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Apache Kafka and the Denodo Platform: Distributed Events Streaming Meets Logical Data Integration

Data Virtualization

Kafka is used when real-time data streaming and event-driven architectures with scalable data processing are essential.

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What Stands Between IT and Business Success? Data Complexity

CIO Business Intelligence

IT teams grapple with an ever-increasing volume, velocity, and variety of data, which pours in from sources like apps and IoT devices. At the same time, business teams can’t access, understand, trust, and work with the data that matters most to them. Often, enterprise data ecosystems are built with a mindset that’s too narrow.

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Snowflake: Data Ingestion Using Snowpipe and AWS Glue

BizAcuity

In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes.

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Go Fast and Far Using Data Virtualization

Data Virtualization

Reading Time: 3 minutes We are always focused on making things “Go Fast” but how do we make sure we future proof our data architecture and ensure that we can “Go Far”? Technologies change constantly within organizations and having a flexible architecture is key.

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Go Fast and Far Using Data Virtualization to help you Go Fast and Go Far

Data Virtualization

Reading Time: 3 minutes We are always focused on making things “Go Fast” but how do we make sure we future proof our data architecture and ensure that we can “Go Far”? Technologies change constantly within organizations and having a flexible architecture is key.

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Snowflake: Data Ingestion Using Snowpipe and AWS Glue

BizAcuity

Introduction In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. Using minutes- and seconds-old data for real-time personalization can significantly grow user engagement.

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Big Data Ingestion: Parameters, Challenges, and Best Practices

datapine

Big data: Architecture and Patterns. The Big data problem can be comprehended properly using a layered architecture. Big data architecture consists of different layers and each layer performs a specific function. The architecture of Big data has 6 layers. Challenges of Data Ingestion.

Big Data 100