What Interviewers Actually Look for in a Fresher Data Analyst

Resume skills section:
Python, R, SQL, Excel, Power BI, Tableau, TensorFlow,
PyTorch, Spark, Hadoop, AWS, Azure, NLP, Deep Learning

Interview:
Q: Write a query for total sales per city, only cities
   above one lakh.
A: (struggles with HAVING vs WHERE)

Result: the long skills list now looks unreliable.

Resume skills section:
SQL (joins, window functions, CTEs), Excel (XLOOKUP,
pivots, COUNTIFS), Power BI (data model, basic DAX),
Python (pandas, matplotlib), Statistics basics

Interview:
Q: Write a query for total sales per city, only cities
   above one lakh.
A: SELECT city, SUM(amount) AS total_sales
   FROM orders
   GROUP BY city
   HAVING SUM(amount) > 100000;

Result: the skills list looks honest and dependable.

WITH product_revenue AS (
  SELECT p.category,
         p.product_name,
         SUM(oi.quantity * oi.unit_price) AS revenue
  FROM order_items oi
  JOIN products p ON p.product_id = oi.product_id
  GROUP BY p.category, p.product_name
),
ranked AS (
  SELECT category,
         product_name,
         revenue,
         DENSE_RANK() OVER (PARTITION BY category
                            ORDER BY revenue DESC) AS rank_in_category
  FROM product_revenue
)
SELECT category, product_name, revenue, rank_in_category
FROM ranked
WHERE rank_in_category <= 3
ORDER BY category, rank_in_category;

-- DENSE_RANK keeps tied products together.
-- Use ROW_NUMBER if exactly three rows are required.

import pandas as pd

items = pd.read_csv('order_items.csv')
products = pd.read_csv('products.csv')

df = items.merge(products, on='product_id', validate='many_to_one')
df['revenue'] = df['quantity'] * df['unit_price']

revenue = (df.groupby(['category', 'product_name'], as_index=False)
             ['revenue'].sum())

revenue['rank_in_category'] = (revenue.groupby('category')['revenue']
                                 .rank(method='dense', ascending=False))

top3 = (revenue[revenue['rank_in_category'] <= 3]
          .sort_values(['category', 'rank_in_category']))
print(top3)

Q: What is the last thing you learned, and how?

A: I am always learning. I recently learned many things
in Power BI and Python. I watch tutorials and practise
regularly. I am a quick learner and passionate about data.

Q: What is the last thing you learned, and how?

A: Last month I learned DAX time intelligence. My sales
dashboard needed a year-on-year comparison and my first
attempt with manual filters was wrong for partial months.

I read the documentation for SAMEPERIODLASTYEAR, built a
proper date table, marked it as a date table, and wrote:

  Sales LY = CALCULATE([Total Sales],
                       SAMEPERIODLASTYEAR('Date'[Date]))

Now I check that every time-based measure uses the
date table, not the order date column directly.

FOUNDATIONS                                   SCORE 1-5

Joins, GROUP BY, HAVING without help          [  ]
CASE WHEN and COALESCE                        [  ]
ROW_NUMBER, RANK, DENSE_RANK                  [  ]
XLOOKUP, COUNTIFS, SUMIFS                     [  ]
Pivot table and a clean chart                 [  ]
Mean vs median, spread, correlation           [  ]

Anything below 3: fix before applying widely.

SOFT SIGNALS                                  SCORE 1-5

I ask clarifying questions before solving     [  ]
I explain a finding in two plain sentences    [  ]
I can say why a metric matters to a business  [  ]
I admit what I do not know calmly             [  ]
I keep answers under two minutes              [  ]

Practise these in mock interviews, not in notes.

EVIDENCE I CAN SHOW

[ ] Two projects I can defend completely
[ ] One recent skill with a real use
[ ] One bug I found and fixed myself
[ ] One piece of feedback I acted on
[ ] A clean resume with honest skills only

Missing one? Build it this week, not after rejection.