Remove Data Lake Remove Data Security Remove Metadata Remove NoSQL
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Data Lakehouse: Concept, Key Features, and Architecture Layers

AltexSoft

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

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Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. A loose schema allows for some data structure flexibility while maintaining a general organization. Data security and privacy.

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97 things every data engineer should know

Grouparoo

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. It is made up of 97 small vignettes that are 2-3 pages each. The articles are in alphabetical order.

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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. Enhanced data security and governance.

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DataOps Architecture: 5 Key Components and How to Get Started

Databand.ai

In a DataOps architecture, it’s crucial to have an efficient and scalable data ingestion process that can handle data from diverse sources and formats. This requires implementing robust data integration tools and practices, such as data validation, data cleansing, and metadata management.

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Data Architect: Role Description, Skills, Certifications and When to Hire

AltexSoft

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

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Data Engineering Glossary

Silectis

Data Architecture Data architecture is a composition of models, rules, and standards for all data systems and interactions between them. Data Catalog An organized inventory of data assets relying on metadata to help with data management.