Data Engineering
Data exactly where it is needed.
Create the foundation to unlock the potential of data across business units and applications within your organization.
Challenge
Most data that companies collect is unstructured and stored in numerous different source systems that cannot communicate with each other. The big picture of the collected data is missing and cross-functional communication is sluggish and cumbersome. Generating value from your data in that situation is impossible.
Collect the right
Data in the right place.
Data engineering deals with collecting data from various sources, storing it and making it available for further use. It is the basis for unleashing the potential of data within
your company across departments and applications.
No more manually updating Excel files and waiting for information to become available. Take control of your data and automate the repetitive work.
Together, we develop a customized digital solution that automatically pulls all the relevant data from the various sources, processes it uniformly and brings it to where it is
needed. Without human intervention.
Our Data Engineering
Tools und Technologies.
Source systems
Databases.
Whether MS SQL, Oracle DB or something else, we extract data from almost all databases.
API.
Specific API for data exchange in use? No problem, we will find a way.
Files.
Data in Excel, CSV or similar? We are happy to extract your data directly from documents.
ELT Pipelines
Azure Data Factory & Azure Synapse.
Modular assembly of pipelines without code.
Azure Data Bricks.
Processing Big Data in an Apache Spark environment.
Data Lake
Azure Data Lake Storage.
Highly scalable, cost-effective storage platform for virtually unlimited data volumes.
Data Warehouse
Azure SQL Database.
Classic provisioning of data in a relational data model.
Azure Synapse.
Suitable for large data volumes and high performance through parallelization.
Data Engineering in
5 phases.
We love talking about data and potential use cases with Business Value. In an open, no-obligation conversation, we'd love to learn more about your current situation and needs. Together, we'll find out if data can add value to your business.
Together, we define a target image of your desired solution. Together we sharpen the requirements, identify the affected surrounding systems and determine the necessary prerequisites. Based on this, we put together the optimal package to achieve the goal.
We get a detailed picture of your data in the business context as a basis for the technical implementation of the solution. Through discussions with experts from your company, we deepen our understanding of your data and the connection to your everyday business.
On the basis of data understanding we realize data pipelines, reports or prediction models. In regularly held project meetings, we bring you up to date and iteratively sharpen the path to the goal.
With feedback from your business experts, we validate your solution in terms of functionality and defined requirements. The modelling and validation phases are repeated until the solution meets your needs.
We integrate the solution into your productive environment and show your employees how it can be used optimally. With the deployment we complete the solution, hand it over to you and ensure that all users have the necessary tools to use the solution in a valuable way.
FAQ – Frequently asked questions about Data Engineering.
Data is information in a form that is readable by computers. Every interaction with your business is a potential source of data: Website clicks, customer feedback, even NOT clicking on one of your ads. Many applications such as ERP or CRM systems store data in a structured way in databases, which can be used as a data source. But there are also many unstructured data sources like office documents, images or social media comments.
Data engineering deals with collecting data from various sources, storing it and making it available for further use. It is the basis for unleashing the potential of data within your company across departments and applications.
You need a Data Engineer if your company already works with data in various sub-areas, but this data is not available in sufficient quality for use outside the source system or cannot be used across areas due to data silos.
Data Engineers deal with the collection and processing of data. Data scientists use this data to generate forecasts, find hidden relationships in data or process unstructured data streams such as images, text and sound.
Data engineers collect the right data and prepare it in such a way that it can be used across departments. In Business Intelligence, data is analyzed and patterns found in it are presented to the company's decision makers in an understandable way.
Questions about
Data Engineering?
If you have any questions about Data Engineering, our Lead Data Engineering, Dominic Schranz, will be pleased to help you.
Dominic Schranz
LEAD DATA ENGINEERING
BSc Business Information Systems (BFH)
MSc Applied Information and Data
Science (HSLU)