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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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Power analytics as a service capabilities using Amazon Redshift

AWS Big Data

For example, you can build visualizations on top of Amazon Redshift and embed them within applications to provide outstanding analytics experiences for end-users. Data processing jobs enrich the data in Amazon Redshift. About the Authors Sandipan Bhaumik is a Senior Analytics Specialist Solutions Architect based in London, UK.

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Best BI Tools For 2024 You Need to Know

FineReport

In 2024, business intelligence (BI) software has undergone significant advancements, revolutionizing data management and decision-making processes. Harnessing the power of advanced APIs, automation, and AI, these tools simplify data compilation, organization, and visualization, empowering users to extract actionable insights effortlessly.

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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

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.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Strategize based on how your teams explore data, run analyses, wrangle data for downstream requirements, and visualize data at different levels. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

Overview of solution As a data-driven company, smava relies on the AWS Cloud to power their analytics use cases. smava ingests data from various external and internal data sources into a landing stage on the data lake based on Amazon Simple Storage Service (Amazon S3).

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Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

With Amazon Redshift, you can build lake house architectures and perform any kind of analytics, such as interactive analytics , operational analytics , big data processing , visual data preparation , predictive analytics, machine learning , and more. Select Redshift data agent , then choose OK.