Web application for statistics
Goal: to systematize information from various API sources into one report. (Please note that links to API statistics will need to be taken from partner APIs independently, so similar experience is required. Documentation and keys for all APIs will be provided - this is the most challenging part of the project).
It is necessary to write backend and frontend code, as well as deploy it on the server, making it a turnkey solution. Set up a working version.
The main data will come from several API sources.
Google Analytics
Partner APIs
Own API
Data from all APIs should go into tables, the unifying criterion is the store name/store domain. Priority is given to the domain.
Main sections of the frontend:
Settings
In this section, APIs are added
There are a total of three sections, each designated for APIs with different tasks.
1. Own API – own data
2. Statistics API - for Google API
3. Affiliate API - partner APIs (main section, there will be 15 APIs here)
In this section, all keys and addresses are filled in, as well as the names of tags for the report tables.
Store Directory
1. Store directory for analysis
This database of all stores from the OWN source, along with its linkage to other sources, should be used as the basis for generating all reports.
At the core (left column) should be the store name from the OWN API, its domain, and ID. Main requirements and functionality: the presence of automatic linkage to store names from partner APIs and manual linkage. Highlight manual linkage. Identification of stores from partner APIs in OWN occurs automatically by its URL (only the name without the domain zone with an exact match), if not possible by URL, then by its name from the partner API. In the right column, indicate all found options on partners, with the name of the partner and the store ID from it. All its variants regarding partner APIs will be linked to the store from the OWN source, and there can be many.
2. All stores from all sources
This is a database of all stores except OWN, as they are transmitted by the API. It should store all stores that come via the API, stored automatically, only replenished with new ones. It contains the structure of partner data: name, URL, ID, partner. This section is purely reference, no actions are performed in it, it should simply be linked to the Store Directory for analysis, it is used for manually filling this directory.
Reports
Should be exported to Excel
1. Affiliate presence
Columns are displayed for all partners, Network 1-20. There will be horizontal scrolling.
Filters: Priority
Sort by: Program Name / Priority / With higher commission / Without network / Google New users
in the table part
Check the box next to Rate – the network that is predominantly API
Put a star next to Rate – which is exclusively predominantly API
Coloring: red for Rates/Hold if the size is greater than that of the network selected in the main API,
yellow for the entire horizontal band if in the main API the store is without a network

2. Affiliate activity
Analysis of top stores
All stores are shown, including those without networks
Export of table data
Filters: There is a network/ no network, Dates from and to, Dates for comparison.
Comparison of Dates: occurs by adding rows below, data for substitution is only filled in the example. If there is data in the comparative period or in the current one for several networks, they are placed as shown below one under the other, sales, clicks, conversion respectively. The comparative period is always similar in the number of days mostly, an example can be taken from Google Analytics.
Sorting: Google New users

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Hello, I worked on a web application for statistics: I integrated 5 APIs, created tables and filters, automatic data binding from domains. Export to Excel - over three thousand rows.
What format of API from partners is provided: REST or SOAP? And do all keys have the same access rights?
I suggest we get in touch, I will consult you for free on the technical side and we will create a development plan + I will tell you about my team!
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416 1 0 Good day,
We are a team of developers with experience in creating complex analytical systems that integrate data from multiple API sources, including Google Analytics, proprietary APIs, and partner networks. We have reviewed your technical description — we can implement the project turnkey: from backend and frontend to deployment and setting up the working version.
Our approach to implementation:
Backend: NestJS / Node.js, integrations with external APIs, automatic data updates, table and report generation, export to Excel.
Frontend: React / Next.js — a modern interface with sections "Settings," "Store Directory," and "Reports," supporting filters, manual binding, and sorting.
Database: PostgreSQL or MongoDB, considering the volume and structure of data.
Integrations: Google Analytics API, partner APIs (with provided keys), proprietary API, reporting module with export to Excel.
Deployment: Docker / VPS / cloud environment (AWS, Render, Vercel).
What we will provide:
… Automatic retrieval and updating of data from partner APIs;
A flexible API settings system in the frontend;
The ability for manual and automatic store binding;
Report generation with filters, sorting, and export;
Stable, optimized system performance.
We have experience working with similar integration and analytical systems (including financial and marketing data). We are ready to discuss technical details, deadlines, and development stages after a brief call or clarification of API details.
Sincerely,
The development team
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3644 17 0 Hello! 👋
I am ready to create a single reporting portal with data aggregation from Google Analytics + 15+ partner APIs + Own API, with a back office for settings, directories, reports, and export to Excel — turnkey (backend, frontend, deployment).
The tech stack I propose:
Backend: Python FastAPI (or Django/DRF), PostgreSQL, SQLAlchemy, Celery+Redis, OAuth2 for GA, SDK/HTTPX for partner APIs.
Frontend: Next.js + TypeScript, TanStack Table (virtualization for large tables),
Infra/deployment: Docker, Nginx,
Excel: openpyxl/xlsxwriter, multi-sheet exports.
…
I am ready to start after discussing the details! 🚀
Best regards,
Andriy!
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1506 6 0 Good day!
I am interested in your project and I am ready to take on its execution. I have extensive experience in developing similar platforms and admin panels for them - I am happy to help.
I am open to communication and discussion of details.
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9972 117 0 Hello.
I am a NodeJS developer. I am ready to take on the task. Write to me, we will discuss.
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278 5 1 1 Hello! I will create a turnkey system for data collection from GA4, your OWN API, and 15 affiliate APIs with a single store directory and two reports with export to Excel.
What I will implement:
1. Configuration of three API groups (OWN, Statistics/GA4, Affiliate) with key verification.
2. Store directory: auto-linking by domain/name + manual linking with marking and history.
3. Affiliate presence report: networks Network1…N, priorities, preferred/exclusive markings, highlighting according to rate/hold/no network rules, filters, and sorting.
4. Affiliate activity report: top stores, comparison of two periods with added rows, filters for presence/absence of network and dates, sorting by Google New Users.
5. Export of reports to Excel with formatting.
6. Logs, retries to API, update schedule, access roles.
… 7. Deployment on the server, documentation, instructions.
Stack:
Backend: Python, FastAPI, PostgreSQL, Redis, Celery/APScheduler.
Frontend: React + TypeScript (Vite), AntD/MUI.
Integrations: GA4 Data API, affiliate API (15), OWN API.
Deployment: Docker, CI/CD, SSL.
Timeline and budget:
1. Discovery sprint – 12,000 UAH, 3–4 working days.
Result: architecture, ERD database schema, list and maps of fields for all APIs, matching rules by domain/name, prototype of the connector for 1 affiliate, layouts of two reports, and an exact estimate/work plan. The cost of this stage will be credited to the next sprint.
2. MVP (OWN + GA4 + 3 affiliates, 2 reports, export, matching):
3–4 weeks, $3000–3500.
3. Full version (all 15 affiliates):
6–8 weeks, $7500–9500.
The final amount will be agreed upon after a brief discussion regarding the list of APIs and metrics.
Clarifications:
1. Complete list of affiliate networks (15), access to their documentation, desired metrics: clicks, sales, commission, CR, hold, rates, etc.
2. GA4: property, account, access; clear definition of Google New Users (measurement/metric, filters).
3. OWN API: structure, store fields (id, name, domain), how we obtain priorities.
4. Matching rules: main key — domain without zone? what name transformations are allowed, how do we resolve collisions.
5. Exact rules for highlighting and markings in Affiliate presence (threshold values, main network, exclusive).
6. Update frequency (cron), data volume, time zones, SLA for relevance.
7. Roles/access, how many users, is an action audit needed.
8. Infrastructure: server/VPS, domain/SSL, is staging needed.
9. Acceptance criteria: what exactly is considered ready in MVP, what are the criteria for performance/export time.
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1562 7 0 Good day!
My name is Roman, and I am among the top 5 developers in the category of "Artificial Intelligence and Machine Learning" among ~1600 specialists on the platform.
I guarantee:
- Fast and high-quality completion of the task
- Strict adherence to deadlines
- Regular communication throughout the entire process
I would be happy to discuss the details of your project in private messages.
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297 1 Hello.
Thank you for the detailed requirements — this project is essentially a platform for aggregating and analyzing data from multiple sources, which combines API data (Google Analytics, affiliate networks, and your own system) into a single backend with automatic store matching, manual overrides, and dynamic reporting capabilities. I will develop both the backend and frontend from scratch, ensuring reliable API synchronization, intelligent data normalization by domain priority, and a scalable database schema optimized for reporting. On the frontend, I will implement an intuitive interface for API configuration, store management, and analytical dashboards that can be exported to Excel, with advanced filtering, comparative views, and visual indicators. I will also handle the complete deployment, environment setup, and optimization for reliable operation. With experience in building high-load systems and analytical platforms based on APIs, I can provide a ready-made solution that is both technically robust and user-friendly.
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Єх, взявся б за роботу та не вистачає досвіду в подібних проектах, тому ставки не роблю. Саме закінчую курс аналітика даних також програмую на python. Маю пет проект з використанням бібліотеки reflex та декілька навчальних на основі looker studio та tableau. Якщо можу бути корисним в проекті то звертайтесь.
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