Give your stakeholders the facts they need. Set up an AWS system that catches data from your databases, API, Excels, or SaaS tools in real-time. We’ve already helped European banks or e-commerce platforms, delivering 160+ projects to date.
DATA ENGINEERING SERVICES
Dig up strategic insights even from millions of data points
One team — all data engineering solutions
Making data-based decisions pays off
Imagine predicting when sales spike or what content makes users act. What would you like to know?
One client with several pet marketplaces bumped their revenue by 400% in two years — in part by using big data.
Our engineering team can show you how to catch and turn data into game-changing insights. You’ll be able to analyze many sources by using the cloud — at an optimized cost.
We use — but aren’t limited to — AWS Glue, AWS EMR, AWS QuickSight, Step Functions, and Kinensis. GDPR and data security compliance is our golden standard.
Collect, filter, and sort information from your backend, any database, file, or SaaS.
Know what customers will do and find ways to boost your revenue
Speed up or automate data analysis
Update your data study methods and re-use the time employees save
Scale up operations
Set more accurate goals, increase customer loyalty, and find ways to build up the product
Track and measure
Prepare your data to be used as business intelligence on a dashboard for your teams
From on-prem to the cloud or between cloud providers — while the service remains live and well
Want to analyze and visualize data at a speed? Move it? Or integrate a new data source with your pipeline? You need an engineering team that has done all of that — sometimes for products servicing 1M users per month.
ETL / ELT
Data lake / warehouse
ETL / ELT
Map, clean, and transform data
Before data works for you, you need to pull it from multiple sources and make it usable. Both ETL (extract-trasform-load) and ELT (extract-load-transform) processes turn data from SQLs, files, PDFs, and CRMs into information that can be assigned clear value.
Depending on what information is needed and who reads it, your engineers need to set up either ETL or ELT before data lands in one bucket. Used by TUI, Slack, or Cisco.
- Store any type of information
- Increase data readability
- Adjust data format
- Rise or lower data processing resources on demand
Transfer data without errors or downtime
Move web services with their content untouched from server to server or between cloud providers. Or prepare an automated and flexible migration system you can reuse. Yes, we’ll keep the product live.
By centralizing your data, swapping technologies or doing deep analysis becomes efficient. Done by Spotify, Waze, Dropbox, or GitLab.
- Expand your cloud capabilities
- Create a manageable ecosystem of services
- Enable deeper data analytics
- Make compliance achievable
Data lake / warehouse
Prepare your data for deep analytics
For fast and unrestricted access to all data, you need to build a lake. If only critical and error-free data matters, better build a warehouse. Rest easy — our engineers can recommend a way forward.
A data lake lets your analysts dig into raw facts with little overhead. Then, your board would appreciate accurate and structured intel from a warehouse. Both solutions are used by Coca-Cola, ING Bank, or Lenovo.
- Store relational and non-relational data
- Increase business insight accuracy
- Enable machine learning, predictive analysis, etc.
- Set up one source of true data (data warehouse)
Know what's happening with a data point in milliseconds
Set up active monitoring for intel that comes from end-users, Marketing, or Sales. Or expand your product’s abilities by processing public data or signals from smart devices.
If you need to catch what’s happening with data now, expand your stack with stream processing technology. Used by Pinterest, Netflix, or Yahoo.
- Get real-time overview of data or metrics
- Speed up decision-making
- Get notified or warned about events
- Provide new functions for your product
Know how to deliver qualified & readable data
Working with data makes sense only if you use it to power up business decisions. As early as possible, let’s show your team value in collecting data and extracting insights.
Then, we’ll consider what solution suits your processes — also by looking at how companies across the industries we’ve worked with handled their engineering.
Rest assured, you won’t get stuck with a custom solution. Your data pipeline will scale by design by using AWS services, and it will comply with changing information processing regulations.
Let your team learn from an official AWS Partner
Connect them with cloud engineers who built dozens of AWS systems. They can show you how Amazon’s services can increase your product’s processing power.
A UK loan platform for SMEs
- To build an ELT pipeline for several data sources including databases, spreadsheets, and documents
- To architect an AWS-based data lake ready for machine learning in the future
Manual data mining turned into smooth automation
The new cloud pipeline loads a database of several gigabytes onto Amazon S3 in just 3-10 minutes
The product team can now extract data from AWS RDS, Excel and CSV files
The client’s Data Scientists received ready data-models they can write queries for
“Each person we dealt with was extremely smart and skilled.”
Said by an engineer of a US energy company in a ★5 review. Give your data a job with us.