article thumbnail

Designing A Non-Relational Database Engine

Data Engineering Podcast

The default association with the term "database" is relational engines, but non-relational engines are also used quite widely. In this episode Oren Eini, CEO and creator of RavenDB, explores the nuances of relational vs. non-relational engines, and the strategies for designing a non-relational database.

article thumbnail

Data Engineering Glossary

Silectis

Data Engineering Data engineering is a process by which data engineers make data useful. Data engineers design, build, and maintain data pipelines that transform data from a raw state to a useful one, ready for analysis or data science modeling.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Azure Data Engineer Skills – Strategies for Optimization

Edureka

Here are some role-specific skills to consider if you want to become an Azure data engineer: Programming languages are used in the majority of data storage and processing systems. Data engineers must be well-versed in programming languages such as Python, Java, and Scala. To store various types of data, various methods are used.

article thumbnail

How to Become an Azure Data Engineer in 2023?

ProjectPro

Here are some role-specific skills you should consider to become an Azure data engineer- Most data storage and processing systems use programming languages. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Learning SQL is essential to comprehend the database and its structures.

article thumbnail

Data Collection for Machine Learning: Steps, Methods, and Best Practices

AltexSoft

Both data integration and ingestion require building data pipelines — series of automated operations to move data from one system to another. For this task, you need a dedicated specialist — a data engineer or ETL developer. They are more scalable than SQL ones and capable of handling larger data volumes.

article thumbnail

Data Virtualization: Process, Components, Benefits, and Available Tools

AltexSoft

If the transformation step comes after loading (for example, when data is consolidated in a data lake or a data lakehouse ), the process is known as ELT. You can learn more about how such data pipelines are built in our video about data engineering. Popular data virtualization tools.

Process 69
article thumbnail

IBM InfoSphere vs Oracle Data Integrator vs Xplenty and Others: Data Integration Tools Compared

AltexSoft

They are applied to retrieve data from the source systems, perform transformations when necessary, and load it into a target system ( data mart , data warehouse, or data lake). So, why is data integration such a big deal? Connections to both data warehouses and data lakes are possible in any case.