Data Engineering and Analytics
Data-driven decisions can only be made with a clear and singular view of the data itself - this need can be met with data engineering and analytics
OUR MAIN CHALLENGES
Data Driven Architecture
Design and implementation of the Data Driven Architecture based on cloud services
Streaming and batch data pipelines for populating Analytics Data Platforms
Modern Data Warehouse
Design and development of business data marts for Advanced Analytics support
Ensure security for the data in motion and for data at rest
Data Quality and Governance
Implementation of Data Quality and Data Governance
Creating of the powerful reports and dashboards for the business support
Preparing data and building machine learning models for text analysis
Engineers in the Division
Engagements of different size and complexity
Supported cloud data related services and technologies
OUR TECH CAPABILITIES
If you need to forecast faster and more accurately, gain insights into your customers’ behaviour, shorten process cycle times, improve data integrity and quality or extract data from multiple sources across the business – you’ve come to the right place.
Godel provides its market-leading clients with experienced data engineering and analytics experts, that deliver accessible and scalable data solutions to make your company’s data work for you.
Some companies are dealing with petabytes of datasets, so the first priority in gaining control of this data is to implement data engineering practices.
Godel's data division has decades of collective experience in helping clients become data-driven, and so their technical and business acumen in building data solutions for clients is top notch.
Visit our technology pages to get a detailed understanding of our technical skills.
If there is something specific you are looking for that we haven’t mentioned, please do contact us and ask. Given the pace of change in our industry, it’s an impossible task to keep this pages up to date!
Head Of Data Division
"During our work, we always try to understand the business needs, because data describes the business. Knowing the data specifics, we can help to improve the business of our customers."