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Three Trends for Modernizing Analytics and Data Warehousing in 2019

Cloudera

Growth factors and business priority are ever changing. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Natural language analytics and streaming data analytics are emerging technologies that will impact the market.

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Building Trust in Public Sector AI Starts with Trusting Your Data

Cloudera

These government-led efforts have had a profound impact on the development and adoption of AI solutions in the public sector, paving the way for a future where data-driven decision-making and automation are the norm. Launched in 2019, this strategy aims to position the US as a leader in AI research, development, and deployment.

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Extend your data mesh with Amazon Athena and federated views

AWS Big Data

Recently, Athena added support for creating and querying views on federated data sources to bring greater flexibility and ease of use to use cases such as interactive analysis and business intelligence reporting. The term data mesh refers to a data architecture with decentralized data ownership.

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Combine transactional, streaming, and third-party data on Amazon Redshift for financial services

AWS Big Data

In this post, we provide a solution architecture that describes how you can process data from three different types of sources—streaming, transactional, and third-party reference data—and aggregate them in Amazon Redshift for business intelligence (BI) reporting.

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How Metadata Makes Data Meaningful

erwin

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

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How Metadata Makes Data Meaningful

erwin

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. 221) to 2019 (No.

IoT 20