Case StudiesBlogAbout Us
Get proposal

Data Analytics Services

We build custom analytics dashboards, scoring engines, and decision-support tools that turn complex data into decisions your teams actually make. From concept to production.

Book a 30-min call

Trusted by:

Siemens
PwC
Toyota
Geberit
Rainbow
Chooose

Data analytics platforms we built

Building Embedded AI Into the Cybersecurity Platform

Building Embedded AI Into the Cybersecurity Platform

95% reduction in onboarding time, daily product use, three personas in one interface. We built Claude-powered embedded AI inside a Fortune 500 cybersecurity platform, without rewriting the core analytics engine.

Explore more case studies

From data audit to production in 5 steps

01

Data & Decision Audit

We map your data sources and, more importantly, the decisions they should support. Output: what to build first and why.

02

Design for the Decision-Maker

Dashboards and scoring interfaces prototyped with the actual users: executives, planners, non-technical teams. Tested before a line of production code.

03

Build & Integrate

Depending on what the audit shows, we build a standalone analytics platform from scratch or add a decision-support layer to your existing product. Either way, we integrate with your current systems (ERP, CRM, data warehouses, product databases).

04

Validate on Your Numbers

Accuracy checked against historical data and real user queries before go-live.

05

Production & Iteration

Deployment with monitoring, then iteration based on how your teams actually use it.

01

Data & Decision Audit

We map your data sources and, more importantly, the decisions they should support. Output: what to build first and why.

02

Design for the Decision-Maker

Dashboards and scoring interfaces prototyped with the actual users: executives, planners, non-technical teams. Tested before a line of production code.

03

Build & Integrate

Depending on what the audit shows, we build a standalone analytics platform from scratch or add a decision-support layer to your existing product. Either way, we integrate with your current systems (ERP, CRM, data warehouses, product databases).

04

Validate on Your Numbers

Accuracy checked against historical data and real user queries before go-live.

05

Production & Iteration

Deployment with monitoring, then iteration based on how your teams actually use it.

Why enterprises choose us for data analytics

We're a 50-person, cross-functional software development team based in Warsaw, Poland, building technology that delivers ROI, strong governance, and real adoption.

10 years

delivering digital products

est. 2016

100+

products shipped

web & mobile

50+

experts on board

Product & UX designers, Software engineers, AI specialists, PMs

75

client NPS

Praised for communication, pace and quality

5

continents served

North America, South America, Europe, Asia, Africa

Frequently Asked Questions

What are data analytics services?

Data analytics services cover the design, development, and deployment of tools that turn raw business data into decisions: dashboards, scoring engines, reporting automation, and decision-support platforms. At SH, this means custom-built products integrated with your existing systems, not off-the-shelf BI licenses.

What's the difference between data analytics and data science?

Data analytics focuses on making existing data usable for decisions: dashboards, visualization, scoring, and reporting. Data science focuses on building predictive capabilities from that data. If you need your teams to see, understand, and act on data, you need analytics. If you need systems that predict and learn, see our Data Science services.

Can you build analytics dashboards for non-technical users?

Yes, that's most of what we do. For Reffine, we built marketing analytics that non-technical teams use daily without analyst support: campaign metrics translated into business language, with automated alerts replacing manual monitoring. The design process starts with the actual decision-makers, not the data schema.

Do you build analytics for regulated industries like fintech or cybersecurity?

Yes. We've delivered an automated credit decisioning platform for Siemens Financial Services (compliant with Polish financial regulations) and a NIST/CIS compliant cyber risk scoring platform for a US cybersecurity company. Compliance requirements shape the architecture from day one, including audit trails and dedicated infrastructure for sensitive data.

Which systems do you integrate with?

ERP systems, CRMs, data warehouses, product databases, and cloud platforms (GCP, AWS, Azure). We build the analytics layer on top of your existing stack; nothing needs replacing.

How long does a data analytics project take?

A focused dashboard or reporting tool typically ships in 6-12 weeks. Full decision platforms with scoring engines and multiple integrations take longer. After the data and decision audit, you get a concrete scope and timeline.

How much do data analytics services cost?

It depends on scope: number of data sources, complexity of the scoring or calculation layer, and user roles served. After a 30-minute call and a short audit, we propose team composition and a fixed estimate. No open-ended billing.

Ready to turn your data into decisions?

Let's talk about your data sources, your decision-makers, and what's blocking them today. We'll propose an approach within a week.

Book a 30-min call

We build what comes next.

Company

Startup Development House sp. z o.o.

Aleje Jerozolimskie 81

Warsaw, 02-001

VAT-ID: PL5213739631

KRS: 0000624654

REGON: 364787848

Contact Us

hello@startup-house.com

Our office: +48 789 011 336

New business: +48 798 874 852

Follow Us

Award
logologologologo

Copyright © 2026 Startup Development House sp. z o.o.

EU ProjectsPrivacy policy