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Data Analyst Skills in 2026: What 2,467 Indian Job Postings Ask For, and What Interviewers Check

Built on 2,467 Indian data-analyst postings collected 23 August to 27 September 2026: how often each of 18 skills was named, which are must-have for a fresher, which depend on the employer, and how interviewers test each.

By Durgesh Yadav — Senior Data Engineer @ 7-Eleven · Updated 15 Oct 2026. Preparation guidance, not a hiring guarantee.

What skills does a data analyst need in 2026?

SQL, Excel, Python and one BI tool. In 2,467 Indian data-analyst postings from 23 August to 27 September 2026, SQL was named in 34.6%, Excel in 23.6%, Python in 23.2%, Power BI in 20.1% and Tableau in 12.7%. Cloud platforms such as Azure and Snowflake depend on the employer, and engineering tools such as Kafka and Docker rarely appear.

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Which data analyst skills are must-have?

Five skills lead analyst postings: SQL, Excel, Python, Power BI and Tableau. In PrepNPlaced's India Tech Hiring Report, the 2,467 data-analyst postings collected 23 August to 27 September 2026 named SQL in 34.6%, Excel in 23.6%, Python in 23.2%, Power BI in 20.1% and Tableau in 12.7%. Power BI was named more often than Tableau, so learn it first. A share counts postings that name the skill anywhere, and one posting can name several, so the shares overlap. The report measured 18 technologies only. Statistics, communication and domain knowledge have no share because the report did not count them, not because employers do not want them.

Must-have data analyst skills: share of 2,467 Indian data-analyst postings, 23 Aug to 27 Sep 2026
SkillNamed inWhat an interviewer checks
SQL34.6% of 2,467Joins, GROUP BY with HAVING, CASE WHEN, and window functions: rank products by revenue, or month-on-month growth with LAG
Excel23.6% of 2,467XLOOKUP or INDEX and MATCH, pivot tables, and cleaning a messy sheet in a timed test
Python23.2% of 2,467Pandas: read a CSV, handle missing values, groupby and merge, then plot one clear chart
Power BI20.1% of 2,467A star schema, DAX measures with CALCULATE, and a measure that stays right under a slicer
Tableau12.7% of 2,467Dimensions against measures, calculated fields, LOD expressions, and one clear dashboard

Which data analyst skills depend on the employer?

Cloud and warehouse platforms appear in a minority of analyst postings, where the company's data lives on that platform. Azure was named in 10.3% of 2,467, AWS in 7.2%, Snowflake in 7.0%, Databricks in 6.6%, Google Cloud (GCP) in 4.4% and Spark in 4.1%. For an analyst, knowing one means writing SQL against it and knowing what makes a query expensive, not building pipelines on it.

Employer-specific data analyst skills: share of 2,467 Indian data-analyst postings, 23 Aug to 27 Sep 2026
SkillNamed inWhat an interviewer checks
Azure10.3% of 2,467Connecting Power BI to an Azure SQL or Synapse source, and what a data gateway does
AWS7.2% of 2,467Querying files in S3 with Athena, or a Redshift table with SQL
Snowflake7.0% of 2,467SQL in a Snowflake worksheet, and why a larger warehouse uses credits faster
Databricks6.6% of 2,467SQL in a Databricks notebook or SQL warehouse, and reading a Delta table
Google Cloud (GCP)4.4% of 2,467BigQuery SQL, and why selecting fewer columns makes a query cheaper
Spark4.1% of 2,467Enough PySpark or Spark SQL to filter and aggregate a table too big for Pandas

Which skills can a data analyst fresher skip for now?

Seven of the 18 skills are engineering or data science skills, and they rarely appear in analyst postings. Machine Learning was named in 8.3% of 2,467, Java in 2.9%, Airflow in 1.9%, Kafka in 1.6%, dbt in 1.5%, Docker in 1.3% and Kubernetes in 1.1%. Skip them until the must-have five are solid. Machine Learning is worth a look later, because it leads toward data science roles.

Skills a data analyst fresher can skip for now: share of 2,467 Indian data-analyst postings, 23 Aug to 27 Sep 2026
SkillNamed inWhat an interviewer checks
Machine Learning8.3% of 2,467Explaining a regression or classification result in plain words, and what overfitting means
Java2.9% of 2,467Not an analyst skill; learn it only if a posting names it
Airflow1.9% of 2,467What a scheduled DAG is, if the team refreshes reports through one
Kafka1.6% of 2,467What streaming data is, and how a real-time dashboard differs from a daily one
dbt1.5% of 2,467Reading a dbt model's SQL, and what a not_null test catches
Docker1.3% of 2,467Not an analyst skill; learn it only if a posting names it
Kubernetes1.1% of 2,467Not an analyst skill; learn it only if a posting names it

How should a data analyst fresher learn these skills, in order?

Follow an order in which each skill feeds the next: Excel teaches the shape of data, SQL gets it out of a database, a BI tool presents it, and Python handles what the others cannot. PrepNPlaced's Data Analytics cohort gives SQL 7 of its 18 live classes, its largest block, for the same reason.

  1. Excel first: cleaning, XLOOKUP, pivot tables and charts on a real dataset.
  2. SQL next and deepest: joins, GROUP BY, CASE WHEN, CTEs and window functions.
  3. Power BI: Power Query for cleaning, a star schema, DAX measures and one published report.
  4. Python with Pandas: read, clean, group, merge and plot a dataset too messy for Excel.
  5. Statistics for analysts: mean against median, distributions, sampling and a simple A/B test.
  6. Tableau, if the postings you want name it: rebuild your Power BI report in it.
  7. Three projects, each answering one business question, written up with the question, method and answer.

How do you show data analyst skills on a resume?

Show each skill inside a result, because a recruiter screening for SQL or Power BI wants to see what you did with it. Put the tools in a short skills line in the posting's own words, then prove each in a project bullet that names the question, the tool and what you found. Use only numbers your project actually produced.

Skills line: SQL (window functions, CTEs), Excel (pivot tables, XLOOKUP), Power BI (DAX, Power Query), Python (Pandas)
Project bullet: the business question, the tool, what you found, and who would use it
Link a published Power BI report or a GitHub repository, not a screenshot
Drop tools you used once in a tutorial; an interviewer can ask about every one

A project bullet that proves SQL and Power BI

Analysed a public retail sales dataset in SQL (CTEs, window functions) and built a Power BI report on a star schema, with DAX measures for month-on-month sales, to show which product categories fell in the final quarter of the data.

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FAQ

Common Questions

What is the most important skill for a data analyst?

SQL. PrepNPlaced's India Tech Hiring Report found it in 34.6% of 2,467 Indian data-analyst postings (23 August to 27 September 2026), ahead of Excel at 23.6% and Python at 23.2%. Most analyst work starts with getting the right rows out of a database.

Is Python required for a data analyst job?

Not in every posting, but often enough to learn: Python was named in 23.2% of the 2,467 postings, about as often as Excel at 23.6%. Learn it after SQL and Excel; with Pandas it handles data too large or messy for a spreadsheet.

Power BI or Tableau: which should a data analyst learn first?

Power BI, for Indian postings: it was named in 20.1% of 2,467 data-analyst postings against 12.7% for Tableau. The two share the same ideas (dimensions, measures, a data model and filters), so moving to the second is mostly learning a new interface.

Which data analyst skills do freshers need?

The five the postings name most, at working depth: SQL, Excel, Python, Power BI and Tableau. Across all 17,748 postings in the report, 792 were tagged entry or junior, so fresher openings are a small slice, and projects that prove the core count for more than a long tool list.

Is statistics a required data analyst skill?

Yes, though this page gives it no share: statistics was not one of the 18 technologies the report counted. Interviewers ask about mean against median, distributions, correlation against causation and A/B tests, and PrepNPlaced's Data Analytics cohort gives it 2 of its 18 live classes.

Are data analyst skills the same as data engineer skills?

They overlap at SQL and Python, then split. SQL was named in 34.6% of 2,467 data-analyst postings and 48.6% of 1,470 data-engineer postings. Analysts then add Excel and a BI tool; engineers add a cloud and Spark.

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