Sales, accounting and operations keep different identifiers and update information at different times.
Data analysis · Practical guide
How do you integrate data from different systems?
Collecting files is not enough. To analyse information from different sources, you need to understand what each field means, how records relate and where they come from.
Explore the guideThe central idea
Linked data still needs to make sense.
Data integration makes different sources usable together. A sales spreadsheet, an accounting system and an application may describe the same client with different names, identifiers and dates. Resolving those differences comes first.
At T2G we start with the task, its data and operating conditions. We agree on a scope that can be checked and explain technical decisions throughout the work.
Step by step
From separate sources to coherent information.
Four points to organise the work. Each diagram supports the explanation; the process adapts to its context.
- 01 / 04
Map the sources
Identify who maintains each source, how it is accessed and how often it changes. Check whether an API, export or query is available. Collect only the fields needed for the question and review permissions before moving information.
Spreadsheet · Application · Record - 02 / 04
Agree meaning and identity
Define what each record represents. A sale is not necessarily an invoice or a payment. Establish common identifiers and matching rules; a person’s or company’s name alone may not reliably link records.
Identity · Meaning · Relationship - 03 / 04
Validate before publishing
Check types, units, duplicates and missing values. Preserve source and update dates. Records that fail checks should remain visible for review rather than silently disappearing from the analysis.
Unify · Validate · Review - 04 / 04
Keep the flow observable
Agree update schedules, failure detection and how to repeat a load without duplicating records. Source format changes should be reported. Reports need to show the date their information represents.
Update · Check · Publish
An explained example
A shared view of clients and pending work
A mapping table links records, validation checks reveal duplicates and data retains its source. Analysis can show pending work with update dates and unresolved cases.
For your decision
What needs to be clear.
Identity
An explicit rule for linking records across sources.
Quality
Checks and a place to review exceptions.
Traceability
Known origin, load time and transformations.
Common questions
Questions before getting started.
Must existing systems be replaced?
Not necessarily. Exports or interfaces may connect information while each system remains the source for its own records.
Does this require a large data project?
Not always. A limited flow for one question supports learning before adding sources and complexity.
Keep exploring
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