InfoQ Homepage Database Content on InfoQ
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/articles/ravendb-interview-oren-eini/en/smallimage/ravendb-logo-1598722454099.jpg)
Interview with RavenDB Founder Oren Eini
RavenDB is a NoSQL document database with multi-document ACID transactions and smart document compression. To learn more about the recent RavenDB 5 release and RavenDB in general, we’ve invited Oren Eini, creator of RavenDB and CEO of Hibernating Rhinos, to join us.
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Easy Interpretation of a Logistic Regression Model with Delta-p Statistics
Delta-p statistics is an easier means of communicating results to a non-technical audience than the plain coefficients of a logistic regression model. In this article, authors Maarit Widmann and Alfredo Roccato discuss how to predict credit eligibility using the Delta-p statistics based solution.
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Combining DataOps and DevOps: Scale at Speed
DataOps is an extension of DevOps standards and processes into the data analytics world. It's about streamlining the processes involved in processing, analyzing and deriving value from big data.
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Data Leadership Book Review and Interview
Data Leadership book, authored by Anthony Algmin, covers the data leadership topic and how data leaders should manage and govern the data management programs in their organizations. Data Leadership is how organizations choose to apply their energy and resources toward creating data capabilities to influence their business.
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Innovation Startups Modeling Agile Culture
Innovation is not only about the most advanced technology; management and processes are the new era of startups' innovation. To mix the power of the data and the importance of people to offer business intelligence is a key point nowadays. The result is not only the most important thing; the way you do it is more important. To be agile is to adapt to today's market.
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/articles/applied-probability-unstructured-events-theta-sketches/en/smallimage/applied-probability-unstructured-events-theta-sketches-s-1593199758266.jpg)
Applied Probability - Counting Large Set of Unstructured Events with Theta Sketches
In this article, author Ronen Cohen discusses the solution to processing the event data using Theta Sketches and technologies like HBase and Kafka.
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State at the Edge: an Interview with Peter Bourgon
Building upon topics in his talk at QCon London, Peter Bourgon answers questions about edge computing, distributed data, and the complexity of synchronization.
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Apache Arrow and Java: Lightning Speed Big Data Transfer
Apache Arrow puts forward a cross-language, cross-platform, columnar in-memory data format for data. It is designed to eliminate the need for data serialization and reduce the overhead of copying.
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2020 State of Testing Report
The 2020 State of Testing report provides insights into the adoption of test techniques, practices, and test automation, and the challenges that testers are facing. It shares results from the 2020 testing survey organized by Joel Montvelisky from PractiTest, and Lalit Bhamare from Tea-Time with Testers.
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/articles/data-gateways-cloud-native/en/smallimage/data-gateways-cloud-native-s-1588679812633.jpg)
Data Gateways in the Cloud Native Era
Data Gateways act like API Gateways but focus on access to the data aspect. A Data Gateway offers abstractions, security, scaling, federation, and contract-driven development features. There are many types of Data Gateways, from the traditional data virtualization technologies, to light GraphQL translators, cloud-hosted services, connection pools, and fully open source alternatives.
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/articles/edge-computing-streaming-data/en/smallimage/edge-computing-streaming-data-s-1586865838285.jpg)
Is Edge Computing a Thing?
Edge Computing is definitely a thing, but the computing need not occur at the edge. Instead what is needed is an ability to compute (anywhere) on streaming data from large numbers of dynamically changing devices, in the edge environment. This in turn demands an architectural pattern for stateful, distributed computing.
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/articles/data-driven-privacy-architecture/en/smallimage/Privacy-Architecture-for-Data-Driven-Innovation-logo-1580376548756.jpg)
Privacy Architecture for Data-Driven Innovation
This article lays out how you build an internal data governance architecture early in the ingestion phase, which enables you to allocate risk to data and identify such data in your systems. You can then protect the data accordingly. The second half of this article lays out various techniques to share data in a privacy-conscious manner.