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How to Create Near Real-time Models With Just dbt + SQL

dbt Developer Hub

When your data is small enough, this is the preferred approach, however it isn’t scalable. Because dbt is primarily designed for batch-based data processing, you should not schedule your dbt jobs to run continuously. Lambda views are a simple and readily available solution that is tool agnostic and SQL based.

SQL 52
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Apache Spark Use Cases & Applications

Knowledge Hut

As per Apache, “ Apache Spark is a unified analytics engine for large-scale data processing ” Spark is a cluster computing framework, somewhat similar to MapReduce but has a lot more capabilities, features, speed and provides APIs for developers in many languages like Scala, Python, Java and R.

Scala 52
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Handling Bursty Traffic in Real-Time Analytics Applications

Rockset

However, these databases tend to sacrifice support for complex SQL queries at any scale. Instead, these database makers have offloaded complex analytics onto application code and their developers, who have neither the skills nor the time to constantly update queries as data sets evolve.

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Data Engineering Weekly #124

Data Engineering Weekly

[link] NYT: Day in the Life of a Senior Analyst in the Data and Insights Group NYT publishes an article on data in the life of a senior analyst. The blog highlights that the job is not just writing SQL but providing a strategic business solution for an organization.

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Aggregator Leaf Tailer: An Alternative to Lambda Architecture for Real-Time Analytics

Rockset

In this blog post, I will describe the Aggregator Leaf Tailer architecture and its advantages for low-latency data processing and analytics. To mitigate the delays inherent in MapReduce, the Lambda architecture was conceived to supplement batch results from a MapReduce system with a real-time stream of updates.

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Exploring Processing Patterns For Streaming Data Integration In Your Data Lake

Data Engineering Podcast

Atlan is a collaborative workspace for data-driven teams, like Github for engineering or Figma for design teams. What are the prevailing architectural and technological patterns that are being used to manage these systems? The Lambda architecture has largely been abandoned, so what is the answer for today’s data lakes?

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Data Pipeline Architecture: Understanding What Works Best for You

Ascend.io

Now, you might ask, “How is this different from data stack architecture, or data architecture?” ” Data Stack Architecture : Your data stack architecture defines the technology and tools used to handle data, like databases, data processing platforms, analytic tools, and programming languages.