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The Future Is Hybrid Data, Embrace It

Cloudera

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 112
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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

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Data Engineering Glossary

Silectis

Big Data Large volumes of structured or unstructured data. Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse.

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Moving Past ETL and ELT: Understanding the EtLT Approach

Ascend.io

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Central to this transformation are two shifts.

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Announcing New Innovations for Data Warehouse, Data Lake, and Data Lakehouse in the Data Cloud 

Snowflake

And, since historically tools and commercial platforms were often designed to align with one specific architecture pattern, organizations struggled to adapt to changing business needs – which of course has implications on data architecture. The schema of semi-structured data tends to evolve over time.

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5 Reasons Data Discovery Platforms Are Best For Data Lakes

Monte Carlo

Data Catalogs Can Drown in a Data Lake Although exceptionally flexible and scalable, data lakes lack the organization necessary to facilitate proper metadata management and data governance. Data discovery tools and platforms can help. Interested in learning how to scale data discovery across your data lake?

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Data Pipeline Architecture Explained: 6 Diagrams and Best Practices

Monte Carlo

Amazon S3 – An object storage service for structured and unstructured data, S3 gives you the compute resources to build a data lake from scratch. Data catalog Some organizations choose to implement data catalog solutions for data governance and compliance use cases. Now Go Build Some Data Pipelines!