Remove Data Analytics Remove Data Architecture Remove Machine Learning Remove Metadata
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What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. Third-generation – more or less like the previous generation but with streaming data, cloud, machine learning and other (fill-in-the-blank) fancy tools.

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Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore federation

AWS Big Data

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.

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The Future Is Hybrid Data, Embrace It

Cloudera

Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform. We deliver cloud-native data analytics across the full data lifecycle – data distribution, data engineering, data warehousing, transactional data, streaming data, data science, and machine learning – that’s portable across infrastructures.

IT 112
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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The program must introduce and support standardization of enterprise data. Programs must support proactive and reactive change management activities for reference data values and the structure/use of master data and metadata.

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2023 Predictions: Data Trends That Will Dominate Business Agenda in APAC

Cloudera

Faced with even more pressure to remain resilient and agile amid looming global economic threats, Asia-Pacific (APAC) region businesses are looking to further mobilize emerging technologies such as artificial intelligence (AI) and machine learning that will optimize operational efficiencies and cost savings. .

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The Future Is Hybrid Data, Embrace It

CIO Business Intelligence

Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform. We deliver cloud-native data analytics across the full data lifecycle – data distribution, data engineering, data warehousing, transactional data, streaming data, data science, and machine learning – that’s portable across infrastructures.

IT 73
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AI at Scale isn’t Magic, it’s Data – Hybrid Data

Cloudera

Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. Different data types need different types of analytics – real-time, streaming, operational, data warehouses. Doing data at scale requires a data platform. .