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Machine learning model serving architectures

Xebia

After months of crunching data, plotting distributions, and testing out various machine learning algorithms you have finally proven to your stakeholders that your model can deliver business value. Selecting the right architectural serving pattern is paramount in creating the most business value from your model.

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Data Mesh Principles and Logical Architecture

Martin Fowler

Last year, my colleague Zhamak Dehghani introduced the notion of the Data Mesh , shifting from the notion of a centralized data lake to a distributed vision of data.

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Streamdal wants to bring greater visibility to streaming data architectures

TechCrunch

The rise of streaming architectures — frameworks of software components built to ingest and process large volumes of data from multiple sources — is driving the demand for better reliability and performance. Engineering teams often encode data to improve app performance by using what are known as “message envelopes.”

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Big Data Realtime Data Pipeline Architecture

Dzone - DevOps

Big data has become increasingly important in today's data-driven world. It refers to the massive amount of structured and unstructured data that is too large to be handled by traditional database systems. To efficiently process and analyze this vast amount of data, organizations need a robust and scalable architecture.

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Top 5 Challenges in Designing a Data Warehouse for Multi-Tenant Analytics

Multi-tenant architecture allows software vendors to realize tremendous efficiencies by maintaining a single application stack instead of separate database instances while meeting data privacy needs. When you use a data warehouse to power your multi-tenant analytics, the proper approach is vital.

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What is enterprise architecture? A framework for transformation

CIO

Enterprise architecture definition Enterprise architecture (EA) is the practice of analyzing, designing, planning, and implementing enterprise analysis to successfully execute on business strategies. Making it easier to evaluate existing architecture against long-term goals.

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Making OT-IT integration a reality with new data architectures and generative AI

CIO

Manufacturers have long held a data-driven vision for the future of their industry. It’s one where near real-time data flows seamlessly between IT and operational technology (OT) systems. Legacy data management is holding back manufacturing transformation Until now, however, this vision has remained out of reach.

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Use Cases for Apache Cassandra®

From understanding its distributed architecture to unlocking its incredible power for industries like healthcare, finance, retail and more, experience how Cassandra® can transform your entire data operations.

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7 Pitfalls for Apache Cassandra in Production

Apache Cassandra is an open-source distributed database that boasts an architecture that delivers high scalability, near 100% availability, and powerful read-and-write performance required for many data-heavy use cases.

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The Next-Generation Cloud Data Lake: An Open, No-Copy Data Architecture

In an effort to be data-driven, many organizations are looking to democratize data. However, they often struggle with increasingly larger data volumes, reverting back to bottlenecking data access to manage large numbers of data engineering requests and rising data warehousing costs.

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Partner Webinar: A Framework for Building Data Mesh Architecture

Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri

Data teams in large enterprise organizations are facing greater demand for data to satisfy a wide range of analytic use cases. Yet they are continually challenged with providing access to all of their data across business units, regions, and cloud environments.

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Build Your Open Data Lakehouse on Apache Iceberg

Speaker: Veena Vasudevan and Jason Hughes

With data stored in vendor-agnostic files and table formats like Apache Iceberg, the open lakehouse is the best architecture to enable data democratization. By moving analytic workloads to the data lakehouse you can save money, make more of your data accessible to consumers faster, and provide users a better experience.

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Top Considerations for Building an Open Cloud Data Lake

Data fuels the modern enterprise — today more than ever, businesses compete on their ability to turn big data into essential business insights. Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data.

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The Unexpected Cost of Data Copies

An organization’s data is copied for many reasons, namely ingesting datasets into data warehouses, creating performance-optimized copies, and building BI extracts for analysis. Read this whitepaper to learn: Why organizations frequently end up with unnecessary data copies.

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Your Team's Pragmatic Guide to Security

Speaker: Naresh Soni, CTO, Tsunami XR

The pandemic has led to new data vulnerabilities, and therefore new cyber security threats. Whether you need to rework your security architecture, improve performance, and/or deal with new threats, this webinar has you covered. What methods and architectures you should consider to proactively protect your data.