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Oracle Database and ELK Stack – Data Visualization
Rating: 4.4 out of 5(59 ratings)
297 students

Oracle Database and ELK Stack – Data Visualization

Visualize Oracle Database using Elasticsearch, Kibana and Logstash. Hands-On Training
Created byCloud Ops
Last updated 1/2022
English
English [Auto],

What you'll learn

  • Configuring ELK Stack from the beginning
  • AWS RDS for Oracle
  • GCP Compute Engine Service
  • Logstash Configuration File
  • Oracle DB connectivity using Logstash
  • Data Visualization using Kibana
  • Oracle HR schema data Visualization

Course content

1 section • 11 lectures • 1h 13m total length

  • Course Introduction and what we going to build2:38

    Create an Oracle database from scratch, push relational data to Elasticsearch, and visualize with Kibana and Logstash. Build dashboards for employees, departments, and jobs, and embed them on Bootstrap page.

  • Introduction to ELK Stack4:24

    Explore how the elk stack, Elasticsearch, Logstash, and Kibana, ingests, analyzes, and visualizes logs for application and infrastructure monitoring with open source tools and rich visualizations.

  • Create AWS Oracle RDS, Connect using SQL developer, and Create HR schema tables5:18

    Create an AWS Oracle RDS instance, connect with SQL Developer, and deploy HR schema tables (departments, employees, jobs, locations) with a ready script and verify data.

  • Let’s create our ELK server on the GCP compute engine6:09

    Launch an elk stack server on the gcp compute engine by provisioning a linux instance, configuring a public key for ssh, and setting firewall rules.

  • Elasticsearch, Kibana, and Logstash Installation and Configuration11:17

    Learn how to install and configure the Elasticsearch, Kibana, and Logstash stack on Linux, including setting up repositories, enabling services, and accessing Elasticsearch and Kibana via public IP.

  • Let’s write our SQL queries for Visualization9:09

    Write Oracle SQL queries for visualization, including highest salary by department and employee country joins, and build a three-part configuration with input, filter, and output to Elasticsearch.

  • Let’s create our Logstash Configuration file and ingest data into Elasticsearch10:01

    Create a Logstash configuration file with input and output sections to ingest Oracle database data into Elasticsearch, using dynamic indexing and JSON output; explore visualization in Kibana for dashboards.

  • Create Index Pattern and Visualize data using Kibana – Part 16:02

    Kibana visualizations by selecting an index pattern, applying aggregations, and building a pie chart and heat map to analyze country distribution and salaries.

  • Create Index Pattern and Visualize data using Kibana – Part 28:37

    Create Kibana visualizations for department and salary data, including line charts of average salary, data tables, and metrics, then assemble a dashboard and explore Kibana lens.

  • It’s time to create our Dashboard in Kibana3:34

    Create a Kibana dashboard by assembling lens visualizations, guided by auto suggestions, and refine with a timestamp field and refresh for a static webpage uploaded to the industry bucket.

  • Learn about S3 static content hosting and embed the Kibana dashboard on a Webpag6:30

    Learn to host static content on an S3 bucket and embed a Kibana dashboard on a web page, enabling public access, Bootstrap styling, and live data visualization.

Requirements

  • Basic Knowledge of SQL.

Description

To take advantage of the powerful search capabilities offered by Elasticsearch, many businesses will deploy Elasticsearch alongside existing relational databases. It will likely be necessary to keep Elasticsearch synchronized with the stored data in the associated relational database in such a scenario. (Source: Official Elastic Documentation)

This course will see how we can visualize RDBMS data using elk stack, and we will use Kibana to create beautiful visualizations and dashboards. We are going to do everything from scratch.

After completing this course, you’ll get an idea that ELK is not only used for logging purposes but can be used for visualizing RDBMS data. Additionally, I will use AWS RDS, GCP Compute Engine, AWS S3 in the course. I’m sure you’ll have fun learning these sessions.

"ELK" is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.

The Elastic Stack is the next evolution of the ELK Stack. Oracle database products offer customers cost-optimized and high-performance versions of Oracle Database, the world's leading converged, multi-model database management system, as well as in-memory, NoSQL and MySQL databases.

Who this course is for:

  • Software Developers
  • Data analyst
  • Managers

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