2012 Data Architecture Metadata 
AWS Big Data
NOVEMBER 14, 2024
The landscape of big data management has been transformed by the rising popularity of open table formats such as Apache Iceberg, Apache Hudi, and Linux Foundation Delta Lake. These formats, designed to address the limitations of traditional data storage systems, have become essential in modern data architectures.
AWS Big Data
APRIL 3, 2024
They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions.
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AWS Big Data
JUNE 10, 2024
Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated. To address this challenge, organizations can deploy a data mesh using AWS Lake Formation that connects the multiple EMR clusters. An entity can act both as a producer of data assets and as a consumer of data assets.
AWS Big Data
JULY 18, 2024
Data domain producers publish data assets using datasource run to Amazon DataZone in the Central Governance account. This populates the technical metadata in the business data catalog for each data asset. Data ownership remains with the producer. using following command $ nvm install 18.12.0
AWS Big Data
MARCH 7, 2024
At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.
AWS Big Data
SEPTEMBER 6, 2023
He works with enterprise FSI customers and is primarily specialized in machine learning and data architectures. . // It serves as a simple API Gateway to Kafka Proxy, accepting requests and forwarding them to a Kafka topic. In this free time, Philipp spends time with his family and enjoys every geek hobby possible.
AWS Big Data
JANUARY 22, 2024
Cost and resource efficiency – This is an area where Acast observed a reduction in data duplication, and therefore cost reduction (in some accounts, removing the copy of data 100%), by reading data across accounts while enabling scaling. In this approach, teams responsible for generating data are referred to as producers.
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