Excel/Power BI ETL: connect, transform, merge, M language, parameters.
Before starting, we run a 1-minute tech check — microphone, ambient noise, connection. If your setup isn't good enough, the test is fully refunded.
Prove your Power Query skills are the real deal — M code, query folding, multi-source merges — with a 15-minute AI oral exam that goes way beyond a LinkedIn checkbox.
The Plume Power Query badge validates your ability to design and run solid ETL pipelines in Excel and Power BI: connecting to heterogeneous sources (flat files, SQL databases, SharePoint, REST APIs), transforming and cleaning data through both the GUI and the Advanced Editor, merging and appending queries, writing custom M functions, and managing refresh performance through query folding. The 15-minute AI oral probes both your conceptual understanding and your real-world problem-solving on topics like missing-column handling, Left Anti Joins, Table.Buffer, and when to disable load on staging queries.
Unlike a self-declared LinkedIn skill, this badge is based on a dynamic oral exam driven by an AI examiner calibrated on real Power Query scenarios. You need to explain your design choices (Merge vs Append, native folding vs buffered tables, Desktop vs Dataflows), justify when you write M by hand, and show you understand where Power Query fits in a broader data stack alongside Power BI Service, Dataflows Gen2, and Microsoft Fabric. A second AI model (Claude Opus) reads the full transcript and produces a 0-100 score, a certified level, and a detailed per-criterion report.
This badge is built for BI analysts, data analysts, financial controllers, and Power Platform consultants who use Power Query daily and want concrete proof of their expertise. It also suits data-career switchers who have learned Power Query on the job and need a credible credential to stand out without an additional degree.
Here are the concrete dimensions the AI examines during the 15-minute oral.
Ability to connect Power Query to Excel files, CSV, SQL databases, SharePoint lists, REST APIs, and folder-based file collections, managing connection parameters and credentials correctly.
Solid command of applied steps: pivot and unpivot, column splitting, value replacement, null handling, data type management, and schema drift when consolidating files from a folder.
Ability to read, write, and debug native M code using let...in, each, List.Generate, and parameterized functions to automate repetitive transformations and dynamic source paths.
Understanding of query folding mechanics, ability to identify steps that break folding, and command of optimization techniques including Table.Buffer, disabling load on intermediate queries, and pushing filters upstream.
Mastery of all join types (Inner, Left Outer, Left Anti, Full Outer, Right Anti) and Append for consolidating multi-source or multi-period datasets, with clear reasoning on when to use each.
Knowing where transformation logic should live: Power Query Desktop, Power BI Service Dataflows, Dataflows Gen2 in Fabric, SQL views, or external tools like dbt or Python/pandas.
Using try...otherwise, Value.NativeQuery, handling missing columns during folder consolidation, and designing queries that survive source schema changes without breaking the whole report.
Ability to identify when Power Query is the wrong tool: very large volumes, complex server-side logic better handled by SSIS, Python, or a SQL view, and making that call confidently.
Final scoring is performed by Claude (Anthropic), which reads back the full transcript and applies this weighted criteria grid.
Accuracy of explanations around applied steps, M syntax, native functions (Table.*, List.*, Text.*), and query execution logic. Can the candidate explain what each piece of code actually does and why?
Quality of personal examples: does the candidate illustrate answers with concrete projects, actual data volumes, real errors encountered, and specific solutions applied? Vague generalities score low here.
Understanding of how query folding works against the data source, ability to spot folding-breaking steps, and knowledge of techniques like Table.Buffer, column pruning, and disabled-load staging queries.
Ability to position Power Query within a broader architecture: Power BI Service, Dataflows Gen2, SharePoint, SQL Server. Does the candidate know when to push transformation logic to the source or use an alternative tool?
Is the oral fluent, well-structured, and clear to a technical peer? Does the candidate use precise Power Query vocabulary without approximations and know when to simplify for a non-technical audience?
A Plume session takes about 20 minutes, from tech check to badge delivery.
The AI verifies your mic quality and connection stability. You confirm you're in a quiet space and ready to go. No technical questions at this stage — just making sure the session runs smoothly.
The AI asks you to introduce yourself and briefly describe your day-to-day use of Power Query: what context you work in, which data sources you connect to, and the scale of data you typically handle.
The heart of the exam: the AI works through 4 to 6 in-depth questions covering your real projects, M code, query folding, merge/append logic, error handling, and stack integration. It follows up on your answers and asks you to unpack specific points.
The AI asks you to assess the real limits of Power Query and name the situations where you'd use something else (Python, SQL, SSIS, dbt). This section tests your maturity as a data practitioner, not just your Power Query knowledge.
Claude Opus reads the full transcript and produces a 0-100 score, a certified level (Novice to Expert), a detailed per-criterion report, and a shareable badge URL. Everything lands in your inbox within 10 minutes.
Your score out of 100 translates into a level a recruiter can grasp at a glance.
You use Power Query's graphical interface for basic transformations (filtering rows, renaming columns, changing data types) on a single source. You haven't written M code or handled multi-source consolidation and schema errors yet.
You build parameterized queries, perform Merge and Append across multiple sources, and can read M code even if you don't write it from scratch. You've consolidated files from a folder and handled common data errors.
You write custom M functions using let...in and each, understand query folding, and optimize refresh performance. You integrate Power Query into Power BI reports and know when to use Dataflows instead of Desktop.
You design full ETL architectures with Power Query as the transformation layer, command native M APIs (Value.NativeQuery, Table.Buffer, List.Generate), train others, and make informed trade-offs between Power Query, Dataflows Gen2 in Fabric, dbt, and Python.
No degree or years of experience required to take the badge. Here are the profiles it makes the most sense for.
You build Power BI models and want proof that your transformation layer is solid — not just 'did some Power Query' on a resume that nobody can verify.
You automate monthly consolidations of multi-entity Excel files and want to validate that your approach is professional, maintainable, and scalable beyond your team.
You deliver data solutions to clients and need an external proof of your Power Query level to back up your proposals and justify your rates.
You don't have a BI degree yet, but you've learned Power Query in the field. This badge gives you a concrete, verifiable credential to show recruiters who can't evaluate your skills from a title alone.
You integrate Power Query into Dataflows Gen2 or Power BI Service pipelines and want to document your ETL layer mastery for senior roles and data architecture projects.
Where and how your Power Query badge will help you day to day.
You're applying at a scale-up that runs on Power BI. The hiring manager gets your badge link and sees you scored 84/100 at Advanced level. Zero follow-up questions about your ETL skills — the badge does the talking.
You're pitching a multi-subsidiary data consolidation project in Power BI. You attach your Expert-level Power Query badge to the proposal, giving the client objective evidence that your day rate is justified.
You're going for a BI Lead role. Your manager is choosing between two candidates. You share your Plume report showing specific scores on query folding and Dataflows integration — the other candidate has nothing comparable.
You run internal Power BI workshops. Your Expert Power Query badge validates your pedagogical credibility with participants and the L&D team, without needing a Microsoft certification to back it up.
You add your Plume badge URL to your LinkedIn profile and your GitHub portfolio. Recruiters can check your certified score and level in one click, with no need to reach out and ask.
A consulting firm submits your profile to a client for a data project. Your certified Power Query badge serves as objective proof of competence in the proposal deck, reducing risk for the client.
A few minutes to check you have everything you need.
At the end of your session you don't just get a score — here's everything that awaits you.
You get a precise score and an official level (Novice, Proficient, Advanced, or Expert) certifying your Power Query mastery, produced by Claude Opus from your full exam transcript.
A full report breaks down your score across the 5 evaluated dimensions: M mastery, problem-solving, query folding, stack integration, and communication. You know exactly what to work on next.
Your exam audio is stored securely and stays under your control. You can choose to share it with a recruiter as proof of authenticity, or keep it private — your call.
You get a permanent public URL for your Power Query badge. Drop it into your LinkedIn profile, your resume, a client proposal, or your data portfolio in one click.
Discover related skills you can validate with Plume.
A 15-min oral exam with an AI, a shareable badge for your recruiters.
Choose this badge · €19.99
