Sun.Mar 10, 2024

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Streaming Real-Time Data From Kafka 3.7.0 to Flink 1.18.1 for Processing

Dzone - DevOps

Over the past few years, Apache Kafka has emerged as the leading standard for streaming data. Fast-forward to the present day: Kafka has achieved ubiquity, being adopted by at least 80% of the Fortune 100. This widespread adoption is attributed to Kafka's architecture, which goes far beyond basic messaging. Kafka's architecture versatility makes it exceptionally suitable for streaming data at a vast "internet" scale, ensuring fault tolerance and data consistency crucial for supporting mission-cr

Data 72
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Scaling Intelligent Experience Orchestration With GenAI

IDC

Parity in the value exchange with customers means that the customer and the organization, equally, get something meaningful out of the exchange. Customer value parity is crucial since an imbalance can lead to loss of customer trust, and often, ends in customer attrition.

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How to Assign Records to Salesforce Queue: A Complete Guide

Perficient

Hello Trailblazers! With the need for effective customer data and records management increasing, Salesforce developed a solution called Salesforce Queue. Queues offer a dynamic solution, allowing users to efficiently organize, assign, and prioritize tasks and records. If you are not aware of what a Salesforce Queue is, how to create one, and its advantages, check out this previous blog.

How To 59
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Rome Wasn't Built in a Day: A Step-By-Step Guide to DevOps Transformation

Dzone - DevOps

The adage “Rome wasn’t built in a day” applies perfectly to DevOps. Many companies yearn for the instant gratification of “blitzing” their way to market dominance, but true success in DevOps is a marathon, not a sprint. It requires a commitment to building a sustainable DevOps culture - one that fosters collaboration, automation , and security from the ground up.

DevOps 40
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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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Understanding the role of Py4J in Databricks

Perficient

I mentioned that my attempt to implement TDD with Databricks was not totally successful. Setting up the local environment was not a problem and getting a service id for CI/CD component was more of an administrative than a technical problem. Using mocks to test python objects that are serialized to Spark is actually the issue. This is a feature, not a bug.