Power BI or POS Reports for Your Restaurant: What to Choose

When iiko or r_keeper reports are enough for a restaurant

Open the report together with the manager. Check sales, receipt count, discounts, and available inventory metrics. Drill down from the total amount to the original transaction. Review permissions, filters, and the analysis workflow. Then write down the questions for which you still have to merge files manually.

Start with a regular meeting on location operations. Ask for answers to the questions you typically ask the manager.

• What happened with sales yesterday?
• During which hours was the venue busy?
• Which dishes were selling?
• Where did write-offs occur?

Document the report and filter for each answer. Check whether the manager can repeat the steps independently. If the required information is readily available, establish a standard process for using it. Use any remaining gaps to define requirements for the next tool.

Check mobile access. iiko offers the iikoDashboard app for viewing reports. Permissions for reports are configured separately. Open the required metrics on the owner's device and test their access. Then determine which questions you can already resolve this way.

For r_keeper, check your specific version and available reports. Select a target period and a sample document. Find the metric, drilldown details, and user permissions in your deployment. Save your test results to include verified capabilities in the comparison.

If you need expenses from 1C, targets from Excel, and delivery calculations, describe how you will merge these sources. First, verify data availability and comparability. For product metrics, prepare inventory counts, recipe cards, and documentation. After that, evaluate the scope of automation.

Criteria for comparing analytics tools

Use your own benchmark period. Select closed sales, a clear objective, and a list of users. Using a single dataset, verify calculations, updates, and error corrections. This lets you assess the routine tasks your team will repeat after launch.

Setup effort. List available data exports, catalogs, formulas, dashboards, and permissions. Note what is ready and what still needs to be built. Test the template against your recipes and accounting structure. Record who is responsible for preparing each data source.

Data sources and locations. Check how to consolidate different POS systems and databases. Map dishes, ingredients, and locations. Resolve identical names with different meanings and different names for the same item. Save a mapping table so another team member can verify the consolidation.

Freshness. Record the time when the source document appears, when it is loaded, and when the screen updates. Test this sequence during a benchmark period. Display the date of the last successful load and the status of incomplete data. If there is a delay, the manager should see which data source is still pending.

Access and maintenance. Determine who views reports from a phone, updates formulas, and troubleshoots errors. Diagram data storage and backups. Discuss data location and transfers through international services with your IT team and corporate legal counsel. Include intermediate components in this review.

How to compare POS, Power BI, DataLens, Looker Studio, Metabase, Superset, and Excel

The tables summarize workflows and test questions. Check them against your setup and permissions. Confirm the terms of your chosen setup with the vendor. Include compatibility, limitations, mobile access, and data storage in your inquiry. For Power BI, also confirm refresh frequency, licensing, payment methods, and availability in Kazakhstan.

Based on test results, document confirmed capabilities and open questions. For each row, specify the version, access permissions, and verified dataset. This helps you evaluate the team's future work and revisit the rationale behind your decision after launch.

What you can retrieve via the iiko API

iiko has an API. OLAP reports are available via the iikoServer API, including hourly revenue and receipt count. A breakdown on Habr covers the reports/olap method with the SALES type. Example of retrieving OLAP reports

Check the official iiko documentation for your version to confirm the current method, permissions, and availability of required fields. Take a sample from a closed day and reconcile it with the POS system. For iikoCloud API and iikoServer API, verify their purpose and available reports separately before selecting a connection.

Start integration with a data sample. For iiko, r_keeper, and 1C, gather available exports or API responses for the required sales, inventory, and documents. Document the fields, history, and refresh rules. For each metric, determine the source and the method to verify totals.

For DataLens, check the availability of the required connection. The availability of an official prebuilt iiko connector requires separate confirmation. Consider intermediate storage and a supported connection, then verify viability on your own data. Document the entire transfer chain in the integration diagram.

Independent iiko connectors exist for ClickHouse and BigQuery to connect with DataLens or Power BI. Treat this connector as an independent component with its own terms and data transfer responsibilities. Check supported fields, completeness of history, and availability for your venue with a test upload.

Define the role of 1C. If it already holds a significant share of your management data, include it when planning data sources. The general approach is described in the article sales dashboard from 1C. For a restaurant, align on recipe cards, periods, and metric definitions separately.

When Excel is more practical than a dedicated BI system

Suppose a hypothetical cafe has a single POS terminal, closed inventory balances, and a few questions for the weekly meeting. This is a fictional scenario. Check the formulas in an approved spreadsheet. If your team understands how updates work and prepares data in time for review, start with this approach.

Walk through the calculation line by line. Together with the manager, verify source data and the logic for each formula. Assign a file owner, maintain versions, and separate data entry from calculations. Determine which copy you use in meetings and how you make corrections.

Track repetitive work. If an employee merges the same data exports every time, document the steps. Note manual fixes and areas where errors are difficult to detect. Use this list to assess which part of the process is worth automating and who will maintain it.

You can keep planned targets in an approved Excel template while pulling actual figures from the POS and accounting records. Maintain a consistent structure, an update date, and a designated owner. Ensure the person entering plan targets understands spreadsheet rules and the correction procedure.

When to choose DataLens, Looker Studio, Metabase, or Superset

Include these tools in your comparison based on data sources and team expertise. Check data transfer, formulas, and refresh performance for a benchmark period. Assign someone who can maintain the result. For any open questions, refer back to the overall checklist of requirements for your chosen setup.

Yandex DataLens. The service provides documentation for the ru-kz zone. For your venue in Kazakhstan, confirm availability, terms, required connections, and component locations separately. Test your chosen setup on sample POS data and record the results.

Looker Studio. Show available POS and inventory sources. Check how they flow into reports, how to adjust past periods, and what limitations apply. Test data loading, editing a source document, and reconciling the totals again.

Metabase or Superset. Discuss deployment with IT. Distribute uptime, updates, access permissions, and recovery among designated owners. If you lack an internal team, determine who will take on these responsibilities. Then test the selected solution together with the person who will maintain it.

For each option, save the formula and validation from raw data rows. With this documentation, you can verify why a specific metric appeared. Calculation quality depends on the data model and accounting rules. Appoint an owner for these rules before launch.

When a specialized restaurant analytics service is more practical

Check preconfigured restaurant metrics. In Kazakhstan, options include Choco "Smart Restaurant" and BEAST. BEAST claims compatibility with iiko. Verify specific compatibility on your own installation. Add these services to your list of options and evaluate whether their workflows address your questions.

Ask to see the path from the final total down to source transactions. Review actual food cost, write off records, and recalculation after inventory adjustments. Compare the formula against your own definition. Discuss any discrepancies with the manager before starting regular reporting.

Check multiple locations, different menus, and any requirements for 1C data. Present a use case that requires an additional source. Include the necessary granularity, permissions, and history in the test. This allows you to determine what scope the preconfigured model covers and what still needs configuration.

Evaluate offboarding from the service. Agree on the format, timeframe, and contents of historical data exports. Appoint someone responsible for documenting calculation formulas. Check whether you can continue working with your data and business rules if you change solutions. Save the answers alongside your test results.

When you do not need Power BI

If you get verifiable answers from your current reports on time, keep using them. Before deploying a dedicated BI system, evaluate the readiness of your sources and team. Use the list below to determine which step will help you achieve the required results right now.

• The POS handles the issue. Metrics and detailed breakdowns are available, and your employee knows how to use them. Set up regular reviews and assign an owner for them.
• Formulas are still under discussion. Test definitions on a short closed period in a spreadsheet. Align the results with the manager and accountant.
• You need clean source data. Recover missing invoices, update recipe cards, and reconcile inventory. Check the completeness of the period before automating.
• You need to assign a maintainer. Identify the person responsible for master data, data uploads, and formulas. Grant them access permissions and establish a troubleshooting procedure.
• A turnkey service covers the task. Verify its formulas, permissions, and history. Based on the results, determine how much configuration is sufficient.

Consider Power BI when regularly combining data sources. Align on metrics and shared dimensions across locations. Test them over a benchmark period, then compare maintenance and licensing terms with other options. This allows you to justify your choice based on your actual business needs.

How to test the selected tool on your venue's data

Take a completed period with sales, documents, and stock balances. Suppose you are testing a hypothetical chain with cafes in Almaty and Astana. This is a fictional scenario. Choose comparable locations and days. Show rent and staffing as separate, clear expenses.

Reconcile a single amount from the source to the screen. Find it in the POS, the calculation, and the report. Fix a test error in a copy of the data, update the result, and repeat the reconciliation. Check the product cost calculation using the article on food cost, and variance handling using the article on checking losses.

For Wolt, Glovo, and Yandex Eats, verify sales records and contractual withholdings. Make sure a delivery order already in the POS is included in revenue only once. Match Kaspi payments with sales according to an agreed rule. For interest from 2GIS, note what connection to receipts you can confirm.

Open the result on the owner's phone. Check the period, the update date, and navigation to the root cause of a variance. Check how the report behaves when a data source is unavailable. Log in separately with manager permissions and verify access to data for their location.

Ask another trained team member to repeat the update and explain the formula. Clarify the procedure for difficult steps. Document the owners of source data, the model, and access permissions. Save recovery instructions so the team can get back to work after a failure.

The metrics and launch process are outlined in the restaurant analytics guide. Use it to draft your requirements. Write down the question, verification of the number, and the manager's action after reviewing the report.

Frequently asked questions

What is Power BI and does a restaurant need it?

Power BI is a tool for data analysis and building reports with metrics and charts. Consider it if you regularly reconcile POS data, 1C, and plans. If your current reports already provide the answers you need, start by using them and reviewing them regularly.

Can you connect iiko directly to Power BI?

Check your version, available reports, permissions, and data transfer method. Start with an iiko API sample or an export and reconcile a closed day. Depending on the chosen setup, intermediate data loading may be required. Confirm the connection components before starting work.

How often will Power BI data be updated?

Confirm the frequency and limitations for the chosen setup. Check POS data readiness, transfer, processing, and the screen. For final actual food cost, also close inventory documents and stock balances. Show the user the status of these data sources.

Which is better for multiple restaurants, POS or BI?

Check the consolidated POS report for the required locations and period. If you have different sources, plans, and accounting rules, evaluate combining them. Choose based on management questions, available data, and the routine tasks your team will repeat after launch.

Where will restaurant data be stored?

Map out your sources, intermediate storage, and backups. Confirm the location of each component and the access procedure. Review data transfers through foreign services with your IT team and corporate legal counsel using this diagram.

Who should maintain analytics after launch?

Assign someone responsible for formulas and data quality. Assign the technical side to an employee or contractor with the relevant expertise. Agree on who responds to missed data loads, catalog updates, and access failures. Test this procedure with a trial refresh.