Analytics - Power BI Guide
A practical guide for business users who are new to Power BI, covering navigation, filters, measures, data models, and data transformation.
The Analytics product package includes a set of pre-built Power BI templates that connect directly to your LS Central data. These templates provide ready-to-use dashboards and reports covering sales, inventory, staff performance, customer loyalty, and more.
This guide focuses on the Sales Analytics report — the most commonly used template. After reading it, you will understand how to navigate, filter, and interpret any Power BI report in the package, and where every number comes from.
Explore the key sections of this guide using the links below:
- Introduction
- Power BI Desktop vs. Power BI Service
- The Report Interface
- Using Filters
- The Data Pane
- The Visualizations Pane
- Measures — Where the Numbers Come From
- The Data Model — How Tables Are Connected
- Transform Data — Power Query
- Quick Reference
- Glossary
- Further Resources
01 — Introduction
What is Power BI?
Power BI is Microsoft's business intelligence tool. It connects to your data — in this case LS Central — calculates metrics automatically, and presents them as interactive visual reports you can explore by clicking, filtering, and drilling down. No technical background is needed.
What is the Sales Analytics Report?
A pre-built Power BI template that reads directly from your LS Central system, giving you instant visibility into:
-
Net and gross sales by period, store, item, or staff member
-
Margin and profitability analysis
-
Item quantity and average transaction values
-
Budget vs. actual comparisons
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Discount analysis and customer/member activity
NOTE: The report shows data as of the last scheduled refresh. Your IT administrator sets the refresh schedule (typically nightly). See Section 2 for an important explanation of Desktop vs. Service refresh cycles.
02 — Power BI Desktop vs. Power BI Service
Before using the report, it is essential to understand that Power BI comes in two separate versions. Confusing the two is a very common source of frustration — especially around data not appearing to refresh.
| Power BI Desktop | Power BI Service | |
|---|---|---|
| What it is | A Windows application (a .pbix file) installed on a computer | A web browser application at app.powerbi.com — also called Power BI Online |
| Who uses it | Developers, LS Retail partners, IT administrators who build and maintain the report | Business users who view, filter, and explore published reports in a browser |
| Where data lives | Locally on the computer where the file is open | In the Microsoft cloud, refreshed automatically on a schedule |
| How it refreshes | Manually — click Refresh in the ribbon. Data stays in the local file | Automatically — your admin configures a scheduled refresh (e.g. nightly at 2 AM) |
| Can you share it? | No — only the person with the .pbix file can see it | Yes — share a link and anyone with access can view it from any device |
WARNING: Refreshing in Power BI Desktop updates only the local .pbix file on your computer — it does NOT update the report your colleagues see in the browser. Conversely, when the scheduled refresh runs overnight in Power BI Service, it updates the cloud copy — it does NOT update anyone's Desktop file. They are completely independent. To push a Desktop change to the browser, the file must be published again using the Publish button.
How the Workflow Works
The typical end-to-end flow for the Sales Analytics report:
- LS Retail configures Analytics that connects to your LS Central database.
- The report (.pbix file) is published to Power BI Service by your administrator.
- A scheduled refresh is configured in Power BI Service (e.g. every night at 2:00 AM).
- Every morning, the browser report automatically shows last night's data.
- Business users open the report at app.powerbi.com (or a shared link) in their browser.
TIP: As a business user viewing the report in a browser, you almost never need to open Power BI Desktop. Everything in this guide applies to both Desktop and Service — the report interface is identical in both.
03 — The Report Interface
The interface looks identical when the report is viewed in a browser (Power BI Service) or in Power BI Desktop.
The Ribbon (Top Bar)
The ribbon contains tools for building and managing reports. As a business user, the only buttons you may occasionally use are:
- Refresh data — fetches the latest data from LS Central into this Desktop file (does NOT update the browser version).
- Transform data — opens Power Query, the data connection area (covered in Section 8).
- Publish — pushes this .pbix file to Power BI Service. Used by administrators only.
The Left Navigation — Three Views
| View | Icon | What you use it for |
|---|---|---|
| Report view | Chart icon (top) | The default. All dashboards and charts live here. Business users work here exclusively. |
| Data view | Table/grid icon | Browse raw data tables and click a measure to see its DAX formula. |
| Model view | Diagram icon | See how all the tables are connected to each other. Covered in Section 7. |
Report Pages (Bottom)
The page tabs at the bottom of the screen give access to all 83 pages of the Sales Analytics report. The home/navigation page lists all reports as clickable links, organised by category:
- Sales Overview — high-level KPIs, trends, averages, forecasts
- Sales Analysis (Top 10, Bubble, YOY, POS Sales Return) — detailed analytical views
- Item Hierarchy (Divisions, Categories, Product Groups, Items) — drill-through item analysis
- Discount Overview — discount types, amounts, and margin impact
- Store Overview — store comparison, growth, channel, income/expense
- Budget — budget vs. actual by store, item, and date
- Member Overview — loyalty member activity and spend analysis
- Staff Overview — performance by staff member
- POS Terminal Overview — terminal and transaction analysis
04 — Using Filters
Filters are the most important tool for a business user. They narrow what data is shown in every visual simultaneously — for example, displaying only January 2024 data, or only one store, or one item category.
The Filters Pane
| Filter level | Scope | Example use |
|---|---|---|
| Filters on this visual | Only the currently selected chart or table | Show only top-10 items in one table without affecting other visuals |
| Filters on this page | All visuals on the current page | Filter the entire page to one item category |
| Filters on all pages | Every page in the entire report | Restrict the whole report to one company or reporting period — cannot be overridden |
TIP: Click the × icon on an active filter card to remove it, or click "Clear all" at the top of the pane. Some filters (like Company Name) are locked by the report designer and cannot be removed by viewers — this is intentional.
Slicers — On-Canvas Filters
Slicers are filter controls placed visually on the report canvas. Click a value to filter the page. Hold Ctrl to select multiple values. Click the eraser icon in the slicer header to clear it.
Cross-Filtering — Click Any Visual to Filter
Clicking any element in a chart (a bar, a data point, a table row) automatically filters all other visuals on the page to show only that selection. Click the same element again to remove the filter. Hold Ctrl to select multiple elements.
NOTE: Exploring a Power BI report — clicking, filtering, drilling — never changes the underlying data in LS Central. All interactions are temporary and visual only. Nothing is saved unless you are the report author and explicitly save and republish.
05 — The Data Pane
The Data pane lists every table and field available in the report. It shows exactly what data the report has access to, and where to find the building blocks behind every visual and measure.
| Table Name | Type | What it contains |
|---|---|---|
| Measure Collection | Measures only | All DAX-calculated metrics: Net Sales, Gross Sales, Margin, Margin %, Cost, Item Quantity, averages, and hundreds more — organised into folders. |
| Actuals Net Sales | Fact Table | Every POS sales transaction line. One row per sales line item. The central table — most measures calculate from here. |
| Actuals Discounts | Fact Table | Discount records from POS: amounts, offer codes, discount types. |
| POS Transactions | Fact Table | Transaction-header data: basket totals, payment methods. |
| Retail Sales Budget | Fact Table | Budget targets by store, item, and period for budget vs. actual comparison. |
| Item | Dimension | Product catalogue: item numbers, descriptions, categories, product groups. |
| Location | Dimension | Store list: store codes, names, and regions. |
| Staff | Dimension | Staff members and their departmental attributes. |
| Date | Dimension | Calendar table with year, quarter, month, week, day, and fiscal period attributes. |
| Member | Dimension | Loyalty members: cards, schemes, and tier information. |
| POS Terminal | Dimension | Terminal names and their store assignment. |
06 — The Visualizations Pane
The Visualizations pane controls the type and configuration of whichever chart or table is currently selected on the canvas. As a report viewer you do not need to change anything here, but understanding it helps you interpret what you are looking at.
| Tab | Icon | Purpose |
|---|---|---|
| Build visual | Bar chart | Shows the fields placed in the visual — what is on each axis, what is the value, what is the legend. |
| Format visual | Paint brush | Controls colours, fonts, titles, borders, and other styling options. |
| Analytics | Magnifying glass | Adds reference lines, trend lines, or forecast lines to a visual. |
07 — Measures — Where the Numbers Come From
Measures are the calculated values shown in KPI cards, charts, and tables — Net Sales, Margin %, Item Quantity, and so on. Each measure is a DAX (Data Analysis Expressions) formula that calculates a result dynamically based on whatever filters are active.
How to View a Measure Formula
- Click the Data view icon on the left navigation bar (table/grid icon).
- In the Data pane, expand Measure Collection, then expand a folder (e.g. "1 - Sales").
- Click a measure name — for example "Net Sales".
- The formula bar at the top shows the DAX expression.
- Hover over the measure name to see its description as a tooltip.
Reading a DAX Formula
Example: Net Sales = Sum( 'Actuals Net Sales'[NetSalesAmountLCY] )
| Part of the formula | What it means |
|---|---|
| Net Sales | The measure name — what appears in visuals and the Data pane. |
| Sum(...) | The calculation type: adds up all matching values. Could also be AVERAGE, COUNT, MAX, or a more complex expression. |
| 'Actuals Net Sales' | The source table name (in single quotes). Points to the raw transaction data table from LS Central. |
| [NetSalesAmountLCY] | The source column (in square brackets). The raw amount field being summed. LCY = Local Currency. |
Key Measures Reference
| Measure | Folder | Formula / Source | What it tells you |
|---|---|---|---|
| Net Sales | 1 - Sales | Sum of Actuals Net Sales[NetSalesAmountLCY] | Total revenue after discounts and returns |
| Gross Sales | 1 - Sales | Sum of Actuals Net Sales[GrossSalesAmountLCY] | Total revenue before any deductions |
| Margin | 2 - Margin | Net Sales − Cost | Profit after cost of goods sold |
| Margin % | 2 - Margin | Margin ÷ Net Sales (%) | Profitability as a percentage of net sales |
| Item Quantity | 4 - Quantity | Sum of Actuals Net Sales[Quantity] | Total units sold |
| Cost | 6 - Cost | Sum of Actuals Net Sales[CostAmountLCY] | Total cost of goods sold |
| AVG Net Sales per Item | 5 - Average | Net Sales ÷ Item Quantity | Average revenue per unit sold |
| AVG Margin per Transaction | 5 - Average | Margin ÷ Transaction count | Average profit per customer basket |
| AVG Nr of Items per Trans. | 5 - Average | Item Quantity ÷ Transaction count | Average basket size (items per visit) |
What is Filter Context?
Every measure re-calculates its result every time you change a filter. The same Net Sales measure returns different numbers depending on what is selected. For example:
- Select Store A → shows only Store A's net sales
- Select January 2024 → shows only January 2024 net sales
- Select both → shows Store A's net sales in January 2024
This automatic recalculation happens for every measure, every time. You never need to refresh or recalculate anything manually.
08 — The Data Model — How Tables Are Connected
The Model view shows how all data tables relate to each other. This diagram explains why selecting a store filter automatically updates the item, staff, and date data — they are all connected through the central fact table.
Fact Tables vs. Dimension Tables
| Table type | Role | Example |
|---|---|---|
| Fact Table | Contains actual transaction records — one row per sales line. Has millions of rows. This is where all the numbers come from. | Actuals Net Sales |
| Dimension Table | Contains descriptive information — one row per entity. Used to filter and label the fact data. | Item, Location, Staff, Date, Member |
How Relationships Work
Each relationship line has a "1" side (dimension) and a "*" side (fact table). When you select a filter value, Power BI follows the relationship to identify matching rows in the fact table and recalculates all measures automatically. Example:
- You select "Clothing" in the Item Category slicer.
- Power BI finds all rows in the Item dimension where Category = "Clothing".
- It follows the relationship into Actuals Net Sales, keeping only matching rows.
- All measures (Net Sales, Margin, Quantity, etc.) recalculate using only those rows.
- Every visual on the page updates instantly.
09 — Transform Data — Power Query
Power Query is the data loading and transformation layer. It connects to the LS Central Analytics database, extracts data, applies transformations, and loads it into the data model. Access it via Home → Transform data.
The Source Step — Database Connection
In the formula bar you can see: = Sql.Database(AnalyticsServer, AnalyticsDatabase) — this reads the server and database name from parameters, pointing to your LS Central Analytics database.
The Navigation Step — Raw Data Preview
The Applied Steps panel shows the transformation chain: Source → Navigation → Removed 3 Columns → Renamed AdjustedCostAmount → Removed Location C Variant → Renamed Date → Fix data types. Each step is one recorded transformation.
WARNING: Do not delete, reorder, or modify the Applied Steps in the Analytics templates. These are pre-configured by LS Retail. Incorrect changes will break the data refresh or cause calculation errors. If customisation is needed, contact your LS Retail partner.
10 — Quick Reference
| Task | How to do it |
|---|---|
| Filter by date | Use the Date slicer on the canvas, or expand "Date" in the Filters pane → Filters on this page |
| Filter by store | Click a store in the Location slicer, or select from Filters pane → Location Name |
| Remove all filters | Click "Clear all" at the top of the Filters pane (locked filters cannot be removed) |
| See exact numbers for a chart | Hover over any bar, line point, or pie slice |
| See the data table behind a visual | Right-click the visual → Show as a table |
| Find a measure formula | Data view icon (left nav) → expand Measure Collection → click the measure |
| Check which database is connected | Home → Transform data → click "Source" step in Applied Steps |
| Understand table relationships | Model view icon (left nav) |
| Navigate between report topics | Click page tabs at the bottom, or use links on the Navigation home page (Page 1) |
| Drill into detail behind a number | Right-click a visual element → Drill through → select destination page |
| Export data to Excel | Right-click a visual → Export data |
| Refresh data (Desktop only) | Home ribbon → Refresh data (updates local file only — does NOT update browser report) |
11 — Glossary
| Term | Definition |
|---|---|
| Power BI Desktop | The Windows application (.pbix file) used to build reports. Used by developers and administrators. |
| Power BI Service | The cloud version at app.powerbi.com where published reports are viewed, shared, and automatically refreshed. |
| Semantic model / Dataset | The combination of data tables, measures, and relationships powering the report. |
| Measure | A DAX formula that calculates a value dynamically. Example: Net Sales = SUM('Actuals Net Sales'[NetSalesAmountLCY]). |
| Column | A raw data field in a table, sourced directly from the LS Central database. |
| DAX | Data Analysis Expressions — the formula language for measures in Power BI. Similar to Excel formulas. |
| Filter context | The combination of all active filters at any moment — determines what each measure calculates. |
| Fact Table | The central table with transaction records (one row per transaction line). Main example: Actuals Net Sales. |
| Dimension Table | A lookup table with one row per entity (item, store, staff, date). Used for filtering and labelling. |
| Relationship | A link between two tables that allows filter selections to flow from dimension to fact table. |
| Slicer | An on-canvas filter control. Clicking a value filters all other visuals on the page. |
| Cross-filtering | When clicking a visual element automatically filters all other visuals on the page. |
| Power Query | The data transformation layer that loads and shapes data from LS Central into the model. |
| Applied Steps | The recorded list of transformations in Power Query (connect, select, rename, fix types, etc.). |
| LCY | Local Currency. Amount columns ending in "LCY" are in the company's local currency. |
| SK_ | Surrogate Key. Internal numeric IDs linking fact rows to dimension tables. Hidden from report visuals. |
| Desktop refresh vs Service refresh | Two independent operations. Desktop refresh updates the local .pbix file only. Service refresh updates the cloud report only. Publishing links them. |
12 — Further Resources
- Analytics help documentation: help.lscentral.lsretail.com — Analytics Reports
- Watch a quick video for this guide directly on YouTube
Analytics - Power BI Guide - Microsoft Power BI documentation: learn.microsoft.com/power-bi
- Microsoft Power BI community: community.fabric.microsoft.com/powerbi
- For report customisation, new measures, or connection issues — contact your LS Retail partner.
SUPPORT: If a measure shows unexpected results, check: (1) which filters are active in the Filters pane, (2) whether the browser report has been refreshed recently, and (3) whether you are viewing the browser (Service) version or a Desktop file. Include this information when contacting your LS Retail partner.