InfoQ Homepage Data Analytics Content on InfoQ
-
Apache Kafka: Ten Best Practices to Optimize Your Deployment
Author Ben Bromhead discusses the latest Kafka best practices for developers to manage the data streaming platform more effectively. Best practices include log configuration, proper hardware usage, Zookeeper configuration, replication factor, and partition count.
-
Natural Language Processing with Java - Second Edition: Book Review and Interview
Natural Language Processing with Java - Second Edition book covers the Natural Language Processing (NLP) topic and various tools developers can use in their applications. Technologies discussed in the book include Apache OpenNLP and Stanford NLP. InfoQ spoke with co-author Richard Reese about the book and how NLP can be used in enterprise applications.
-
Democratizing Stream Processing with Apache Kafka® and KSQL - Part 2
In this article, author Robin Moffatt shows how to use Apache Kafka and KSQL to build data integration and processing applications with the help of an e-commerce sample application. Three use cases discussed: customer operations, operational dashboard, and ad-hoc analytics.
-
How to Choose a Stream Processor for Your App
Stream Processors are software platforms that enable users to respond to incoming data streams faster compared to traditional batch data processing. In this article, the authors discuss the stream processor reference architecture, key features required by most streaming applications and optional features that can be selected based on specific use cases.
-
Democratizing Stream Processing with Apache Kafka and KSQL - Part 1
In this article, author Michael Noll discusses the stream processing with KSQL, the streaming SQL engine for Apache Kafka. Topics covered include challenges of stateful stream processing and how KSQL addresses them, and how KSQL helps to bridge the world of streams and databases through streams and tables.
-
Pascal Desmarets on NoSQL Data Modeling Best Practices
NoSQL databases are specialized to store different types of data like Key Value, Documents, Column Family, Time Series, Graph, and IoT data. Pascal Desmarets talks about how to perform data modeling in NoSQL databases compared to the modeling in Relational databases.
-
Traffic Data Monitoring Using IoT, Kafka and Spark Streaming
Internet of Things (IoT) is an emerging disruptive technology and becoming an increasing topic of interest. One of the areas of IoT application is the connected vehicles. In this article we'll use Apache Spark and Kafka technologies to analyse and process IoT connected vehicle's data and send the processed data to real time traffic monitoring dashboard.
-
Spark GraphX in Action Book Review and Interview
“Spark GraphX in Action” book from Manning Publications, authored by Michael Malak and Robin East, provides a tutorial based coverage of Spark GraphX, the graph data processing library from Apache Spark framework. InfoQ spoke with authors about the book and Spark GraphX library as well as overall Spark framework and what's coming up in the area of graph data processing and analytics.
-
Lana Gibson on Using Analytics to Influence Content Design
Lana Gibson gave a talk at the AgileNZ conference on using analytics data to design website content, based on her experiences as Content Performance Lead working on the GOV.UK whole of government website.
-
Getting Ready for IoT’s Big Data Challenges with Couchbase Mobile
Our physical world is about to become digitally enabled and according to various predictions for example by Gartner or Cisco, there will be many billions of IoT devices going online and constantly gathering data in the coming years. We got in touch with Wayne Carter and Ali LeClerc of Couchbase to discuss how Couchbase Mobile is also ready for the upcoming era of Internet of Things.
-
Big Data Processing with Apache Spark - Part 3: Spark Streaming
In this article, third installment of Apache Spark series, author Srini Penchikala discusses Apache Spark Streaming framework for processing real-time streaming data using a log analytics sample application.
-
7 Habits of Highly Effective Monitoring Infrastructures
There is a right way and a wrong way to engineer effective telemetry systems and there is a finite combination of practices which — whatever your choice of individual tools — are predictive of success. If you are building or designing your next monitoring system, take a look at this short list of habits exhibited by the most successful monitoring systems in the world today.