Top 12 Reporting Analyst Skills to Put on Your Resume
In today's data-fueled business world, reporting analysts turn raw tables into decisions. Clean data, sharp queries, and clear visuals. That’s the job. Build the right stack of skills and you don’t just fill a role—you accelerate it.
Reporting Analyst Skills
1. SQL
SQL (Structured Query Language) is how reporting analysts fetch, join, aggregate, and shape data in relational databases so that reporting isn’t guesswork—it’s grounded.
Why It's Important
Without SQL, most enterprise data stays locked away. With it, you can query precisely, audit logic, and deliver repeatable, trustworthy reports.
How to Improve SQL Skills
- Know your schemas: Normalize where it helps, understand primary/foreign keys, and map relationships before you write a single line.
- Level up core queries: Window functions, CTEs, conditional aggregation, subqueries. Write fewer, smarter queries.
- Think performance: Index strategies, execution plans, predicate pushdown, avoiding N+1 joins, minimizing scans.
- Harden your logic: Handle NULLs deliberately, beware implicit conversions, validate row counts end to end.
- Use dialect strengths: Postgres, SQL Server, MySQL, Snowflake, BigQuery—each has quirks and power features. Learn them.
- Automate repeatables: Views, stored procedures, materialized views, scheduled jobs for stable pipelines.
Practice on real data, profile results, then refactor until it sings.
How to Display SQL Skills on Your Resume
2. Excel
Excel is the analyst’s Swiss Army knife: formulas, PivotTables, charts, Power Query, and the Data Model for quick-to-deploy reporting.
Why It's Important
It’s everywhere. Stakeholders know it, trust it, and expect fast turnarounds. Great Excel chops turn messy inputs into digestible dashboards.
How to Improve Excel Skills
- Modern formulas: XLOOKUP, FILTER, UNIQUE, SORT, LET, LAMBDA, dynamic arrays—cleaner logic, fewer helper columns.
- Pivot mastery: PivotTables/Charts with slicers, timelines, and calculated fields for rapid summaries.
- Power Query: Reliable imports and transformations. Build refreshable steps instead of manual cleanups.
- Power Pivot: Star schemas, relationships, and DAX measures for robust models on large datasets.
- Automation: Use VBA or Office Scripts to remove drudgery. Add data validation and error checks.
- Design with intent: Layered charts, sparklines, conditional formatting, consistent number formats, and readable layouts.
Document assumptions, protect formulas, and make refresh a one-click habit.
How to Display Excel Skills on Your Resume
3. Tableau
Tableau turns tables into stories—interactive dashboards, sleek visuals, and governed sharing that help teams see and act.
Why It's Important
It bridges analyst and audience. Complex data becomes approachable, trends pop, and decision-makers engage instead of skimming.
How to Improve Tableau Skills
- Structure first: Prefer relationships over heavy joins when possible, define clean data sources, and extract where performance matters.
- Calculations, not chaos: Table calcs, LOD expressions, parameters, and reusable calculated fields. Minimize duplicated logic.
- Design for speed: Fewer quick filters, indexed fields, aggregated extracts, mindful mark counts, and performant custom SQL.
- Prep well: Use Tableau Prep or upstream tools to deliver tidy, typed tables with clear grain.
- Tell the story: Bullet charts, small multiples, highlight actions, and guided navigation. Clarity over clutter.
- Governance: Permissions, data source certification, and versioning on Server/Cloud for durable reporting.
Measure twice, publish once—then iterate with feedback.
How to Display Tableau Skills on Your Resume
4. Power BI
Power BI is Microsoft’s analytics workbench—data modeling with DAX, slick visuals, and enterprise distribution baked into the ecosystem.
Why It's Important
It connects to almost anything, scales from scrappy to enterprise, and slots neatly into Microsoft 365 and Azure.
How to Improve Power BI Skills
- Model like a pro: Star schemas, surrogate keys, sensible granularity, and clear naming. Relationships drive everything.
- DAX depth: Measures over columns, CALCULATE with filter context, time intelligence, variables for readability.
- Performance focus: VertiPaq-friendly data types, summarize early, reduce cardinality, use Performance Analyzer, and consider composite models.
- Fabric-aware: Incremental refresh, Direct Lake/DirectQuery where appropriate, and governance in workspaces.
- Polished visuals: Field parameters, bookmarks, drill-through, tooltips, and consistent themes for a cohesive feel.
- Security and ops: Row-level security, deployment pipelines, and scheduled refresh with solid credentials.
Ship small, validate, then harden for scale.
How to Display Power BI Skills on Your Resume
5. Python
Python lets analysts wrangle data, automate pipelines, and build reproducible reports with libraries that punch far above their weight.
Why It's Important
It scales from quick fixes to full workflows—cleaning, analysis, visualization, even scheduled reporting.
How to Improve Python Skills
- Data stack: Pandas for dataframes, Polars for speed, NumPy for arrays. Know when each shines.
- Visuals that speak: Matplotlib and Seaborn for fundamentals, Plotly for interactivity when stakeholders want to poke at the data.
- Reproducibility: Virtual environments, notebooks with narrative, scripts that can be scheduled, logging for traceability.
- Packaging and style: Type hints, docstrings, tests, and modular code. Reduce notebook sprawl.
- Dashboards/apps: Dash or Streamlit for light-weight analytics apps and shareable reports.
Start simple, automate the boring parts, and keep outputs consistent.
How to Display Python Skills on Your Resume
6. R
R is built for statistics and graphics, loved for tidy workflows and publication-quality visuals.
Why It's Important
When the analysis leans statistical, R makes modeling, visualization, and scripted reporting feel native.
How to Improve R Skills
- Tidyverse fluency: dplyr, tidyr, readr—clean pipelines with readable verbs.
- Visualization craft: ggplot2 with themes, facets, and annotations. Clear, honest charts.
- Reproducible reporting: Quarto or R Markdown for parameterized reports; Shiny for interactive apps.
- Modeling: tidymodels for consistent preprocessing, tuning, and validation.
- Project hygiene: renv for dependencies, testthat for reliability, and organized scripts.
Keep analyses scripted, not manual, so results are repeatable on demand.
How to Display R Skills on Your Resume
7. SAS
SAS is an analytics suite used widely in regulated industries for rigorous data management, reporting, and statistical procedures.
Why It's Important
It brings traceable workflows, robust procedures, and governance—key where audits matter.
How to Improve SAS Skills
- Core building blocks: DATA step mastery, PROC SQL, PROC REPORT, and PROC TABULATE.
- Macros and automation: Macro variables and %MACRO to standardize repetitive logic.
- ODS output: Clean exports to HTML, PDF, Excel with styles and controlled formatting.
- Data ops: Joins/merges, reshaping, handling missing values, and efficient indexing.
- Modern platform: Explore SAS Viya and CAS for scalable, cloud-friendly workloads and Python interoperability.
Comment generously and keep programs modular for easier validation.
How to Display SAS Skills on Your Resume
8. VBA
VBA (Visual Basic for Applications) automates Excel, turning clicky, error-prone steps into button-press routines.
Why It's Important
It saves hours, standardizes outputs, and reduces mistakes when reports need dependable refreshes.
How to Improve VBA Skills
- Object model comfort: Workbooks, Worksheets, Ranges, and ListObjects—know the hierarchy.
- Quality of life: Error handling, Option Explicit, modular procedures, and meaningful names.
- Performance: ScreenUpdating off, batch writes, avoid Select/Activate, and use With blocks.
- Integration: Drive PivotTables, charts, and Power Query refreshes. Generate PDFs or emails on schedule.
- Durability: Parameterize inputs, validate data, and log actions for auditability.
Automate what’s repeated; leave the rest flexible.
How to Display VBA Skills on Your Resume
9. QlikView
QlikView delivers associative analytics with fast in-memory exploration and dynamic dashboards.
Why It's Important
It enables quick, interactive slice-and-dice analysis that surfaces relationships traditional filters miss.
How to Improve QlikView Skills
- Scripting strength: Robust load scripts, QVD layers, and tidy data models that avoid synthetic keys.
- Set analysis: Comparative metrics, year-over-year views, and context-aware expressions.
- Model hygiene: Concatenate fact tables when appropriate, resolve circular references, and document field lineage.
- Security: Section Access for row-level controls and safe distribution.
- Future-proofing: Many teams are shifting to Qlik Sense—skills transfer well; be ready to adapt.
Build responsive apps with purposeful selections and clear navigation.
How to Display QlikView Skills on Your Resume
10. Google Analytics
Google Analytics (GA4) tracks user behavior across sites and apps, shifting to an event-based model that’s flexible and future-facing.
Why It's Important
It reveals how people find you, what they do, and where the experience leaks—vital for product and marketing decisions.
How to Improve Google Analytics Skills
- GA4 mindset: Events and parameters over pageview-only thinking. Define conversions intentionally.
- Tagging discipline: Use a tag manager, consistent naming, and robust UTM governance. Test with DebugView before you trust it.
- Explorations: Funnels, pathing, cohorts—answer questions that standard reports can’t.
- Data quality: Cross-domain setup where needed, filters for internal traffic, and periodic audits.
- Warehouse handshake: Export to BigQuery for raw data analysis, joins with backend tables, and unsampled reporting.
Measure what matters, not everything that moves.
How to Display Google Analytics Skills on Your Resume
11. SPSS
SPSS provides approachable statistical analysis, robust data management, and templated reporting—especially useful when consistency is key.
Why It's Important
It’s steady and structured, helping analysts run sound tests and package results for stakeholders who need confidence and clarity.
How to Improve SPSS Skills
- Syntax first: Move from point-and-click to syntax for reproducibility and automation.
- Statistical breadth: t-tests, ANOVA, regression, nonparametrics, and reliability analysis—know which tool fits which question.
- Automation: Macros and scripting to standardize recurring analyses and outputs.
- Output control: Use OMS to export clean tables and charts to desired formats without manual cleanup.
- Extend wisely: Tap into Python integrations for custom procedures when SPSS menus hit their limits.
Consistency trumps novelty when your audience wants stable evidence.
How to Display SPSS Skills on Your Resume
12. Salesforce
Salesforce is the CRM backbone for many orgs. Reports, dashboards, automation, and CRM Analytics (formerly Einstein Analytics/Tableau CRM) turn customer data into action.
Why It's Important
From pipeline to support, it captures the customer journey—perfect ground for timely, targeted reporting.
How to Improve Salesforce Skills
- Report types: Master custom report types, joined reports, row-level formulas, and bucket fields.
- Dashboards that guide: Tailored filters, drill-down paths, and KPI tiles aligned to stakeholder goals.
- Data quality: Validation rules, required fields, deduplication, field history tracking, and ownership hygiene.
- Automation: Flows for scheduled updates, notifications, and data shaping that keeps reports fresh.
- CRM Analytics: Datasets, recipes, lenses, and security predicates for governed, scalable insights.
Test in a sandbox, document the logic, and schedule the delivery.
How to Display Salesforce Skills on Your Resume
