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Expanding data analysis and visualization options: Amazon DataZone now integrates with Tableau, Power BI, and more

AWS Big Data

Amazon DataZone now launched authentication supports through the Amazon Athena JDBC driver, allowing data users to seamlessly query their subscribed data lake assets via popular business intelligence (BI) and analytics tools like Tableau, Power BI, Excel, SQL Workbench, DBeaver, and more. Lionel Pulickal is Sr.

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Streamline AI-driven analytics with governance: Integrating Tableau with Amazon DataZone

AWS Big Data

With this integration, you can now seamlessly query your governed data lake assets in Amazon DataZone using popular business intelligence (BI) and analytics tools, including partner solutions like Tableau. Joel has led data transformation projects on fraud analytics, claims automation, and Master Data Management.

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How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes

AWS Big Data

This post explores how the shift to a data product mindset is being implemented, the challenges faced, and the early wins that are shaping the future of data management in the Institutional Division. About the Authors Leo Ramsamy is a Platform Architect specializing in data and analytics for ANZ’s Institutional division.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

“Digitizing was our first stake at the table in our data journey,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. That step, primarily undertaken by developers and data architects, established data governance and data integration.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

Comparison of modern data architectures : Architecture Definition Strengths Weaknesses Best used when Data warehouse Centralized, structured and curated data repository. Inflexible schema, poor for unstructured or real-time data. Data lake Raw storage for all types of structured and unstructured data.

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Unlock scalability, cost-efficiency, and faster insights with large-scale data migration to Amazon Redshift

AWS Big Data

However, you might face significant challenges when planning for a large-scale data warehouse migration. Data engineers are crucial for schema conversion and data transformation, and DBAs can handle cluster configuration and workload monitoring. Platform architects define a well-architected platform. Vijay Bagur is a Sr.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021! Discover why.