Format variation
Each carrier file structure required its own source-to-target field mapping and processing logic.
Anonymous telecommunications analytics case study
Standardizing telecom billing data for web reporting
A telecommunications billing-analysis provider needed to ingest several carrier file formats, standardize their fields, and let customers review or export management reports through the web.
The situation
Monthly telecom insight depended on billing data that arrived in several incompatible formats.
The provider analyzed landline, mobile, voice, data, and paging charges for business customers. Management relied on a concise set of telecommunications performance indicators to spot areas that needed investigation.
Carrier data arrived as DBF, BIL, CSV, text, fixed-width DAT, and MDB files. Users needed a web system that could process those sources automatically, store standardized data, and make reports available for review or download.
The data challenge
Standardize different carrier files without hiding mapping errors or report rules.
The system needed a repeatable ingestion path, configurable management functions, and flexible report output across many customer accounts.
Management breadth
The web application needed upload, processing, report, client, configuration, and allocation controls.
Reliable reporting
Processed data had to support filters, totals, browser viewing, and several export formats.
The solution
Format-specific SSIS packages fed a managed pipeline and SSRS reporting layer.
The team separated each billing format into a dedicated import package, then used a coordinating package, web services, and SQL Server jobs to run the appropriate workflow.
- 01
Map each source
Define the field relationship between every carrier format and the standardized target data.
- 02
Orchestrate ingestion
Use a main SSIS package to select and manage the required format-specific subpackage.
- 03
Publish flexible reports
Use SSRS, database views, queries, and web services to generate filtered reports in browser and export formats.
How we worked
Separate source-specific parsing from the shared reporting model.
Field mapping clarified what each billing file contained and how it should enter the common database.
Dedicated subpackages isolated format rules, while a main package determined which processing path to invoke through web services and scheduled database work.
Report behavior was built on standardized data access and business entities so filtering, totals, and export options could be applied consistently.
01Map
Define source fields and the standardized target.
02Ingest
Run the correct format-specific SSIS package.
03Standardize
Store validated billing data in the shared model.
04Report
Generate web, PDF, Excel, or HTML output.
The result
The architecture created a repeatable path from varied billing files to consistent web reports.
The source documents a web reporting solution that combined format-specific ingestion, centralized orchestration, standardized data, and flexible report generation; it does not provide a quantified business result.
Multiple carrier formatshandled through dedicated mapping and import packages
One reporting modelfor billing, client, configuration, and allocation data
Several output optionsincluding browser, PDF, Excel, and HTML reports
Complexity stayed contained
A new or changed source format could be addressed in its own import package rather than rewriting the whole pipeline.
Management functions stayed connected
Upload, processing, setup, generation, client, configuration, and allocation work shared the same system.
Reports remained usable
Filters, totals, online review, and export choices supported different management needs.
Case taxonomy
Searchable by industry, technology, product, and business need.
Industry and product
- Telecommunications
- Telecom Billing
- Billing Analytics
- Web Reporting
Technology and delivery
- SSIS
- SSRS
- SQL Server
- Web Services
- ETL
Business need
- Data Mapping
- DBF
- BIL
- CSV
- Fixed-width Data
- Report Generation
- PDF Export
- Excel Export
Turn source variation into reporting clarity
Need a dependable reporting layer across inconsistent operational data?
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