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Accelerate Amazon Redshift Data Lake queries with AWS Glue Data Catalog Column Statistics

AWS Big Data

Over the last year, Amazon Redshift added several performance optimizations for data lake queries across multiple areas of query engine such as rewrite, planning, scan execution and consuming AWS Glue Data Catalog column statistics.

Data Lake 105
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DataKitchen’s 2020 Honors & Awards

DataKitchen

In June of 2020, CRN featured DataKitchen’s DataOps Platform for its ability to manage the data pipeline end-to-end combining concepts from Agile development, DevOps, and statistical process control: DataKitchen. DBTA Big Data Quarterly’s Big Data 50—Companies Driving Innovation in 2020.

Testing 241
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What is a data architect? Skills, salaries, and how to become a data framework master

CIO Business Intelligence

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.

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Simplify data integration with AWS Glue and zero-ETL to Amazon SageMaker Lakehouse

AWS Big Data

While traditional extract, transform, and load (ETL) processes have long been a staple of data integration due to its flexibility, for common use cases such as replication and ingestion, they often prove time-consuming, complex, and less adaptable to the fast-changing demands of modern data architectures.

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The Top Three Entangled Trends in Data Architectures: Data Mesh, Data Fabric, and Hybrid Architectures

Cloudera

Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. Data teams are confused as to whether they should get on the bandwagon of just one of these trends or pick a combination. First, we describe how data mesh and data fabric could be related.

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The Race For Data Quality in a Medallion Architecture

DataKitchen

This architecture is valuable for organizations dealing with large volumes of diverse data sources, where maintaining accuracy and accessibility at every stage is a priority. It sounds great, but how do you prove the data is correct at each layer? How do you ensure data quality in every layer ?

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Data Architecture Movements in 2020

TDAN

Data is commonly referred to as the new oil, a resource so immensely powerful that its true potential is yet to be discovered. We haven’t achieved enough with data research and other statistical modeling techniques to be able to see data for what it truly is and even our methods of accruing data are rudimentary […].