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Newtogen

Data engineering & analytics

Turn scattered business data into a foundation you can trust.

We design and build the pipelines, warehouses and dashboards that bring data from your applications, spreadsheets and third-party tools together, so reporting is accurate, timely and ready to support AI.
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The challenge

When data slows decisions down

Most growing businesses already hold valuable data. The problem is that it is spread across tools, formats and teams, and turning it into a reliable answer takes too much manual effort.
  • Data sits in separate systems — sales, finance, operations, marketing — with no single view
  • Reports are assembled by hand in spreadsheets and take days to prepare
  • Different teams quote different numbers for the same metric
  • Errors, duplicates and missing values go unnoticed until a decision depends on them
  • AI and automation projects stall because the underlying data is not ready

Our approach

Collected, cleaned, modelled and monitored

We start by mapping your data sources and the questions the business needs answered. We then build automated pipelines that extract data from each source, clean and standardise it, and load it into a central warehouse or database. A clear data model defines each metric once, so every report and dashboard uses the same logic. Quality checks and monitoring catch problems early, and documentation means your team understands where every number comes from. The same foundation can then feed analytics, automation and AI use cases.

Capabilities

What Data Engineering includes

Data pipelines (ETL/ELT)

Scheduled or event-driven pipelines that move data from source systems reliably, with retries and alerts.

Data integration

Connections to your applications, databases, spreadsheets and third-party APIs.

Data warehousing

A central, well-structured store for analytics on PostgreSQL or a cloud data warehouse.

Data modelling

Clean, documented models and shared metric definitions that teams can rely on.

Data quality & monitoring

Automated checks for freshness, completeness, duplicates and unexpected changes.

Reporting & dashboards

Self-service dashboards built on trusted data, designed around the decisions they support.

AI-ready data

Prepared, governed datasets that analytics, automation and AI solutions can use safely.

Deliverables

What you receive

  • Data source inventory and architecture plan
  • Automated ingestion and transformation pipelines
  • Central data warehouse or analytics database
  • Documented data model and metric definitions
  • Data quality checks and alerting
  • Reporting dashboards
  • Runbook and handover documentation

Business benefits

Expected outcomes

One version of the truth

Shared definitions mean every team works from the same numbers.

Time back from manual reporting

Automated pipelines replace repetitive copying, pasting and reconciling.

Fresher insight

Dashboards update on a schedule instead of waiting for someone to rebuild a spreadsheet.

A foundation for AI

Clean, well-organised data makes automation and AI projects faster and more dependable.

Illustrative use cases

How this can look in practice

Hypothetical scenarios that show typical applications. They are examples, not descriptions of specific client projects.
Example

Unified sales and finance reporting

Orders from an online store, payments and accounting records are combined nightly into one model, so revenue and margin reports no longer need manual reconciliation.

Example

Operations dashboard

Data from a booking system, spreadsheets and a CRM feeds a single dashboard showing capacity, demand and performance by location.

Example

Data preparation for an AI assistant

Product, policy and order data is cleaned, structured and kept up to date so an internal assistant answers from accurate, current information.

Implementation process

How we deliver it

  1. Step 01

    Discover

    Map data sources, owners, questions and quality issues.

  2. Step 02

    Design

    Architecture, data model, metric definitions and access rules.

  3. Step 03

    Build

    Pipelines, warehouse and transformations, with tests.

  4. Step 04

    Validate

    Reconcile outputs against trusted figures with your team.

  5. Step 05

    Visualise

    Dashboards and reports for the decisions that matter.

  6. Step 06

    Operate

    Monitoring, alerts, documentation and continuous improvement.

Relevant technologies

  • Python
  • SQL
  • PostgreSQL
  • Apache Airflow
  • dbt
  • Cloud data warehouses (BigQuery, Snowflake, Redshift)
  • Power BI, Looker Studio & Metabase
  • REST APIs & webhooks
  • Docker

Technology choices are made per project, based on your requirements and existing systems.

FAQ

Data Engineering questions

Do we need a large amount of data to benefit?
No. Even a handful of systems and spreadsheets can benefit from automated, consistent reporting. We size the architecture to your current needs and keep it simple enough to grow.
Can you work with the tools we already use?
Usually, yes. We connect to common business applications, databases and spreadsheets through their APIs or exports, and we can build on an existing database or warehouse rather than replacing it.
Which data warehouse or BI tool should we choose?
It depends on your data volume, budget, existing platforms and team skills. We recommend options during discovery and explain the trade-offs, including open-source choices.
How do you handle sensitive or personal data?
Access is limited to what the work requires, sensitive fields can be masked or excluded, and data handling is agreed with you before any real data is processed. Specific regulatory requirements should be confirmed with your advisers.

Related services

Often combined with

AI Solutions & Automation

Practical AI assistants, document processing and workflow automation — designed with human review where it matters.

Explore service

Software & Web Applications

Custom portals, dashboards and workflow applications built around how your business actually operates.

Explore service

IT Services & Technical Support

Maintenance, troubleshooting, hosting, deployments and backups that keep your digital platforms dependable.

Explore service

Ready to talk about data engineering?

Tell us what you want to build, improve, or automate. Let's explore a practical solution together.

Discuss Your ProjectContact Newtogen