Remove Aggregated Data Remove Kafka Remove MongoDB
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The Good and the Bad of Apache Kafka Streaming Platform

AltexSoft

Kafka can continue the list of brand names that became generic terms for the entire type of technology. Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. What is Kafka? What Kafka is used for.

Kafka 93
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How Rockset Enables SQL-Based Rollups for Streaming Data

Rockset

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. But until this release, all these data sources involved indexing the incoming raw data on a record by record basis.

SQL 52
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Comparing ClickHouse vs Rockset for Event and CDC Streams

Rockset

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Event streams, such as clickstreams, IoT data and other time series data, are common sources of data into these apps. The broad adoption of Apache Kafka has helped make these event streams more accessible.

MySQL 52
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Python for Data Engineering

Ascend.io

Use Case: Transforming monthly sales data to weekly averages import dask.dataframe as dd data = dd.read_csv('large_dataset.csv') mean_values = data.groupby('category').mean().compute() compute() Data Storage Python extends its mastery to data storage, boasting smooth integrations with both SQL and NoSQL databases.

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

In addition, to extract data from the eCommerce website, you need experts familiar with databases like MongoDB that store reviews of customers. You can use big-data processing tools like Apache Spark , Kafka , and more to create such pipelines. However, it is not straightforward to create data pipelines.

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How to Become an Azure Data Engineer? 2023 Roadmap

Knowledge Hut

To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases. You should be able to create intricate queries that use subqueries, join numerous tables, and aggregate data.

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

This architecture shows that simulated sensor data is ingested from MQTT to Kafka. The data in Kafka is analyzed with Spark Streaming API, and the data is stored in a column store called HBase. Finally, the data is published and visualized on a Java-based custom Dashboard. This is called Hot Path.