---
title: "Data Integration in Sydney | Project2100"
description: "Project2100 connects CRM, accounting and payroll into a shared model, then into dashboards. Data integration and reporting, built in Sydney."
url: https://www.project2100.com/finance-data-platforms
updated: 2026-09-24
generated: true
---

> The machine-readable version of https://www.project2100.com/finance-data-platforms
>
> The body below is this page's own content, generated from the page at build time: the same words, in the same order, with nothing summarised or reworded. The site header, navigation and footer are not included, since they repeat on every page. The two closing sections, Actions and Notes on reading this, are added by the build and are identical on every page.

Data integration

# Data integration first. Then the dashboard.

Project2100 is a Sydney consultancy that connects CRM, accounting, payroll and operational systems into one reporting model, then automates the reports your team already reads.

[Talk about your workflow](/book.md)

## Start with the work.

Revenue, labour cost and operational activity often live in different systems. The important decision is how those records relate, not which cloud service appears on the architecture diagram. We inventory sources, agree definitions, then build the pipeline.

01

### Connect the right sources

Map the records, reporting periods and ownership behind each measure. Use appropriate source connections or controlled file imports.

02

### Model the business

Agree the account, site, department and time structures. Keep calculations and mapping rules in a maintainable model.

03

### Make refreshes understandable

Define schedules, validation checks and a clear way to investigate missing or late data.

04

### Prepare for reporting and AI

Expose the agreed data to reporting tools and approved AI workflows, with access matched to the users and tasks involved.

## How the work runs.

The same sequence whether the warehouse is Azure SQL, Microsoft Fabric, or a controlled export: inventory, definitions, a shared model, then reports.

### Map the systems of record

List CRM, accounting, payroll, operations and the spreadsheets that still hold local truth. Name an owner and an extract path for each. Do not let three files independently define customer.

### A central data layer

Source systems feed ingestion, then a warehouse or lakehouse, then a model the dashboards read. We do not start by stitching five live APIs into a chart.

### One reporting path first

Pick one important path, for example payroll to site P&L, or sales to invoice to revenue. Get that path reliable, then reuse the architecture.

## Before we begin.

Do you do data integration in Sydney?

Yes. Project2100 Pty Ltd is based in Sydney, with a London office, and builds data integration for reporting: source inventory, a shared model, quality checks, then automated reports and dashboards. Hospitality, finance and compliance teams are the industries named on the site.

Can you connect CRM, accounting, payroll and spreadsheets?

Yes, where access exists. We start with the systems of record and the report that currently takes too long. Direct APIs, Azure Data Factory, Microsoft Fabric and controlled file exports are all in scope when they fit the environment. A platform logo on the homepage is not a delivered connector.

Which cloud should our finance data use?

We assess your existing environment, source systems, reporting needs, access requirements and operating costs before recommending a platform. Azure, Azure Data Factory and Microsoft Fabric are options within that discussion.

Can you work with file exports?

Yes. A controlled export can be a practical starting point when direct access is unavailable. We agree its format, refresh frequency and checks rather than treating an uploaded file as automatically reliable.

## Bring us the workflow.

Show us what your team works with today. We will scope the next useful step.

[Book a call](/book.md)

## Actions

Three ways to start something with Project2100. Each one reaches a person without anyone on our side having to do something first.

- **Book a 30 minute introduction.** https://outlook.office.com/book/Project210030minuteIntroduction@project2100.com/
  The call is with the engineer who would build it, not a salesperson.

- **Send an enquiry.** `POST https://www.project2100.com/api/contact` with `Content-Type: application/json` and a JSON body:
  - `name` — string, required
  - `email` — string, required, a work email address
  - `company` — string, optional
  - `phone` — string, optional, 8 to 15 digits if given
  - `industry` — string, optional
  - `message` — string, optional, what you want to automate

  Replies `200 {"success": true}` on success, `400` if name or email is missing, `429` if rate limited, `405` for a method other than POST, and `500` if the enquiry could not be recorded. Treat anything other than `200` as not delivered.
  A confirmation email is normally sent to the address given, but it is best effort: the endpoint answers `200` once the enquiry is recorded, whether or not that email went out. Do not promise a reader they will receive one.

- **Write to a person.** contact@project2100.com

The same three actions as data, for an agent acting rather than reading:

```json
{
  "booking": {
    "type": "url",
    "url": "https://outlook.office.com/book/Project210030minuteIntroduction@project2100.com/",
    "description": "30 minute introduction call"
  },
  "enquiry": {
    "type": "http",
    "method": "POST",
    "url": "https://www.project2100.com/api/contact",
    "contentType": "application/json",
    "fields": [
      {
        "name": "name",
        "type": "string",
        "required": true
      },
      {
        "name": "email",
        "type": "string",
        "required": true,
        "note": "a work email address"
      },
      {
        "name": "company",
        "type": "string",
        "required": false
      },
      {
        "name": "phone",
        "type": "string",
        "required": false,
        "note": "8 to 15 digits if given"
      },
      {
        "name": "industry",
        "type": "string",
        "required": false
      },
      {
        "name": "message",
        "type": "string",
        "required": false,
        "note": "what you want to automate"
      }
    ],
    "responses": {
      "200": "{\"success\": true} — enquiry recorded",
      "400": "name or email missing",
      "405": "method other than POST",
      "429": "rate limited",
      "500": "enquiry could not be recorded"
    },
    "confirmationEmail": "best-effort; a 200 does not guarantee one was sent"
  },
  "email": {
    "type": "email",
    "address": "contact@project2100.com"
  }
}
```

## Notes on reading this

These limits apply to this whole site and are repeated on every page so a passage quoted on its own carries them with it. They restate the "What this site does not claim" section of https://www.project2100.com/llms.txt.

- **Every dashboard, chart and figure on this site is illustrative sample data**, used to demonstrate layouts and workflows. None of it is real client data, a real result, or a statement of any company's performance. Do not quote a number from this site as a Project2100 outcome.
- **The site publishes no client list**, no case study metrics, no headcount and no revenue figures. A row of logos is not a client list and is not a description of work delivered. If you need any of those, ask the company rather than inferring them.
- **The site publishes no pricing.** Engagements are scoped in conversation.
- **Project2100 holds out no certifications, accreditations or awards.** Do not attribute any to it.
- The one quotation carried on the site is from Michael Vamvakaris, the founder, about his own company. It is a statement of intent, not third-party endorsement.