenAI tool (like ChatGPT or DeepSeek) to help quickly...

Solving problems can feel difficult because it involves multiple cognitive processes, such as understanding, analyzing, reasoning, and decision-making . Here are some key reasons why problem-solving is challenging: 🔹 1. Lack of Clear Understanding If a problem is not well-defined, it’s hard to know where to start. Sometimes, missing information or vague instructions make it confusing. ✅ Solution: Break the problem into smaller parts and clarify any doubts before proceeding. 🔹 2. Information Overload Too much data or too many options can lead to paralysis by analysis . The brain struggles to filter out relevant vs. irrelevant information. ✅ Solution: Focus on key details and simplify the problem before attempting a solution. 🔹 3. Lack of a Structured Approach Many people try to guess solutions instead of following a methodical approach. Without a step-by-step strategy , it’s easy to feel lost. ✅ Solution: Use frameworks like: Understand → Plan → Execute → Review (UPE...

  📌 Data Analyst Interview Questions & Answers Here’s a structured list of common Data Analyst interview questions , covering SQL, Excel, Python, Statistics, and Business Acumen . 🔹 1. General & Behavioral Questions ✅ Tell me about yourself. ✅ Why do you want to become a data analyst? ✅ What are the key responsibilities of a data analyst? ✅ Explain a project where you analyzed data to solve a business problem. ✅ How do you handle missing or inconsistent data? ✅ Have you ever worked with large datasets? How did you manage them? ✅ Tell me about a time you presented data insights to non-technical stakeholders. ✅ How do you ensure the accuracy and integrity of data? 🔹 2. SQL Interview Questions (Most Important) ✅ Basic SQL Queries: 1️⃣ Write a query to fetch the top 5 highest-paid employees from an employees table. sql SELECT name, salary FROM employees ORDER BY salary DESC LIMIT 5 ; 2️⃣ Find the total number of orders placed by each customer from...

  📌 Data Analyst vs. Data Engineer: Key Differences Feature Data Analyst 🧐 Data Engineer 🔧 Main Focus Analyzing & interpreting data for insights Building & managing data infrastructure Role in Data Pipeline Works with cleaned & processed data to generate reports Prepares raw data , ensuring it's structured & accessible Key Responsibilities - Data visualization & reporting 📊 - Identifying trends & business insights 📈 - Using statistical methods for analysis - Designing & managing databases 🏗️ - ETL (Extract, Transform, Load) processes ⚙️ - Optimizing data storage & performance 🚀 Tools Used - Power BI, Tableau (Visualization) 🎨 - Excel, SQL (Data manipulation) 🔍 - Python, R (Statistical analysis) - SQL, NoSQL (Databases) 🗄️ - Hadoop, Spark (Big Data) 🔥 - AWS, Azure, GCP (Cloud computing) ☁️ Programming Skills Basic to Intermediate (SQL, Python, R) 📝 Advanced (SQL, Python, Java, Scala) 💻 Data Handling Works with structured & cleaned...