Excel data analysis help from FIZ Business Solutions (FIZBS) is for students who have a spreadsheet full of data and a brief that asks for more than they feel ready to deliver. Perhaps your formulas return errors, your pivot table will not group the way you need, or you are unsure how to turn regression output into a paragraph your marker will accept.
Excel sits at the heart of many business, finance, accounting, economics and health modules. Lecturers use it to test whether you can organise raw data, apply the right functions and draw sensible conclusions, not just whether you can click the right buttons.
Since 2015 we have supported more than 10,000 students and completed over 350 research projects. A Master's or PhD-qualified expert works on your request with you, explaining the logic behind each formula, chart and model so the finished analysis is something you genuinely understand.
What our Excel data analysis help covers
Most Excel tasks follow a similar path: prepare the data, calculate, summarise, visualise and interpret. Your expert can step in at whichever stage is causing trouble, or guide you through the whole workflow from raw file to final write-up.
Good Excel data analysis help is not about producing a polished file you cannot explain. It is about making sure every calculation is traceable, every chart has a purpose and every conclusion links back to your brief.
- Data cleaning: removing duplicates, fixing text and date formats, splitting columns and handling blanks
- Lookup and logic formulas: VLOOKUP, XLOOKUP, INDEX MATCH, IF, IFS and nested conditions
- Conditional calculations with SUMIFS, COUNTIFS and AVERAGEIFS
- Pivot tables, slicers and grouped summaries
- Charts that suit the data: column, line, scatter, histogram and combination charts
- Data Analysis ToolPak: descriptive statistics, correlation, regression and t-tests
- Financial modelling, NPV, IRR, payback and sensitivity analysis
- Forecasting with trendlines, moving averages and FORECAST functions
- Interactive dashboards built from clean, linked data
Cleaning data, formulas and pivot table help
Most problems in an Excel workbook start with messy data. Numbers stored as text, inconsistent category spellings, merged cells and dates in mixed formats will quietly break formulas and pivot tables later on.
Your expert will show you how to convert your sheet into a proper table, with one header row, one record per row and one variable per column. Tools such as TRIM, CLEAN, Text to Columns, Remove Duplicates and Power Query basics make the data reliable before any analysis begins, and you will know how to repeat the process yourself.
Lookup formulas are where many students lose marks. VLOOKUP fails when the lookup column is not on the left or when an approximate match is used by mistake, while XLOOKUP is more flexible but is not available in older versions of Excel. Your expert explains which one suits your file and why.
Pivot table help is one of our most common requests. We cover choosing rows, columns and values, switching between sum, count and average, grouping dates by month or quarter, showing values as a percentage of total, and refreshing the pivot when the source data changes.
Logic functions such as IF, IFS, AND and OR let you classify records, flag outliers or apply business rules. Combined with SUMIFS and COUNTIFS, they turn a long transaction list into meaningful totals by region, product or customer group.
Statistics with the Data Analysis ToolPak
Many modules ask students to run basic statistics in Excel rather than SPSS. The Data Analysis ToolPak can produce useful output, but it gives no guidance on which test to choose or what the results mean.
- Descriptive statistics: mean, median, standard deviation, skewness and range, and what they tell you about your sample
- Correlation matrices and how to describe the strength and direction of relationships
- Simple and multiple regression: R squared, coefficients, standard errors and p-values explained clearly
- Two-sample t-tests with equal or unequal variances, and paired t-tests for before and after data
- Checking assumptions and noting the limits of what Excel can test
- Writing up results in plain academic English with properly formatted tables
Financial modelling help in Excel
Finance, accounting and MBA modules often require a working model rather than a static table. Financial modelling help in Excel starts with a clear layout: inputs and assumptions on one sheet, calculations on another and outputs on a summary page, with no hard-coded numbers buried in formulas.
Your expert can guide you through investment appraisal using NPV, IRR and XNPV, discounted cash flow valuation, loan and lease schedules with PMT, ratio analysis, budgets and break-even models. Sensitivity tables and scenario analysis then show how your conclusions change when key assumptions move, which is exactly the kind of critical judgement markers reward.
Forecasting, charts and dashboards
Forecasting tasks usually involve sales, demand or cost data over time. Your expert can explain linear trendlines, moving averages, the FORECAST.LINEAR function and the Forecast Sheet tool, and help you judge whether a seasonal pattern or a simple trend fits your data better.
A good chart answers one question at a glance. We help you pick the right chart type, label axes properly, remove clutter and link charts to pivot tables and slicers so they form a compact dashboard for reports, presentations or management briefs.
What markers look for in an Excel-based assignment
UK marking criteria for quantitative coursework usually reward accuracy, clear structure, sound interpretation and critical evaluation. A spreadsheet that calculates correctly but is never discussed in the report rarely reaches the higher grade bands.
Markers want to see that you chose methods for a reason, stated your assumptions, acknowledged limitations such as small samples or missing data, and linked your numbers to theory or the case context. Our Excel data analysis help pays attention to the written analysis as much as the workbook, so the two tell the same story.
Excel data analysis help for dissertations
Not every dissertation needs SPSS or Stata. If your project uses survey results, company accounts or secondary data from a public source, Excel can handle descriptive statistics, cross-tabulations, correlation and simple regression perfectly well.
Your expert can help you plan which analyses answer each research question, organise a clean master dataset, produce consistent tables and charts for your findings chapter and explain how to describe the results in the past tense with appropriate caution. If your analysis outgrows Excel, we can also suggest when moving to SPSS, Stata or Python would make sense.
Common Excel mistakes markers notice
- Hard-coded figures typed over formulas, so the model cannot be checked or updated
- Absolute and relative references mixed up, breaking formulas when they are copied down
- Pivot tables built on incomplete ranges that leave out new rows
- Charts with no titles, unlabelled axes or misleading scales
- Regression output pasted into a report with no interpretation of coefficients or significance
- NPV calculated on the wrong cash flow timing, such as discounting the initial outlay
- No explanation of assumptions, data sources or limitations in the written analysis
How Excel assignment help works and pricing
Send your brief, marking criteria, dataset and deadline on WhatsApp. Your expert reviews the task, confirms what analysis is needed and works on your request with you, sharing an annotated workbook and clear explanations of each step so you can follow and present the work yourself.
Because Excel assignment help varies so much, from a single pivot table to a full financial model, the price depends on scope. You receive a clear quote on WhatsApp before anything starts, new customers get 10% off their first order, and deadlines from 48 hours are possible. Everything you share stays 100% confidential.
Our Excel help for students supports Bachelor's, Master's, MBA and PhD learners in the UK, Saudi Arabia and the wider Gulf. Typical projects include sales performance analysis for a marketing module, ratio analysis of a listed company, a capital budgeting case study, survey summaries for a dissertation, and hospital or patient data for health management courses.
Every piece of Excel data analysis help we provide is built on the data you have collected or been given by your module. We never create or alter data to produce a preferred result, and your files stay 100% confidential.