Google Tag Manager Reviews

Apache Kafka Reviews

Google Tag Manager mentions (3)

• 5 WEBSITES TIPS TO SUPERCHARGE YOUR BUSINESS GROWTH- Creative Wave Tech

  Design a change global positioning framework, for example, Google Tag Manager and Google Analytics objectives and occasions, to log transformations and client ways (you can gain proficiency with about how to do that in our post, The Top 12 Website KPIs for Small Business). Source: over 2 years ago

• 4 Reasons Why Data Engineers Hate Google Tag Manager

  For years, Google Tag Manager (GTM) has made it easy for marketers and analysts to install and manage third-party analytics and marketing tools on their websites and apps. It provides a centralized platform allowing non-technical team members to add, edit, and disable tags without having to touch the source code. This means they don't have to bug you to add new tags or edit existing ones in the event of an update. - Source: dev.to / over 2 years ago

• Graph database question?

  For C360 implementations the there’s a tool called Segment (https://segment.com/) that unifies all the customer identities used across websites/phone apps. Within Segment there is a defined matching logic for identity resolution based on different keys used across apps such as User ID, email, phone number, address, social media account. The end result is each persona will have one Segment ID where all your traits... Source: about 3 years ago

Apache Kafka mentions (120)

• Empowering Real-Time Data Pipelines: Leveraging Apache Kafka and Rudderstack

  In today’s fast-paced digital landscape, effective data management and analysis are essential for businesses aiming to stay ahead of the curve. Fortunately, modern tools like Apache Kafka and RudderStack have revolutionized the way we handle and derive insights from large datasets. In this blog post, we’ll explore our experience implementing the Kafka Sink Connector to facilitate seamless event data transfer to... - Source: dev.to / 2 months ago

• Choosing Between a Streaming Database and a Stream Processing Framework in Python

  Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a... - Source: dev.to / 4 months ago

• How to Use Reductstore as a Data Sink for Kafka

  Apache Kafka is a distributed streaming platform capable of handling high throughput of data, while ReductStore is a databases for unstructured data optimized for storing and querying along time. - Source: dev.to / 4 months ago

• 🦿🛴Smarcity garbage reporting automation w/ ollama

  *Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...). - Source: dev.to / 4 months ago

• How to Build & Deploy Scalable Microservices with NodeJS, TypeScript and Docker || A Comprehesive Guide

  RabbitMQ comes with administrative tools to manage user permissions and broker security and is perfect for low latency message delivery and complex routing. In comparison, Apache Kafka architecture provides secure event streams with Transport Layer Security(TLS) and is best suited for big data use cases requiring the best throughput. - Source: dev.to / 4 months ago