Data Engineering

Data engineering contains all topics related for storage, management and disclosure of data. So all prerequisitional methods and tools to work with data are managed here. The main goal is to efficiently store and disclose data to various users and applications in a secure manner.

Data Sources

The data sources for a project need to be identified and combined into one source of truth.

Mining, reporting and analysis

Combine all data to leverage the power of big data for analysis and mining purposes.

Different data types

Data types do not really matter anymore. Everything can be stitched together with automated flows (ETL jobs) to combine all data into a single format and location.

Safe and fast

Performance and security are of course of main performance for data engineering. This is ensured with working with the latest technologies and clear architecture and processes.

1. Integrate

Integrate all data sources into one source of truth

  • Identify sources and structure
  • Map to wanted scheme
  • Choose storage system
  • Create ETLs to perform transformation on regular basis

2. Connect

Connect the data

  • Identify users and applications
  • Determine and build interfaces
  • Authentication and authorization

3. Analyse

Get insights from data

Use data for analysis and models:

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