AISkillWalaData analyst ka kaam "data dekhna" nahi, business ke sawaal ka jawab dena hai: kya bik raha hai, kya nahi, kyun, aur aage kya karein. Is lesson mein samjho ki ye kaam roz kaisa dikhta hai, kaunse tools chahiye, aur ye course tumhe kahan tak le jayega.
1Roz ka kaam
Ek analyst ke din mein aam taur pe ye hota hai:
- Sawaal aata hai: "Pichhle mahine sales kyun giri?"
- Data nikalna: Excel file, company ka database (SQL), ya kisi tool se export.
- Saaf karna: galat entries, duplicates, khaali cells.
- Analysis: total, trend, tulna (is mahina vs pichhla).
- Batana: chart, dashboard ya 3-4 line ka message manager ko.
Job titles jo isi kaam ke hote hain: Data Analyst, MIS Executive, Business Analyst (junior), Reporting Analyst.
2Tools: kya zaroori, kya baad mein
- Excel / Google Sheets: sabse zaroori. Pehle wala Excel course poora kar chuke ho toh achha.
- SQL: database se data nikalne ki bhasha. Lagbhag har analyst job mein maangi jaati hai.
- Dashboard tool: Looker Studio (Google ka, free, browser mein), Power BI Desktop (free, sirf Windows), ya Tableau Public.
- Python: baad mein, jab basics pakke ho jaayein. Shuruaati naukri ke liye zaroori nahi.
Is course mein Excel/Sheets, SQL aur Looker Studio, teeno free tools se seekhoge.
3Practice files set karo
Poore course mein ek hi data use hoga: ek online dukaan ke Jan-Mar 2026 ke 24 orders aur 8 customers. Har lesson ke jawab isi data se check honge.
- Neeche se orders.csv download karo (lesson 2 mein customers.csv bhi milegi).
- Google Drive kholo, "Data Analysis Course" naam ka folder banao.
- File ko Google Sheets mein kholo (File, Import, Upload) ya Excel mein.
- Dekho: har row ek order hai, columns hain order_id, order_date, customer_id, product, category, qty, price.
Example: Maan lo: ek sawaal, poora kaam
Maan lo dukaan ka malik poochhta hai: "Electronics badhaayein ya Home items?" Analyst data se dekhega ki 3 mahine mein Electronics se ₹8,689 aaye aur Home se ₹3,430, yaani kul bikri ka lagbhag 61% Electronics se. Phir woh ek line mein batayega: "Electronics paisa laata hai; stock pehle wahi rakho." Yahi kaam hai: sawaal → data → jawab.
Aam galtiyan
- Shuru mein hi Python ya machine learning pe kood jaana, jabki naukri Excel aur SQL se milti hai.
- Sirf tools seekhna aur business ke sawaal samajhna bhool jaana.
- Data saaf kiye bina seedha chart bana dena.
Practice task
orders.csv ko Sheets ya Excel mein kholo. Bina formula ke, sirf dekh ke likho: kitne orders hain, kaunsi 3 categories hain, aur data kis mahine se kis mahine tak ka hai.
Jaldi se recap
- Kaam: sawaal → data → saaf → analysis → batana
- Must: Excel/Sheets + SQL
- Dashboard: Looker Studio (free) / Power BI (Windows)
- Python baad mein
- Titles: Data Analyst, MIS, Reporting Analyst
A data analyst's job is not "looking at data"; it is answering business questions: what is selling, what is not, why, and what to do next. In this lesson, see what this work looks like day to day, which tools you need, and how far this course will take you.
1The daily work
An analyst's day usually includes:
- A question arrives: "Why did sales drop last month?"
- Getting data: an Excel file, the company database (SQL), or an export from a tool.
- Cleaning it: wrong entries, duplicates, blank cells.
- Analysis: totals, trends, comparisons (this month vs last).
- Telling people: a chart, a dashboard or a 3-4 line message to the manager.
Job titles for this work: Data Analyst, MIS Executive, Business Analyst (junior), Reporting Analyst.
2Tools: what you need now, what later
- Excel / Google Sheets: the most essential. Good if you have finished the Excel course.
- SQL: the language for getting data out of databases. Asked for in almost every analyst job.
- A dashboard tool: Looker Studio (Google's, free, in the browser), Power BI Desktop (free, Windows only), or Tableau Public.
- Python: later, once the basics are solid. Not required for a first job.
In this course you will learn Excel/Sheets, SQL and Looker Studio, all three free tools.
3Set up the practice files
The whole course uses one dataset: 24 orders and 8 customers of an online shop from Jan-Mar 2026. Every lesson's answers are checked against this data.
- Download orders.csv below (you will get customers.csv in lesson 2).
- Open Google Drive and create a folder called "Data Analysis Course".
- Open the file in Google Sheets (File, Import, Upload) or in Excel.
- Look: each row is one order; the columns are order_id, order_date, customer_id, product, category, qty, price.
Example: Say: one question, the whole job
Say the shop owner asks: "Should we grow Electronics or Home items?" The analyst sees from the data that in 3 months Electronics brought ₹8,689 and Home ₹3,430, so about 61% of all sales came from Electronics. Then they say it in one line: "Electronics brings the money; stock it first." That is the job: question → data → answer.
Common mistakes
- Jumping straight into Python or machine learning, when jobs come from Excel and SQL.
- Learning only tools and forgetting to understand the business question.
- Making charts without cleaning the data first.
Practice task
Open orders.csv in Sheets or Excel. Without formulas, just by looking, write: how many orders there are, the 3 categories, and which months the data covers.
Quick recap
- Work: question → data → clean → analysis → tell
- Must: Excel/Sheets + SQL
- Dashboard: Looker Studio (free) / Power BI (Windows)
- Python later
- Titles: Data Analyst, MIS, Reporting Analyst
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