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

Data Virtualization

Reading Time: 3 minutes More and more companies are managing messages and events in real time using tools like Apache Kafka. Kafka is used when real-time data streaming and event-driven architectures with scalable data processing are essential.

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5 modern challenges in data integration and how CIOs can overcome them

CIO Business Intelligence

The growing volume of data is a concern, as 20% of enterprises surveyed by IDG are drawing from 1000 or more sources to feed their analytics systems. Data integration needs an overhaul, which can only be achieved by considering the following gaps. Heterogeneous sources produce data sets of different formats and structures.

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3 Huge Reasons that Data Integrity is Absolutely Essential

Smart Data Collective

However, your data integrity practices are just as vital. But what exactly is data integrity? How can data integrity be damaged? And why does data integrity matter? What is data integrity? Indeed, without data integrity, decision-making can be as good as guesswork.

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Data Integrity, the Basis for Reliable Insights

Sisense

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is. What is data integrity?

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IBM named a leader in the 2022 Gartner® Magic Quadrant™ for Data Integration Tools

IBM Big Data Hub

The only question is, how do you ensure effective ways of breaking down data silos and bringing data together for self-service access? It starts by modernizing your data integration capabilities – ensuring disparate data sources and cloud environments can come together to deliver data in real time and fuel AI initiatives.

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The New Data Integration Requirements

In(tegrate) the Clouds

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. They are: Application integration is done primarily through REST & SOAP services. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses.

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The Need For Personalized Data Journeys for Your Data Consumers

DataKitchen

’ It assigns unique identifiers to each data item—referred to as ‘payloads’—related to each event. By offering real-time tracking mechanisms and sending targeted alerts to specific consumers, a Payload DJ can immediately notify them of any changes, delays, or issues affecting their data.

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