Structured data analysis support for consulting teams that need to move from raw client, survey, benchmark or engagement data to defensible findings, concise visuals and decision-ready outputs.
Do not send confidential datasets through the enquiry form. File-transfer arrangements are confirmed after scope review.
Entry pricing is for clearly bounded work with usable inputs. Final scope depends on data condition, analytical complexity, number of cuts, output depth and deadline.
For a consultant who already knows the question and needs one bounded dataset analysed clearly.
For workstreams that need cleaning, deeper analysis and material suitable for a consulting deliverable.
For high-complexity consulting work with advanced methods, many cuts, repeatable outputs or demanding review cycles.
Pricing excludes data acquisition, primary research/fieldwork, software licences, third-party paid data, legal/regulatory sign-off and work outside the agreed analytical scope.
Share the business question, expected decision, data structure and any mandated methodology. The analysis can then be scoped around the engagement rather than treated as a generic reporting task.
Consulting teams often work under short decision cycles, with datasets assembled from client systems, surveys, interviews, spreadsheets and prior analysis. The failure point is usually not “making a chart” — it is preserving analytical logic while moving quickly enough for client review.
Two teams may use the same metric name with different calculation rules, time windows or denominators.
A preferred technique may not fit sample size, distribution, data type or the business question.
Repeated slicing can create noise and accidental “findings” that are difficult to defend in a client room.
Correct outputs still need a clear answer to “so what?” with boundaries around what the data does and does not show.
Late workbook changes can leave slides, tables and written findings inconsistent with the final analytical output.
The exact path changes by engagement, but each stage exists to keep the final recommendation traceable to the underlying data and assumptions.
Different consulting engagements create different analytical risks. The scope should reflect whether the work is based on operational data, primary research outputs, benchmark comparisons or the economics of service delivery.
Translate exported client data into performance views that can support diagnostic, transformation or operating-model work.
Analyse structured research outputs without losing question wording, base sizes, weighting logic or subgroup context.
Support internal consulting-firm decisions using the metrics that matter in professional services rather than generic corporate KPIs.
Multiple labels, missing values, mixed date formats, duplicate rows or incomplete business definitions are surfaced before conclusions are drawn.
Cleaning decisions, analytical logic and key assumptions remain visible so the consulting team can challenge the work before it reaches the client.
Outputs focus on the decision: what changed, where the difference sits, how confident the team can be and what limitation must travel with the finding.
Use the table as a scoping guide. Final inclusions are confirmed before work begins.
| Scope Area | Focused Analysis | Engagement Analysis + Results | Complex / Multi-Source |
|---|---|---|---|
| Primary use | One bounded question | Client workstream or analysis pack | Complex engagement / repeatable analysis |
| Data preparation | Light cleaning | Cleaning + joins | Extensive / multi-source |
| Descriptive analysis | Included | Included | Included |
| Statistical testing | When tightly scoped | As appropriate | Custom method set |
| Segmentation / subgroup cuts | Limited | Included | Extensive |
| Tables & figures | Up to 5 | Publication / deck-ready set | Custom volume & format |
| Written findings | Concise summary | Structured findings + implications | Extended analytical narrative |
| Reusable code / automation | Not standard | By agreement | Custom scope |
| Correction rounds | 1 | 2 | Defined in scope |
| Starting price | From $80 | From $225 | Custom Quote |
The consulting team retains control of the business question and client narrative; the analytical workflow keeps evidence and outputs aligned as the engagement moves.
Exact formats depend on the engagement and tools used. Editable source outputs can be included when relevant to the agreed scope.
Prepared analytical tables with the transformations needed for the agreed scope.
XLSX / CSVConcise explanation of the results, important differences and relevant limitations.
DOCX / PDFLabelled visuals structured so consultants can place them into the engagement deliverable.
PNG / XLSX / PPTX*Documented analytical choices, exclusions and interpretation boundaries.
DOCX / PDFCode or reusable logic can be supplied when reproducibility is part of the agreed engagement.
PY / R / SQL**Where relevant and included in the agreed scope.
Good analysis starts with usable context. A dataset without definitions, time periods or a business question can create avoidable rework.
Clear boundaries matter when analysis is one dependency inside a larger consulting engagement.
Shorter timelines work when the question is narrow, the data is ready and the consulting team can answer clarification questions quickly.
Suitable for most focused analyses after usable files and scope are confirmed.
May be available for bounded work when data is ready and review turnaround is fast.
Reserved for very limited, clearly defined analysis where feasibility is confirmed before acceptance.
*Express availability is not guaranteed. Complex cleaning, multi-source joins, advanced methods, extensive output writing or delayed clarification can extend delivery.
The service can support consulting engagements that need structured analysis of client operational data, survey or research data, benchmark datasets, project or financial information, customer or workforce data, and other decision-relevant datasets where the scope and lawful use are clear.
Yes. Data quality review, cleaning and preparation can be included. The required effort depends on missing values, inconsistent labels, duplicates, joins, outliers, date or currency issues, and whether business rules are available.
Method selection is based on the consulting question, data structure, assumptions and intended use. If a client methodology is mandatory, it should be supplied and the analysis can be aligned to it where feasible.
Client-ready tables, figures and concise findings can be prepared as part of scope. Final branding, storylining and presentation assembly can be included only when agreed.
The starting package is intended for a tightly scoped analysis using one supplied, reasonably structured dataset, with data review, descriptive analysis, a small set of visuals and a concise findings summary.
Multiple data sources, extensive cleaning, complex joins, advanced statistical methods, weighting, large numbers of cuts, bespoke visualisation, urgent turnaround, repeatable code, and extensive client-ready writing can increase scope and price.
A focused analysis is commonly planned around a 5–7 business day delivery window after usable inputs and scope are confirmed. More complex or multi-source work requires a project-specific timeline.
Priority delivery may be possible for clearly scoped work when capacity and data readiness allow. Very short deadlines are suitable only for limited analyses with complete inputs and fast feedback.
Common analytical inputs include Excel workbooks, CSV files, exported tables, survey extracts and structured text or tabular data. Other formats can be reviewed before scope is confirmed.
Tool choice depends on the work. Common options include Excel, Python, R, SQL and statistical or BI tools where the requested method and output require them.
Yes, where the data, questionnaire or codebook and required cuts are supplied. Scope can include cleaning, frequencies, cross-tabulation, subgroup comparisons, statistical tests and clear presentation of findings.
Yes, when the comparison population, metric definitions and source data are available. The analysis can compare teams, locations, client segments, time periods or other agreed groups without overstating causal conclusions.
Do not place confidential datasets in the enquiry form. Data-transfer method, access limits, retention needs and any confidentiality requirements should be agreed before files are shared.
No. Findings depend on the underlying data and valid analytical methods. Results are reported as supported by the evidence rather than shaped to reach a predetermined conclusion.
Not by default. This service assumes the consulting firm or its client provides the relevant data. Survey design, fieldwork, primary research or data acquisition require separate scope.
Rudrriv reviews the requested analysis and consulting context, may ask clarifying questions, and confirms the usable inputs, scope, price and delivery expectation before work begins.
Email ID, Phone and Requirement Details are required. Name is optional.
