The fiscal-period database problem
Many ERPs, led by Netsis and Logo, the ERP systems widely used in Türkiye, open a separate database for each year or fiscal period. That structure makes sense for closing the books, but it is a serious obstacle for reporting. A company with ten years of history has it split across ten separate databases; every comparison means running separate queries and combining the results by hand.
There is also a less well-known side to the problem: a database's name does not always tell you which year it actually holds. A database with one year in its name may in fact carry transactions from a neighboring year as well. A reporting tool that maps by name will show some years as empty or incomplete — and it will not warn you.
How does READERP merge them?
READERP does not map by database name; it counts the transactions inside. Each year is assigned to whichever database actually holds its records. The result is that all periods come together in a single time series.
| Database name (illustrative) | Years it actually holds |
|---|---|
| EXAMPLECO2019 | 2019 · 2020 |
| EXAMPLECO2021 | 2021 · 2022 |
| EXAMPLECO2023 | 2023 · 2024 |
| EXAMPLECO2025 | 2025 · 2026 |
In this example, the 2024 data sits in the database named 2023. A system that looks at names would show 2024 as empty; READERP connects it to the right place. Because it works read-only, not a single row is written to the ERP during this mapping.
What does a single time series give you?
- Year-over-year comparison: See this year's first quarter next to the same period of the last five years in one chart.
- Long-term trends: How sales have changed over the years by customer, product or region becomes visible.
- Seasonality: Which months are strong and which are weak shows up from many years of data, not just one.
- Unbroken account history: Follow a customer's payment behavior over the years on a single screen.
- Consistent definitions: Sales or receivables are calculated by the same rule every year; Excel formulas that change from year to year disappear.
An example question
"Which ten customers grew the most in the first quarter over the last four years?" Answering this in Excel means pulling separate lists from four databases, matching customer codes and merging the tables. With a single time series, the same question is answered with one report — or simply by asking it in plain language.
Checklist
- How many years of history to include in reporting
- Whether the fiscal-period databases sit on the same server or different servers
- Whether any period saw a change in code structure (customer/supplier account or inventory coding)
- Whether there has been a company merger or spin-off
- A few known figures you trust, for comparison
Frequently asked questions
What if the fiscal-period databases are on different servers?
As long as access is provided, periods on different servers can also be connected into the same time series.
Can we still compare if the coding changed at some point?
A matching rule is set up for periods where the code structure changed. We clarify this with you during the first check.
For the full service, go back to the ERP reporting page, or use the contact page to talk through your own period structure.