Data your business can act on, not just report on

Stackera designs, builds, and operates data platforms, pipelines, analytics products, and decision intelligence—so the numbers in every dashboard, model, and workflow come from one governed source, arrive while they still matter, and can be trusted enough to run the business on.

Explore Platforms

Data Platform & Lakehouse

Pipelines & Streaming

Analytics & Semantic Layer

Embedded & Customer-Facing Analytics

Decision Intelligence & AI-Ready Data

What's happening in Data Analytics

The tooling has commoditised. Warehouses, lakehouses, and BI are a procurement decision now. What separates companies is whether their data is trusted, timely, and wired into the decisions and products that make money.

AI has made data quality the bottleneck

Every AI initiative lands on the same foundation. Teams that skipped governance, lineage, and semantic consistency are discovering that models amplify the mess instead of hiding it.

Lakehouse and open formats won

Open table formats and separated storage and compute have ended vendor lock-in for data at rest. The architecture question is now about the layers above, not the warehouse below.

Real-time is expected

Operations, fraud, pricing, and supply chains no longer accept yesterday's batch. Streaming and change-data-capture pipelines are becoming the default, not the exception.

Analytics is moving into the product

Customers expect embedded dashboards, usage insights, and self-serve reporting inside the software they already pay for—and they judge the product on them.

Semantic layers replace dashboard sprawl

Governed metrics defined once and consumed everywhere—BI, notebooks, APIs, AI agents—are replacing hundreds of dashboards that each compute revenue slightly differently.

Cost is now a data-engineering metric

Consumption-priced platforms make every pipeline and query a cost line. FinOps for data—efficiency, tiering, and observability—is part of the engineering job.

The problems data teams are facing

The gap between having data and running the business on it shows up in trust, latency, fragmentation, cost, and how far the insight actually travels toward a decision.

Three dashboards show three revenue figures. Without lineage, tests, and one metric definition, every leadership meeting starts with an argument about which number is right instead of what to do about it.

Book a Meeting

Let’s talk about your project. View available times and choose your appointment.

Platforms we deliver

Each platform starts from the decisions the business needs to make—then works backward to the metrics, the data model, the pipelines, and the controls required to trust them.

Connect With Us→

Data Platform & Lakehouse

Cloud data foundations on open table formats with separated storage and compute, environment management, cost controls, and observability built in.

Lakehouse architecture
Open table formats
Cost governance

Pipelines & Streaming

Batch, change-data-capture, and streaming pipelines with schema management, tests, and lineage so data arrives on time and breaks loudly when it breaks.

CDC & streaming
Orchestration
Data quality tests

Analytics & Semantic Layer

Governed metric definitions, dimensional models, and BI that give finance, operations, and leadership one version of the truth across every tool.

Metrics layer
Dimensional modelling
Self-serve BI

Embedded & Customer-Facing Analytics

Dashboards, insights, and reporting APIs inside your product—multi-tenant, fast, and secure enough to put in front of paying customers.

Multi-tenant analytics
Reporting APIs
Usage insights

Decision Intelligence & AI-Ready Data

Feature stores, forecasting, anomaly detection, and AI-assisted analysis delivered inside the workflows where decisions are actually made.

Forecasting
Anomaly detection
AI-assisted analysis

We build data platforms, dashboards, and analytics tools

From collecting source data to delivering forecasts and dashboards, we build the pipelines, models, and analytical tools your teams use to make decisions.

Data Warehouses & Lakehouses

Centralized data platforms with structured models, storage layers, and query access for reporting and analysis

Data Integration & Pipelines

Batch and streaming pipelines that connect business applications, databases, and event sources with monitored ingestion and recovery

Business Intelligence & Dashboards

Executive and operational dashboards with shared metric definitions, drill-down views, and scheduled reporting

Data Quality & Observability

Freshness checks, schema validation, reconciliation, and pipeline alerts that help teams detect and resolve unreliable data

Data Governance & Catalogs

Data catalogs, ownership records, lineage, and access policies that help teams find and use the right datasets

Predictive Analytics & Forecasting

Demand forecasts, anomaly detection, and predictive models with evaluation and monitoring tied to business outcomes

Embedded Analytics & Data APIs

Customer-facing dashboards, reporting endpoints, and analytical features integrated into your applications

Self-Service Analytics & Semantic Models

Reusable business metrics, curated datasets, and exploration tools that let teams answer questions using consistent definitions

The right engagement for your next data platform

Start with a defined build, extend your team, or take over an existing platform. We agree the scope, success measures, and ownership before delivery begins.

Fixed-Scope Build

A focused data platform, dashboard, or analytics product delivered against an agreed specification, integration plan, and acceptance criteria.

Best for: Teams launching a defined data platform with a clear business outcome.

4–8 weeks

Dedicated Team

An embedded team that brings product, data, and security engineering into your roadmap, with attention to data sources, metric definitions, and quality controls.

Best for: Organizations expanding their platform with an ongoing product and engineering roadmap.

Team embedded in 3 days

AI-Inclusive Build

Add forecasting, anomaly detection, or analytical assistance to your product with trusted data, evaluation criteria, and human review built in.

Best for: Teams adding intelligent assistance to workflows their customers and operators already use.

Scoped

Existing Platform Takeover

Take ownership of an existing platform, review pipeline reliability, metric consistency, and source dependencies, and prioritize the improvements needed for dependable production use.

Best for: Teams inheriting a codebase or moving beyond their original delivery partner.

Platform takeover in 3 days

How Delivery Runs

1 week
Discovery & Architecture
Define data sources, metric definitions, and quality expectations, then agree the architecture, delivery scope, and measures of success.
4–6 weeks
Build & Launch
Deliver working increments with pipeline checks, metric reconciliation, and user validation. Prepare the team and production environment before release.
Ongoing
Operate & Improve
Monitor data freshness, platform cost, and changing source systems. Maintain tests and improve the platform as requirements evolve.

Not sure which model fits?

Start with a discovery sprint to assess your data sources, business metrics, and reporting needs, then define a practical path to production.

Book a Discovery Sprint→

Why Stackera Is
The Right Partner

+10 Years Of Experience

We start from the decisions the business needs to make and work backward to the metrics, the model, and the pipelines—so nothing gets built that doesn't change an outcome.

Production stories of data made decision-ready—fragmented sources unified into one trusted picture, delivered inside the workflows where operators, traders, and finance teams actually act.