vectorient

How we work

This is what a data project with vectorient looks like.

We find out what you have and where, propose a plan in stages and deliver something useful as early as possible, even if it's simple. From there we grow, all in your cloud.

Contact usSee the project step by step

The project, step by step.

  1. 1

    Diagnosis

    What do you have, and where?

    We review your systems, reports and files, and understand what hurts and which decisions depend on it.

  2. 2

    Plan and proposal

    What will we deliver?

    A plan in stages with concrete deliverables, clear scope and timelines.

  3. 3

    First delivery

    What can we use now?

    If there's nothing yet, we start with a base business dashboard: simple, but useful from day one.

  4. 4

    Expansion

    What's next?

    We add sources, areas, automations and models on the same foundation.

How we run it.

We work in Scrum: short deliveries, clear priorities and progress you can see.

  • Short sprints

    Every sprint ends with something you can see and use.

  • Priorities set with you

    The backlog is ordered by business impact, and you decide what goes first.

  • A demo at every close

    We review what was built with your team and adjust course.

  • One project lead

    A single point of contact, visible progress and risks flagged early.

Inside: the data pipeline.

An automated process (ETL) takes the information from your systems to the dashboard, every day, with no manual work.

  1. 1

    Extract

    We copy the data from each system (ERP, point of sale, APIs, spreadsheets) on a schedule.

  2. 2

    Load

    We store it as it arrives, with its history, in your cloud.

  3. 3

    Clean

    We remove duplicates, fix dates and types and check against the sources.

  4. 4

    Transform

    We apply your business rules and define each metric once.

  5. 5

    Serve

    Tables ready for dashboards, reports, alerts and models.

Where your data lives.

  1. Data lake

    Low-cost storage for everything that arrives, raw and with its history.

  2. Data warehouse

    Clean, modeled tables, fast to query and ready for BI.

  3. Lakehouse

    The best of both on one platform, like Databricks, when the volume and the use cases call for it.

Not every company needs all three. We choose based on your size, your data and your team.

Architecture: your cloud, well protected.

We build with the practices of an enterprise data platform, sized to yours.

Your systems

  • POS
  • ERP
  • Spreadsheets
Encrypted, read-only connection

Your cloud account

Private network

  1. Ingestion
  2. Data lake
  3. Warehouse

Encrypted with keys in your account

  • Role-based access
  • Audit log
  • Monitoring and alerts
  • Backups
Single sign-on and MFA

Your team

Dashboards and reports

  • Private networks

    Private subnets and encrypted connections; nothing exposed to the internet without need.

  • Identity and access

    Single sign-on, MFA and least-privilege permissions by role.

  • Encryption

    In transit (TLS) and at rest, with keys managed in your account.

  • Data governance

    A catalog, an owner for each dataset, lineage and access policies.

  • Data quality

    Tests and reconciliation on every load, with alerts when something doesn't tie out.

  • Monitoring and auditing

    A log of access and changes, and alerts when a process fails.

  • Backups and recovery

    Versions and history to restore after any mistake.

  • Infrastructure as code

    Everything defined in code, reviewed and reproducible.

  • Continuous delivery (CI/CD)

    Changes tested and deployed automatically and under control.

  • Cost control

    Budgets and alerts so the bill holds no surprises.

Tools sized to your company.

A company that's starting out can solve it with BigQuery and Looker Studio; a large operation, with AWS and Databricks. It isn't a rule: we start from what you already have, your volume and your team.

Cloud

  • AWS
  • Google Cloud
  • Azure

Data and processing

  • BigQuery
  • Databricks
  • Snowflake
  • Redshift
  • PostgreSQL
  • Spark
  • Airflow
  • dbt
  • Python

Dashboards and BI

  • Looker
  • Power BI
  • QuickSight
  • Tableau
  • Metabase

Infrastructure and code

  • Terraform
  • GitHub

You own the platform.

  • Your cloud account

    The provider bills you directly.

  • Your data

    With its history, under your control.

  • Your code

    In your company's repository.

  • Your infrastructure

    Defined as code: understood and rebuildable.

  • Your documentation

    How it works and what every metric means.

No black boxes.

You don't depend on us to understand what we build.

Frequently asked questions

Do we have to change our ERP?

No. We work around the systems you already have.

Do we need AWS or Databricks?

Not necessarily. We use what makes sense for your size; many companies start with BigQuery and Looker Studio.

Do we need to hire a data team?

Not necessarily. The solution is designed to be maintained by the team you have.

We already use Power BI. Is this the same thing?

Power BI can be part of the solution. The dashboard is the last part; first, the information behind it has to be reliable.

Can we use artificial intelligence with our data?

Yes, on a foundation reliable enough for its answers to be useful and controllable.

Start with what isn't working today.

Tell us which decision is going unanswered and we'll define the first step.

Contact ushello@vectorient.com