Методы анализа данных
Выберите подходящий метод, чтобы понять, что происходит с вашими данными и какие выводы можно получить в MS Excel.
Dynamics analysis in Excel
Dynamics analysis shows how a metric changes over time: it rises, falls, or remains broadly stable.
Required data
You need dates or periods and the metric you want to analyze.
For example:
- date + revenue;
- month + sales;
- year + profit;
- date + number of orders.
How it works in Excel
- Group data by days, months, or years.
- Calculate the metric for each period.
- Compare periods with each other.
- Calculate percentage growth or decline.
- Show the result in a table or chart.
What you get
The results show:
- when growth or decline began;
- which periods were the best and worst;
- how much the metric changed;
- whether there were sharp changes.
For most methods, the first column is the item name or period, and the second is a numeric metric: amount, revenue, profit, quantity, or sales.
Get analytics report
After configuring the method, your metrics, tables, and visualizations will appear here.
ABC analysis in Excel
ABC analysis shows which items contribute most of the result and which make a small contribution.
For example, identify products or customers that generate most of the revenue.
Required data
You need an analysis object and a metric.
For example:
- product + revenue;
- customer + profit;
- category + sales.
How it works in Excel
- Calculate the result for each item.
- Sort from highest to lowest.
- Calculate each item's share.
- Calculate the cumulative share.
- Classify items into groups:
- A — approximately the first 80% of the result;
- B — the next 15%;
- C — the remaining 5%.
What you get
The results show:
- which items drive the main result;
- which make a moderate contribution;
- which have virtually no impact on the overall result.
For most methods, the first column is the item name or period, and the second is a numeric metric: amount, revenue, profit, quantity, or sales.
Get analytics report
After configuring the method, your metrics, tables, and visualizations will appear here.
Structure analysis in Excel
Structure analysis shows what makes up the overall result and the share of each part.
For example, identify the product with the largest share of total revenue.
Required data
You need a category and a metric.
For example:
- product + revenue;
- expense category + amount;
- branch + sales;
- category + profit.
How it works in Excel
- Group data by category.
- Calculate the result for each category.
- Calculate the total.
- Calculate each category's percentage share.
- Compare the resulting values.
What you get
The results show:
- what makes up the overall result;
- which categories have a larger share;
- which categories make a smaller contribution;
- how the metric is distributed across groups.
For most methods, the first column is the item name or period, and the second is a numeric metric: amount, revenue, profit, quantity, or sales.
Get analytics report
After configuring the method, your metrics, tables, and visualizations will appear here.
Variance analysis in Excel
Variance analysis shows how much an actual result differs from another value.
For example: plan versus actual, current month versus previous month, or expenses versus budget.
Required data
You need two values to compare.
For example:
- plan + actual;
- current month + previous month;
- budget + actual expenses;
- current year + previous year.
How it works in Excel
- Compare two metrics.
- Calculate the difference.
- Calculate the percentage variance.
- Determine whether there was growth or decline.
- Highlight material variances.
What you get
The results show:
- where there is an overrun or decline;
- how much the metrics differ;
- where the plan was met or missed;
- which variances require attention.
For most methods, the first column is the item name or period, and the second is a numeric metric: amount, revenue, profit, quantity, or sales.
Get analytics report
After configuring the method, your metrics, tables, and visualizations will appear here.
Ranking analysis in Excel
Ranking analysis helps identify the best and worst items by the selected metric.
For example, rank products, customers, branches, or managers.
Required data
You need a comparison item and a metric.
For example:
- manager + sales;
- supplier + amount;
- customer + revenue;
- branch + number of orders.
How it works in Excel
- Calculate the result for each item.
- Sort the values.
- Determine the rank of each item.
- Highlight leaders and low-performing items.
What you get
The results show:
- which items are at the top;
- which items have low results;
- how much the metrics differ;
- how ranks are distributed.
For most methods, the first column is the item name or period, and the second is a numeric metric: amount, revenue, profit, quantity, or sales.
Get analytics report
After configuring the method, your metrics, tables, and visualizations will appear here.
Trend analysis in Excel
Trend analysis helps determine the overall direction of a metric over a period.
It shows a sustained tendency rather than a one-off spike: for example, sales gradually rise or profit declines.
Required data
You need data for several periods.
For example:
- month + revenue;
- week + number of orders;
- year + profit;
- date + sales.
How it works in Excel
- Arrange data over time.
- Build a chart of the metric's change.
- Determine the overall direction.
- Add a trend line.
- Assess how consistent the trend is.
What you get
The results show:
- whether there is sustained growth or decline;
- which direction the metric is moving;
- whether the change is temporary or lasting;
- how the metric develops over time.
For most methods, the first column is the item name or period, and the second is a numeric metric: amount, revenue, profit, quantity, or sales.
Get analytics report
After configuring the method, your metrics, tables, and visualizations will appear here.
Anomaly analysis in Excel
Anomaly analysis helps identify unusual values that differ significantly from the rest of the data.
For example, a sharp increase in expenses or an unexpected drop in sales.
Required data
You need a set of values that can be compared with one another.
For example:
- daily sales;
- monthly expenses;
- orders by branch;
- manager results.
How it works in Excel
- Compare the values with one another.
- Determine the normal range of the metric.
- Identify values that differ substantially from it.
- Highlight these values in a table or chart.
What you get
The results show:
- where an unusual spike or drop occurred;
- which values differ from the rest;
- during which period the anomaly appeared;
- which data should be reviewed in more detail.
For most methods, the first column is the item name or period, and the second is a numeric metric: amount, revenue, profit, quantity, or sales.
Get analytics report
After configuring the method, your metrics, tables, and visualizations will appear here.
Comparative analysis in Excel
Comparative analysis shows how one metric changed for each item between two periods.
For example, compare product profit across two years.
Required data
You need an item and two values to compare.
For example:
- product + profit 2025 + profit 2026;
- branch + sales for two months;
- manager + plan + actual.
How it works in Excel
- Specify the item and the two values to compare.
- Calculate the difference between them.
- Determine whether there was growth or decline.
- Display both values side by side in a table and chart.
What you get
The results show:
- which items increased or decreased;
- how much the value changed;
- where the difference between periods is most pronounced.
For most methods, the first column is the item name or period, and the second is a numeric metric: amount, revenue, profit, quantity, or sales.
Get analytics report
After configuring the method, your metrics, tables, and visualizations will appear here.