Usługi w zakresie architektury danych

Most companies don’t need more data. They need a better way to organize it. We help businesses build scalable, secure, and high-performing ecosystems for better data flow and actionable insights.

100+

data architecture projects delivered

40+

data analysts & engineers

80%

specjalistów na poziomie senior i mid

Most companies don’t need more data. They need a better way to organize it. We help businesses build scalable, secure, and high-performing ecosystems for better data flow and actionable insights.

100+

data architecture projects delivered

40+

data analysts & engineers

85%

specjalistów na poziomie senior i mid

Usługi
Przypadki
Rozwiązania
Dlaczego my
Proces
Technologie
Zatrudnianie modeli
Recenzje
Funkcje iOS
Projekty
Architecture4

Data architecture setup 
& development

We design sturdy, flexible, modern enterprise data architectures that support your business today and scale cleanly for tomorrow. No spaghetti systems, no rebuilds in year two.

Property 1=Expertise

Platform health checks

We audit your current stack to identify performance issues, integration gaps, and security risks, then deliver a step-by-step plan to fix, upgrade, and secure it.

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Data warehouse strategy

A bloated warehouse is just an expensive sinkhole. We help you pick the right platform, define schema strategy, and build for speed, governance, and growth.

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Data ecosystem implementation

We unify scattered systems into one clean and trusted environment. Fewer data silos, fewer sync issues, and way less manual cleanup.

AI infrastructure establishment and maintenance

We set up the data pipelines, storage layers, 
and compute environments needed to power machine learning models, ensuring your 
AI projects won’t collapse mid-training.

Analytics process management

We turn raw data into real-time decisions. 
From ingestion to visualization, we streamline your analytics pipeline so teams aren’t stuck waiting for yesterday’s numbers.

Struggling with poor data quality?

We’ll implement solutions to standardize and clean your data for trusted insights.

How data architecture services benefit your business

  • Streamlined data workflow
  • Secure & scalable infrastructure
  • Real-time, reliable insights
  • Smarter data visualization
  • Automated data collection
  • Cost-efficient data storage

Streamlined data workflow

Build structured pipelines that move, clean, and organize your data — so teams stop fighting fires and start making fast decisions.

Streamlined Data Workflow

Secure & scalable infrastructure

Protect sensitive data across all environments and scale your setup as the business evolves, without replatforming or growing pains.

Secure Infrastructure

Real-time, reliable insights

Enable always-fresh data streams so dashboards and reports reflect what’s happening now, not what happened yesterday.

Real-Time Insights

Smarter data visualization

Turn complex datasets into visual stories that reveal trends, gaps, and KPIs at a glance — helping leaders act with clarity and speed.

Wizualizacja danych

Automated data collection

Automatically collect and update data by connecting APIs, databases, and services into automated pipelines. No more data delays or missing files.

Automated Data Collection

Cost-efficient data storage

Select the optimal storage architecture — hot, cold, or hybrid — and optimize storage costs while maintaining performance and compliance.

Data Storage
Streamlined data workflow

Build structured pipelines that move, clean, and organize your data — so teams stop fighting fires and start making fast decisions. Streamlined Data Workflow

Secure & scalable infrastructure

Protect sensitive data across all environments and scale your setup as the business evolves, without replatforming or growing pains. Secure Infrastructure

Real-time, reliable insights

Enable always-fresh data streams so dashboards and reports reflect what’s happening now, not what happened yesterday. Real-Time Insights

Smarter data visualization

Turn complex datasets into visual stories that reveal trends, gaps, and KPIs at a glance — helping leaders act with clarity and speed. Wizualizacja danych

Automated data collection

Automatically collect and update data by connecting APIs, databases, and services into automated pipelines. No more data delays or missing files. Automated Data Collection

Cost-efficient data storage

Select the optimal storage architecture — hot, cold, or hybrid — and optimize storage costs while maintaining performance and compliance. Data Storage

Logo Google. Logo Hays. Logo PayPal. Logo Siemens. Logo Nike. Logo Volkswagen. Logo LVMH. Logo Nestle. Logo Novartis. Logo Spotify.
Logo Google. Logo Hays. Logo PayPal. Logo Siemens. Logo Nike. Logo Volkswagen. Logo LVMH. Logo Nestle. Logo Novartis. Logo Spotify.
Logo Aramco Logo Mercedes. Logo Costco Wholesale. Logo powłoki. Logo Accenture. Logo NVIDIA. Logo SPAR. Logo Mastercard. Logo CVS Health. Logo Walt Disney.
Logo Aramco Logo Mercedes. Logo Costco Wholesale. Logo powłoki. Logo Accenture. Logo NVIDIA. Logo SPAR. Logo Mastercard. Logo CVS Health. Logo Walt Disney.
Logo Google. Logo Hays. Logo PayPal. Logo Siemens. Logo Nike. Logo Volkswagen. Logo LVMH.
Logo Google. Logo Hays. Logo PayPal. Logo Siemens. Logo Nike. Logo Volkswagen. Logo LVMH.
Logo Nestle. Logo Novartis. Logo Spotify. Logo Aramco. Logo Mercedes. Logo Costco Wholesale.
Logo Nestle. Logo Novartis. Logo Spotify. Logo Aramco. Logo Mercedes. Logo Costco Wholesale.
Logo powłoki. Logo Accenture. Logo NVIDIA. Logo SPAR. Logo Mastercard. Logo CVS Health. Logo Walt Disney.
Logo powłoki. Logo Accenture. Logo NVIDIA. Logo SPAR. Logo Mastercard. Logo CVS Health. Logo Walt Disney.

Industries we transform

  • Handel detaliczny
  • Nieruchomości
  • Finanse
  • Ubezpieczenia
  • Logistyka

By architecting unified, real-time data ecosystems, we connect sales, inventory, and behavioral insights into one actionable platform. This enables precision forecasting, dynamic pricing, and personalized engagement. Retailers gain the clarity to optimize every shelf, every offer, every transaction.

  • Increased sales from optimized stock levels
  • Higher revenue through personalized offers
  • Lepsze utrzymanie klientów
Handel detaliczny

In real estate, decisions hinge on fast access to fragmented data — leases, listings, tenant info, and financials. We build centralized data platforms that bring all of it together, automating manual work like lease extraction and enabling dynamic dashboards for asset performance and regional trends.

  • Faster deal cycles and approvals
  • Significant reduction in manual data handling
  • Lower operational overhead
Nieruchomości

Financial institutions can’t afford data delays. We architect secure data environments that give teams real-time visibility into risks. From API integration to regulatory reporting automation, we help finance clients reduce overhead, stay compliant, and act fast when the market shifts.

  • Stronger fraud prevention and detection
  • Reduced compliance costs
  • Increased trust in data-driven decisions
Finanse

We help insurers streamline claims and customer management by unifying siloed systems into an efficient data environment. Whether it's accelerating underwriting, predicting fraud, or tailoring coverage with real-time insights, we give insurance teams the tools to make smarter decisions faster.

  • Shorter claim processing times
  • Improved pricing accuracy
  • Reduced exposure to fraudulent claims
Ubezpieczenia

Efficiency in logistics depends on how fast you can react, and that depends on how your data flows. We build architectures that integrate live fleet tracking, WMS, and TMS systems into a cohesive control layer to anticipate disruptions, optimize delivery routes, and align operations in real time.

  • Fewer delivery delays and disruptions
  • Better planning from real-time insights
  • Higher fleet and warehouse productivity
Logistyka
Philip Tihonovich
Kierownik Działu Big Data

In 2025, data architecture is shifting from rigid pipelines to dynamic ecosystems. The real innovation lies in combining data mesh’s decentralized ownership with data fabric’s automation — enabling governed self-service, real-time observability, and AI-powered lineage across the entire data lifecycle. 
For clients, this means faster access to trustworthy data, fewer bottlenecks between teams, and the ability to make data-driven decisions at scale.

Philip Tihonovich
Kierownik Działu Big Data

Advanced data architecture solutions

ETL/ELT Workflows architecture
Modelowanie danych
Data lake architecture
Zarządzanie danymi
Data lakehouse architecture
Projektowanie bazy danych
Data orchestration 
& automation
Data pipelines healthcheck monitoring
Zarządzanie danymi podstawowymi
Migration between 
BI systems

Nasz proces

Initial assessment

We dig into your current setup, uncover 
blind spots, and align your data goals 
with real business impact.

Implementation strategy

We map out the smartest path forward — choosing the right tools, platforms, and architecture for your unique needs.

Structure design

We bring your architecture to life, building clean data models, robust pipelines, and storage 
that scales.

Wdrożenie

Zero chaos, full functionality. Your new data ecosystem goes live without disruption.

Wizualizacja danych i raportowanie

We don’t stop at structure; we connect your data 
to BI tools and dashboards that tell stories, 
not just stats.

Take control of your data

We build the data infrastructure you need to thrive, 
not just survive.

Our data architecture tools

ETL Tools
  • Apache NiFi
  • Talend
  • Informatica PowerCenter
  • IBM InfoSphere DataStage
  • SSIS
  • Apache Kafka
  • Dremio
  • RabbitMQ
  • Amazon Kinesis
  • Google Cloud Pub/Sub
  • Apache Pulsar
  • Denodo
Data Warehouse Tools
  • MySQL
  • PostgreSQL
  • SQL Server
  • Oracle
  • MongoDB
  • Cassandra
  • Couchbase
  • DynamoDB
  • Google Firestore
  • Parquet
  • InfluxDB
  • OpenTSDB
  • TimescaleDB
  • Snowflake
  • Amazon Redshift
  • Clickhouse
  • Vertica
  • Google BigQuery
  • Azure Synapse Analytics
  • Teradata
Platformy Cloud
BI and Data Visualization
  • Domo
  • Sisense
  • ThoughtSpot
  • Google Data Studio

Dlaczego Innowise?

We don’t just design data architecture, we make it work in 
the real world. From predictive analytics in healthcare to live insurance dashboards, our team builds systems that deliver clarity, not complexity. We’ve done it across 120+ projects, helped companies cut operational costs by 20–40%, and delivered insights 30% faster with clean, scalable architecture.

Wybierz odpowiedni dla Ciebie plan cenowy

Cena ustalona z góry

If you have a clear scope, we’ll help you define the technical specs, estimate the timeline, and deliver within a set budget.

Czas i materiały

You see exactly where the time and money go, and you only pay for what’s actually done. The spending cap sets a clear limit, so you stay in control with no runaway costs.

Turn your data chaos into clarity

Whether you’re drowning in spreadsheets or scaling fast — we’ll build the architecture to power smarter decisions.

Opinie naszych klientów

Joanna Wołyńska HR i Manager Projektu Netdevops Luxembourg S.a.r.l
Netdevops' logo

"Innowise pomogło skończyć nam projekt w wyznaczonym terminie. Ich elastyczne podejście zapewniło nam płynną współpracę. Ogólnie rzecz biorąc, byli komunikatywni, responsywni i łatwo się z nimi współpracowało, nie wspominając o ich rozległej wiedzy technicznej."

  • BranżaUsługi IT
  • Wielkość zespołu1 specjalista
  • Czas trwania projektuPonad 6 miesięcy
  • UsługiStworzenie oprogramowania niestandardowego
Johannes Schweifer Dyrektor Generalny CoreLedger AG
CoreLedger AG's logo

"Innowise stworzyło świetną aplikację od zera w niezwykle szybkim tempie. Zajęło im to jedynie 3 tygodnie. Ich staż pracy i rozległa wiedza na temat branży czyni z nich wartościowych partnerów".

  • BranżaUsługi IT
  • Wielkość zespołu6 specjalistów
  • Czas trwania projektuPonad 17 miesięcy
  • UsługiTworzenie aplikacji mobilnej
Tim Benedict Dyrektor ds. technologii Vitreus
Vitreus's logo

“Innowise z powodzeniem dostarczyło klientowi MVP, co jest dowodem na sukces projektu. Zespół wykazał się świetnymi umiejętnościami z zakresu zarządzania projektem. Działają bardzo efektywnie i realizują wszystkie prace w wyznaczonych terminach. Ogólnie rzecz biorąc, wyróżnia ich pasja i rozległa wiedza”.

  • BranżaUsługi biznesowe
  • Wielkość zespołu30 specjalistów
  • Czas trwania projektu15 miesięcy
  • UsługiProjektowanie architektoniczne, blockchain, rozwój niestandardowy

FAQ

What is data architecture in a company?

Data architecture is the structural design that governs how data flows through your organization, from ingestion to storage, transformation, access, and analytics. It defines the standards, tools, and models that ensure data is accurate, secure, and usable across departments. Without a solid architecture, data becomes fragmented and unreliable, leading to poor decision-making and missed opportunities.

The most important part of data architecture is designing a system that can scale efficiently, maintain data integrity, and support business goals through reliable analytics. That includes choosing the right storage models (e.g. data lakes vs. warehouses), ensuring clean data pipelines, and setting up governance for security, lineage, and access control. When done right, it helps everyone in the company make faster, smarter decisions and sets the stage for things like analytics, AI, and compliance.

Data architecture services typically include assessment of your current data environment, design of logical and physical data models, development of ETL/ELT pipelines, setup of data warehouses or lakehouses, implementation of governance and security policies, and integration with BI tools. The goal is to create a scalable, secure, and analytics-ready data ecosystem tailored to your business needs.

Some common examples of data architecture include a centralized data warehouse that consolidates data from multiple departments for unified reporting, an ELT pipeline that processes retail transactions in near real time, or a data lakehouse that merges raw IoT sensor data with curated datasets for advanced analytics. These architectures are designed to support specific business needs like forecasting, personalization, or regulatory compliance.

Data architecture is about organizing and managing data in traditional systems, making it easy to access and store. Big data architecture, on the other hand, is built to handle large amounts of fast-moving data. The main difference is that data architecture is for regular data management, while big data architecture is designed to scale and process massive datasets in real time.

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    Dlaczego Innowise?

    2000+

    specjalistów ds. IT

    93%

    klientów powracających

    18+

    lat doświadczenia

    1300+

    projektów zakończonych sukcesem

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