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Geospatial Data Analysis in Angular

Immersive experience has tapped into data analysis with a dazzling array of visualization techniques. The evolution of visualization-based data analysis influences business and sets apart from the competition since it can help provide the desired user experience. Users prefer data storytelling and demand data visualization beyond reports and dashboards. IT teams add visualization features to enable and standardize data visualization as it is a powerful mode for displaying the metrics.

You may also like: What Data Analysis Tools Should I Learn to Start a Career as a Data Analyst?

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Nginx Log Analytics With AWS Athena and Cube.js

Sometimes, existing commercial or out-of-the-box open-source tools like Grafana don’t fit requirements for Nginx log analytics. Whether it is pricing, privacy, or customization issues, it is always good to know how to build such a system internally.

In the following tutorial, I’ll show you how to build your own Nginx log analytics with Fluentd, Kinesis Data Firehose, Glue, Athena, and Cube.js. This stack also makes it easy to add data from other sources, such as Snowplow events, into the same S3 bucket and merge results in Athena. I’ll walk you through the whole pipeline from data collection to the visualization.

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How to Get Started Using CrateDB and Grafana to Visualize Time-Series Data

Grafana, the open platform for time-series data visualization and monitoring that is quite useful for time-series analytics, makes a pretty compelling team when paired with CrateDB, the open-source distributed SQL database that simplifies the real-time storage and analysis of massive quantities of machine data.

Getting started using Grafana and CrateDB together is a relatively simple process, which this article will walk you through (these instructions pertain to macOS, but can be adapted for other platforms quite easily).