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Laying the Foundation for Modern Data Architecture

Cloudera

It’s not enough for businesses to implement and maintain a data architecture. The unpredictability of market shifts and the evolving use of new technologies means businesses need more data they can trust than ever to stay agile and make the right decisions.

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Modern Data Architectures Provide a Foundation for Innovation

Precisely

At Precisely’s Trust ’23 conference, Chief Operating Officer Eric Yau hosted an expert panel discussion on modern data architectures. The group kicked off the session by exchanging ideas about what it means to have a modern data architecture.

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Straining Your Data Lake Through A Data Mesh

Data Engineering Podcast

Summary The current trend in data management is to centralize the responsibilities of storing and curating the organization’s information to a data engineering team. This organizational pattern is reinforced by the architectural pattern of data lakes as a solution for managing storage and access.

Data Lake 100
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Transforming Data Architecture through Data Mesh and Striim

Striim

For instance, analytical data may uncover customer preferences or seasonal product trends, helping teams in strategic planning. This data is commonly gathered through an ETL process and stored in a central location, such as a data lake. Want to see how Striim’s Data Mesh and AI can benefit your organization?

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Data Fabric: The Future of Data Architecture

Monte Carlo

Today, as data sources become increasingly varied, data management becomes more complex, and agility and scalability become essential traits for data leaders, data fabric is quickly becoming the future of data architecture. If data fabric is the future, how can you get your organization up-to-speed?

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Data Fabric: The Future of Data Architecture

Monte Carlo

Today, as data sources become increasingly varied, data management becomes more complex, and agility and scalability become essential traits for data leaders, data fabric is quickly becoming the future of data architecture. If data fabric is the future, how can you get your organization up-to-speed?

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Simplify Your Data Architecture With The Presto Distributed SQL Engine

Data Engineering Podcast

For analytical use cases you often want to combine data across multiple sources and storage locations. This frequently requires cumbersome and time-consuming data integration. What are the tradeoffs of using Presto on top of a data lake vs a vertically integrated warehouse solution?