How to implement report generation in a mobile app

TRUETECH is engaged in the development, support and maintenance of iOS, Android, PWA mobile applications. We have extensive experience and expertise in publishing mobile applications in popular markets like Google Play, App Store, Amazon, AppGallery and others.

Development and support of all types of mobile applications:

Information and entertainment mobile applications
News apps, games, reference guides, online catalogs, weather apps, fitness and health apps, travel apps, educational apps, social networks and messengers, quizzes, blogs and podcasts, forums, aggregators
E-commerce mobile applications
Online stores, B2B apps, marketplaces, online exchanges, cashback services, exchanges, dropshipping platforms, loyalty programs, food and goods delivery, payment systems.
Business process management mobile applications
CRM systems, ERP systems, project management, sales team tools, financial management, production management, logistics and delivery management, HR management, data monitoring systems
Electronic services mobile applications
Classified ads platforms, online schools, online cinemas, electronic service platforms, cashback platforms, video hosting, thematic portals, online booking and scheduling platforms, online trading platforms

These are just some of the types of mobile applications we work with, and each of them may have its own specific features and functionality, tailored to the specific needs and goals of the client.

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How to implement report generation in a mobile app
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Users expect a 'Download PDF' button, but developers face device memory limits, asynchronous generation, and complex multi-page layout. Recently, a client came to us with a report of 5,000 rows — on Android it triggered OutOfMemoryError, and we urgently re-architected to server-side generation. Our team has 5+ years of experience in implementing report generation systems for mobile apps — we guarantee stable operation even with large data volumes. We will evaluate your project and offer a cost-optimal solution.

Without the right approach, reports can consume too much memory, throw errors on opening, or display empty rectangles instead of Cyrillic. We've stepped on these rakes on dozens of projects and know how to avoid typical pitfalls. As Apple recommends: Use UIActivityViewController to let users export files.

How to implement report generation in a mobile app

Successful implementation requires choosing an approach, formatting data, rendering, and exporting to the required format. Let's look at three main ways to generate PDF.

Three approaches to PDF generation

Native rendering via Canvas

On iOS — UIGraphicsPDFRenderer, the most controllable option. Draw each element manually via Core Graphics:

func generateReport(data: ReportData) -> Data {
    let pageRect = CGRect(x: 0, y: 0, width: 595, height: 842) // A4 in points
    let renderer = UIGraphicsPDFRenderer(bounds: pageRect)

    return renderer.pdfData { context in
        context.beginPage()
        let ctx = context.cgContext

        // Header
        let titleFont = UIFont.boldSystemFont(ofSize: 18)
        let title = data.title as NSString
        title.draw(at: CGPoint(x: 40, y: 40), withAttributes: [
            .font: titleFont,
            .foregroundColor: UIColor.black
        ])

        // Data table
        drawTable(ctx, rows: data.rows, startY: 80, pageWidth: pageRect.width)

        // If data doesn't fit — new page
        if needsNewPage {
            context.beginPage()
            // continue...
        }
    }
}

Labor-intensive, but the result is precise control over pixel output. Good for a fixed report template.

On Android via PdfDocument:

val document = PdfDocument()
val pageInfo = PdfDocument.PageInfo.Builder(595, 842, 1).create()
val page = document.startPage(pageInfo)
val canvas = page.canvas

val paint = Paint().apply { textSize = 18f; isFakeBoldText = true }
canvas.drawText(data.title, 40f, 60f, paint)

document.finishPage(page)
val stream = ByteArrayOutputStream()
document.writeTo(stream)
document.close()

HTML → PDF via WebView

Generate an HTML template and convert it to PDF. Easier for complex layouts, tables, and text blocks — HTML/CSS is more flexible than Canvas. On Flutter use printing + pdf package:

import 'package:pdf/widgets.dart' as pw;
import 'package:printing/printing.dart';

Future<Uint8List> buildPdf(ReportData data) async {
  final doc = pw.Document();
  final font = await PdfGoogleFonts.notoSansRegular();
  final boldFont = await PdfGoogleFonts.notoSansBold();

  doc.addPage(
    pw.MultiPage(
      pageFormat: PdfPageFormat.a4,
      build: (context) => [
        pw.Header(text: data.title, textStyle: pw.TextStyle(font: boldFont, fontSize: 18)),
        pw.SizedBox(height: 16),
        pw.TableHelper.fromTextArray(
          headers: data.headers,
          data: data.rows,
          cellStyle: pw.TextStyle(font: font, fontSize: 10),
        ),
      ],
    ),
  );
  return doc.save();
}

pw.MultiPage automatically splits into pages — solving the main problem of long reports.

Server-side generation (recommended for complex reports)

Reports with large data volumes, complex charts, or corporate branding are better generated on the server. Puppeteer (Node.js) renders HTML + Charts into PDF with browser engine accuracy. The client receives a link or file via WebSocket after completion.

This is the only right path if the report needs interactive charts (Echarts, Highcharts) — you can't render them on the device without WebView.

Parameter Native Canvas HTML → PDF WebView Server-side generation
Implementation complexity High Medium Low (client)
Layout control Full Depends on CSS Depends on HTML/CSS
Data volume Up to 50 pages Up to 100 pages Unlimited
Interactive charts No Via WebView Yes (Puppeteer)
Device memory High Medium Low

To choose the optimal solution, contact us — we will analyze your data and propose an approach.

Which report format to choose?

Besides PDF, CSV and Excel are often required. CSV is the lightest: data is written in delimiter-separated rows. The main nuance is encoding: Excel opens CSV in UTF-8 only with BOM (\uFEFF). Otherwise, Cyrillic turns into gibberish. Excel (xlsx) is more complex: you need a library that supports formulas, styles, and multiple sheets. For simple tables, CSV is sufficient. In practice, CSV with 10,000 rows generates on the device in under a second, while PDF with the same number of rows requires pagination.

Format Implementation complexity Style support File size Universality
PDF High Yes (fixed layout) Medium High (opens everywhere)
CSV Low No Small Medium (Excel, Numbers)
Excel Medium Yes (formulas, colors) Large High (Excel, Google Sheets)

What to choose: native rendering or HTML in PDF?

The choice depends on the complexity of the layout and data volume. For a fixed template with a small number of pages, native rendering is suitable. For complex tables and charts — HTML to PDF or server. Our experience shows that 80% of projects use a hybrid approach: simple reports on the device, complex ones on the server. We will help you choose the optimal turnkey solution.

CSV export

Simpler than PDF, but there are encoding nuances. Excel expects UTF-8 with BOM — otherwise Cyrillic displays as garbage. On Flutter:

String buildCsv(List<List<dynamic>> rows) {
  final buffer = StringBuffer();
  buffer.write('\uFEFF'); // UTF-8 BOM for correct opening in Excel
  for (final row in rows) {
    buffer.writeln(row.map((cell) {
      final str = cell.toString();
      // Escape cells with commas and quotes
      return str.contains(',') || str.contains('"')
          ? '"${str.replaceAll('"', '""')}"'
          : str;
    }).join(','));
  }
  return buffer.toString();
}

Sharing the generated file

share_plus on Flutter, UIActivityViewController on iOS, FileProvider + Intent.ACTION_SEND on Android. Saving to gallery / Files — via path_provider + open_filex.

On iOS you need NSPhotoLibraryAddUsageDescription in Info.plist for saving to Photos, UIFileSharingEnabled for file access via Files.app.

What typical problems occur during report generation?

Generating a PDF with a table of 10,000 rows on the device — OutOfMemoryError on Android or memory warning on iOS. Solution: data pagination, page-by-page generation, for large volumes — server.

Cyrillic in PDF without an embedded font — white rectangles instead of letters. Be sure to embed a custom font with Unicode support via pw.Font.ttf(...).

Problems with Excel: if using a library like excel (Dart), don't forget about row styles — otherwise the file won't open in old versions of Excel. We recommend always testing on real office suite versions.

Steps to implement report generation

  1. Analyze data and layouts: determine the format, volume, and type of reports.
  2. Choose an approach: native, HTML→PDF, or server-side.
  3. Develop templates with layout and font embedding.
  4. Integrate export and sharing.
  5. Test with real data (empty, large, with Cyrillic).
  6. Optimize memory and performance.

What's included in the work

  • Choosing the approach based on data specifics and layout (native / HTML→PDF / server)
  • Implementing report templates (PDF/CSV/Excel)
  • Integrating file sharing and saving
  • Handling edge cases: empty data, large volumes, page breaks

Timeframes

One PDF report template with basic formatting: 2–3 days. Multiple report types with charts and server-side generation: 1–2 weeks. Cost is calculated individually. Get a consultation for your project — we will implement a turnkey reporting system. Order development, and we will offer the optimal solution considering your data and budget.

More about Excel libraries

For Flutter, use the excel package (version 4.x) — it supports styles, cell merging, and formulas. For Android — Apache POI (via JNI or server). For iOS — SwiftExcel or xlsxwriter. The choice depends on report complexity and development time.

Mobile App Analytics: Firebase, Amplitude, AppsFlyer and Attribution

Our team regularly encounters projects where analytics is already "set up" but yields no real insights. A typical example is a startup with 50k DAU: tracking dozens of events without a single answer to the question "why don't users reach payment?". In two weeks we built a basic funnel and found that 70% of users drop off at the phone number verification screen. After fixing the bug, retention increased by 12%. The takeaway: analytics should start with specific questions, not tracking everything indiscriminately.

Why Event Taxonomy is the Foundation of Mobile App Analytics?

Firebase Analytics, Amplitude, Mixpanel — technically similar. The difference lies in what you put into them. A common mistake: events like screen_view, button_tap_1, button_tap_2 without context. A month later, no one remembers what button_tap_2 means.

Proper taxonomy: object + action + context. product_viewed, checkout_started, payment_completed with parameters product_id, category, price, source. This allows building funnels, cohort analysis, and retention without additional tracking.

We document the naming convention in a tracking plan — a document (Google Sheet or Amplitude Data Catalog) describing every event, its parameters, and triggering conditions. The tracking plan is synced with the analytics team before development begins, not after. This approach ensures that data remains interpretable months later and doesn't become a dump. Experience from 50+ projects confirms: without a tracking plan, analytics maintenance costs increase 2-3 times due to rework.

What Should You Choose for Mobile App Analytics: Firebase, Amplitude, or Mixpanel?

The table below highlights key differences between the three popular platforms. Choice depends on budget, traffic, and tasks.

Criteria Firebase Analytics Amplitude Mixpanel
Free limit Unlimited (Spark plan) Up to 10M events/month Up to 1K MTU/month (Special)
Data latency Up to 24 hours (standard) Minutes (real-time) Minutes (real-time)
Funnels and cohorts Basic funnels, limited count Deep funnels, Journeys, cohorts Funnels, Retention, Insights
BigQuery export Yes (free, raw data) Yes (subscription) Yes (Enterprise)
Session Replay No Yes (iOS/Android SDK) No
Ad integration Google Ads (native) Via Universal Links Via partners

Firebase Analytics — free, deep integration with Google Ads, BigQuery export for raw data. Limitations: data latency up to 24 hours, limited funnels. For startups with Google Ads traffic, it's the first choice.

Amplitude — product analytics focused on cohorts and user journeys. Journeys (formerly Pathfinder) shows actual paths between events — not assumed funnels but real routes. Session Replay records sessions for UX analysis. The free tier up to 10M events/month is enough for most products at launch.

Mixpanel — close to Amplitude, stronger in real-time segmentation. Insights, Funnels, Retention cover 90% of product analysts' tasks.

How to Solve Multi-Channel Attribution with AppsFlyer?

Knowing where a user came from is a separate task. Firebase Attribution works only within the Google ecosystem. For multi-channel attribution (Facebook Ads, TikTok, Apple Search Ads, programmatic), an MMP (Mobile Measurement Partner) is needed.

AppsFlyer is the market leader. OneLink — universal deep link working on iOS and Android, correctly attributing installs from any channel. Protect360 — built-in fraud protection (fake installs, click injection on Android). Adjust and Branch are competitors with similar features. Branch excels in deep linking; Adjust is popular in gaming.

According to Apple, with iOS 14.5, apps must obtain user permission via ATT before collecting IDFA for tracking. AppsFlyer uses probabilistic matching (IP + user agent + timing) for these users — accuracy is lower but better than nothing. SKAdNetwork and Privacy Preserving Attribution provide aggregated data from Apple with a 24-72 hour delay.

How to Set Up Crash Analytics to Not Miss Bugs?

Firebase Crashlytics is the standard for crash reporting. It automatically groups crashes by stack trace, shows affected users %, and sends velocity alerts when crash rate increases by more than 10% per hour.

Important: symbolication. On iOS, .dSYM files must be automatically uploaded with each build — via Fastlane upload_symbols_to_crashlytics or Xcode Cloud built-in. Without symbols, crashes in Crashlytics appear as memory addresses. This happens more often than expected when switching to a new CI — in one project with 500k users, we found that 40% of crashes remained unsymbolicated due to a missing CI/CD step. After automation, bug response time dropped from 3 hours to 15 minutes.

For React Native and Flutter, @sentry/react-native and sentry_flutter provide additional context: breadcrumbs, network requests before the crash, Redux/Provider state.

Below is a comparison of popular crash analytics tools to choose according to your needs.

Criteria Firebase Crashlytics Sentry Instabug
Free limit Unlimited (Spark) 5k events/month 250 MAU
Grouping By stack trace + parameters By fingerprint By stack trace + metadata
Symbolication Automatic (via file) Automatic (via CLI) Automatic
Velocity alerts Yes (by % change) Yes (by count) Yes (by threshold)
Extra context Logs, Keys, Custom Keys Breadcrumbs, User, Tags User steps, network requests
Price Free (in Firebase) Paid plans available Paid plans available

Environment Setup

Three environments with separate Firebase projects: dev, staging, production. Mixing analytics from test sessions and production is a common mistake that skews all metrics. On iOS via GoogleService-Info.plist per scheme, on Android via google-services.json in each flavor folder.

Timelines: basic analytics with Firebase + Crashlytics — 3-5 days. Full tracking plan + Amplitude/Mixpanel with funnels and cohorts — 2-3 weeks. Attribution via AppsFlyer with deep linking and fraud protection — 1-2 weeks. Cost is calculated individually based on integration complexity.

What Is Included in Our Work

As part of analytics implementation, we provide:

  • Development and approval of a tracking plan with product and marketing teams.
  • SDK integration (Firebase, Amplitude, Mixpanel, AppsFlyer) considering your stack (Swift/Kotlin/Flutter/React Native).
  • Setup of funnels, cohorts, dashboards, and alerts.
  • Automation of symbolication and .dSYM upload via Fastlane.
  • Documentation of events and parameters.
  • Team training on the analytics platform.
  • Two weeks of post-release support and tracking adjustments.

Our experience: 7 years of analytics implementation and over 80 successful projects in mobile development. We guarantee data correctness and transparency at every stage.

Contact us for a consultation on setting up analytics for your app. Request an audit of your current analytics — and we will show you which metrics you are losing.