Our data is in ERPNext. Can you build reporting on top of it?

Yes. We build Azure-based data layers on top of ERPNext for clients who need reporting that goes beyond what ERPNext's built-in reports provide particularly for multi-entity, multi-currency, or cross-module analytics.

We use Power BI already but the reports are slow and unreliable. Can you help?

Yes. Slow or unreliable Power BI is usually caused by reports querying source systems directly rather than a properly structured data warehouse. We build the data layer that Power BI should be connecting to.

What if our data quality is poor?

We assess data quality during the audit phase and tell you clearly what needs to be resolved. In some cases we can build data quality checks and transformation rules into the pipeline. In others, the source data needs to be improved before reliable reporting is possible.

Do we need to be on Azure already?

No. We can set up the Azure infrastructure as part of the project. You do not need an existing Azure environment, though we can work within one if it already exists.

DataEngineering&Reporting

Most businesses have more data than they can use. The problem is not data volume it is that the data lives in separate systems, is only accessible to those who built the report, and is always a week out of date. Techseria builds data pipelines, Azure data warehouses, and operational dashboards that give your team live, reliable information without the manual effort.

Discuss a Data Challenge See Data Unification Outcomes

What Techseria builds for data teams

Azure Data Warehouse: A centralized, structured repository for data from across your business systems ERP, CRM, finance, operations. Built on Azure Synapse Analytics or Azure SQL, with defined schemas and refresh schedules.

Operational Dashboards: Live Power BI or custom dashboards showing the metrics your team uses to manage the business not a static report produced once a month, but a view that updates as your operational systems update.

ETL / ELT Pipelines: Extract, transform, and load pipelines that move data reliably between systems on a schedule or in near-real-time. Built on Azure Data Factory or Python-based pipelines with monitoring and alerting.

Financial Consolidation & Reporting: Automated financial reporting that pulls from ERPNext or your accounting system, applies your consolidation rules, and produces the reports your finance team currently builds manually in Excel.

Inventory & Operations Analytics: Stock level trends, supplier performance, production throughput, and field service efficiency visible without opening the ERP and running queries.

When is data engineering the right investment?

A data engineering project adds clear value when:

Technology we use

Azure Data Factory: Managed ETL/ELT orchestration for moving and transforming data at scale. Connects to databases, APIs, file stores, and SaaS platforms.

Azure Synapse Analytics: For analytics workloads that require querying large datasets sales history, production records, multi-year financials at speed.

Power BI: Dashboard and reporting layer connected to your data warehouse. Deployed to your Microsoft 365 tenant so reports are accessible to the right people without additional tooling.

Python & dbt: For data transformation logic dbt provides version-controlled, testable SQL transformations. Python handles API integrations, custom extraction, and automation.

Process

How we deliver data engineering projects

01

Phase 1

Data Audit & Requirements

We map all data sources, assess data quality, and identify the specific metrics and reports the business needs. The output is a clear list of what will be built and what data quality issues need to be resolved first.

02

Phase 2

Pipeline & Warehouse Build

We build the data pipelines, warehouse schema, and transformation logic to a fixed-fee scope. Each pipeline is tested against your real data before delivery.

03

Phase 3

Dashboard Delivery & Handover

Dashboards are built and connected to the warehouse. We train the relevant team members on how to use and maintain the reports, and hand over documentation for the full data layer.

Impact

Techseria has built data warehouses and operational dashboards for manufacturers, distributors, and professional services businesses. Projects include ERPNext-to-Azure-Synapse pipelines, multi-site inventory reporting in Power BI, and financial consolidation dashboards replacing monthly Excel processes.

Spending too much time on manual reporting?

Tell us what reports your team produces, how long they take, and what data they pull from. We'll tell you what a data engineering project would look like and what it would take to replace the manual process.

Book a Data Discussion