Data Visualization Training in Oxford

Grafana and Prometheus are industry-standard tools used to monitor, visualize, and alert on IT infrastructure and application metrics through real-time dashboards and integrations.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level IT professionals who wish to integrate Grafana with Prometheus and multiple data sources, and build actionable visualizations and alerts across distributed systems.

By the end of this training, participants will be able to:

• Install and configure Grafana and Prometheus in production-ready setups.
• Integrate multiple data sources including SQL, Elasticsearch, InfluxDB, and cloud APIs.
• Create advanced dashboards with variables, templating, transformations, and alerts.
• Apply best practices in data modeling, performance tuning, and user access control.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

This instructor-led, live training in Oxford (online or onsite) is aimed at intermediate-level Grafana users who wish to build interactive, drill-down dashboards with dynamic thresholds and contextual updates.

By the end of this training, participants will be able to:

• Create dashboards that respond to user interactions, such as clicking a graph bar
• Implement visual drill-downs that update in-place (without new tabs)
• Configure pie charts and detailed panels based on selection filters
• Use dynamic thresholds that react to user input and real-time data

This instructor-led, live training in Oxford (online or onsite) is aimed at intermediate-level system administrators and monitoring professionals who wish to effectively use Grafana for setting up monitoring solutions, managing dashboards, and creating alerts.

By the end of this training, participants will be able to:

• Understand the difference between observability and monitoring.
• Install and set up the Grafana server.
• Configure and connect various data sources such as Prometheus, InfluxDB, and ElasticSearch.
• Create, manage, and customize dashboards and charts.
• Use variables and queries to create dynamic dashboards.
• Set up notifications and alerts through Grafana.
• Install and manage plugins to extend Grafana’s functionality.

This instructor-led, live training in Oxford (online or onsite) is aimed at advanced-level DevOps engineers and SREs who wish to manage and scale Prometheus and Grafana for large environments effectively.

By the end of this training, participants will be able to:

• Architect Prometheus and Grafana for large-scale and distributed environments.
• Optimize Prometheus performance for high-traffic systems.
• Configure Grafana for large datasets and complex visualizations.
• Implement advanced troubleshooting and scalability strategies.

This instructor-led, live training in Oxford (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to instrument their applications to export and monitor custom metrics effectively using Prometheus and Grafana.

By the end of this training, participants will be able to:

• Understand the importance of custom metrics for application monitoring.
• Instrument applications to export custom metrics for Prometheus.
• Create and configure dashboards in Grafana to visualize custom metrics.
• Apply best practices for integrating monitoring into the development lifecycle.

This instructor-led, live training in Oxford (online or onsite) is aimed at advanced-level Kubernetes administrators and DevOps engineers who wish to enhance their monitoring skills for Kubernetes clusters using Prometheus and Grafana.

By the end of this training, participants will be able to:

• Set up Prometheus and Grafana for Kubernetes monitoring.
• Monitor key metrics for pods, nodes, and services.
• Create dynamic dashboards to visualize cluster health and performance.
• Implement alerting strategies for proactive issue resolution.
• Apply best practices for scaling monitoring solutions in Kubernetes environments.

This instructor-led, live training in Oxford (online or onsite) is aimed at advanced-level DevOps and SRE professionals who wish to enhance their alerting and automation skills with Grafana and Prometheus.

By the end of this training, participants will be able to:

• Create and manage advanced alerting rules in Prometheus.
• Integrate Prometheus Alertmanager with external tools using webhooks.
• Automate responses to alerts for faster issue resolution.
• Use Grafana to visualize and manage alerts effectively.

This instructor-led, live training in Oxford (online or onsite) is aimed at intermediate-level cloud and DevOps engineers who wish to enhance cloud observability with Grafana and Prometheus.

By the end of this training, participants will be able to:

• Understand the benefits of integrating Grafana and Prometheus with cloud platforms.
• Set up Prometheus for monitoring cloud-based resources.
• Configure Grafana for visualizing cloud service metrics.
• Leverage cloud-native tools and integrations for monitoring scalability.

This instructor-led, live training in Oxford (online or onsite) is aimed at intermediate-level DevOps and SRE professionals who wish to create impactful dashboards and optimise their monitoring practices using Grafana and Prometheus.

By the end of this training, participants will be able to:

• Understand best practices for designing effective dashboards.
• Create and configure advanced Grafana dashboard elements.
• Leverage Grafana templating for dynamic and reusable dashboards.
• Implement alerting mechanisms to enhance operational awareness.

This instructor-led, live training in Oxford (online or onsite) is aimed at beginner-level system administrators and DevOps engineers who wish to develop core monitoring skills using Grafana and Prometheus.

By the end of this training, participants will be able to:

• Understand the purpose and importance of monitoring in IT environments.
• Install and configure Grafana and Prometheus for basic monitoring tasks.
• Create simple dashboards and alerts to visualize system performance.
• Apply best practices for monitoring system availability and performance.

This instructor-led, live training in Oxford (online or onsite) is aimed at beginner-level data scientists who wish to learn how to create meaningful and visually appealing data visualizations.

By the end of this training, participants will be able to:

• Set up and navigate Google Colab for data visualization.
• Create various types of plots using Matplotlib.
• Utilize Seaborn for advanced visualization techniques.
• Customize plots for better presentation and clarity.
• Interpret and present data effectively using visual tools.

This instructor-led, live training in Oxford (online or onsite) is aimed at beginner-level IT professionals and DevOps practitioners who wish to learn the basics of Grafana and Prometheus.

By the end of this training, participants will be able to:

• Understand the purpose and key features of Grafana and Prometheus.
• Install and configure Grafana and Prometheus on a Linux environment.
• Set up basic data sources and dashboards in Grafana.
• Monitor system metrics and visualize data using Prometheus.

Elastic Stack (ELK) is a powerful platform for searching, analyzing, and visualizing log data in real-time from multiple sources.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT professionals who wish to deepen their ELK expertise for managing distributed log data, automating alerts, and creating advanced visualizations and dashboards.

By the end of this training, participants will be able to:

• Configure advanced ingestion and parsing flows from multiple sources including databases.
• Create customised Kibana dashboards for different teams or use cases.
• Implement email notifications and condition-based alerts.
• Use regular expressions to improve search precision in logs.
• Manage user roles and access rights for secure log environments.
• Interact with the Elasticsearch REST API for automation and integration.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

This instructor-led, live training in Oxford (online or onsite) is aimed at beginner to intermediate-level IT professionals who wish to gain the knowledge and practical skills necessary to excel in the administration of Grafana and GLPI.

By the end of this training, participants will be able to:

• Create and customize Grafana dashboards with different visualizations.
• Implement alerting and notifications for monitoring.
• Administer user accounts, teams, and permissions.
• Manage IT assets effectively, including hardware and software inventory.
• Implement a helpdesk system for user support and ticket management.

This instructor-led, live training in Oxford (online or onsite) is aimed at intermediate-level administrators and developers who wish to deepen their understanding of Elasticsearch administration, including advanced techniques for dashboard development in Kibana, as well as maintenance of the system.

By the end of this training, participants will be able to:

• Set up and configure Elasticsearch and Kibana environments for advanced administration and dashboard development.
• Create and manage Elasticsearch indices, mappings, and data models.
• Develop advanced queries and filters to extract valuable insights from Elasticsearch data.
• Design and build interactive dashboards in Kibana using various visualization types and techniques.
• Implement best practices for Elasticsearch and Kibana administration, optimization, and troubleshooting.

Data Analysis is the process of inspecting, cleaning, transforming, and modeling data to discover useful information, conclusions, and support decision-making.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to manage, analyze, and visualize data effectively for performance and decision support.

By the end of this training, participants will be able to:

• Create and manage databases.
• Apply regression, classification, and basic machine learning models.
• Develop dynamic reports and dashboards using Excel and Power BI.
• Use statistical techniques to inform decisions and analyze trends.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

This instructor-led, live training in Oxford (online or onsite) is aimed at intermediate-level data analysts who wish to learn and utilize the advanced features and components of Grafana for data visualization and analysis.

By the end of this training, participants will be able to:

• Gain an in-depth understanding of advanced Grafana concepts and components.
• Leverage template variables and dynamic dashboards for enhanced data visualization.
• Use Grafana Query Language for complex queries.
• Learn best practices for scaling Grafana, optimizing performance, and ensuring high availability.

Participants who complete this training will gain a practical, real-world understanding of Data Science and its related technologies, methodologies and tools.

Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class.

The course starts with an introduction to elemental concepts of Data Science, then progresses into the tools and methodologies used in Data Science.

Audience

• Developers
• Technical analysts
• IT consultants

Format of the Course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

• To request a customised training for this course, please contact us to arrange.

This instructor-led, live training in Oxford (online or onsite) is aimed at data analysts who wish to build analytic applications using Python with Plotly and Dash.

By the end of this training, participants will be able to:

• Set up a real-time interactive dashboard for streaming live updating data.
• Build interactive dashboards using Python for data science solutions.
• Secure interactive dashboards with advanced authentication methods.

By the end of this training, participants will be able to:

In this instructor-led, live training in Oxford, participants will learn how to create web-based data-driven visualizations that run on multiple devices responsively.

• Use D3 to create interactive graphics, information dashboards, infographics and maps.
• Control HTML with jQuery-like selections.
• Transform the DOM by selecting elements and joining to data.
• Export SVG for use in print publications.

This course is intended for engineers and decision makers working in data mining and knoweldge discovery.

You will learn how to create effective plots and ways to present and represent your data in a way that will appeal to the decision makers and help them to understand hidden information.

In this instructor-led, live training in Oxford, participants will learn the skills, strategies, tools and approaches for visualizing and reporting data for different audiences. Case studies are also analyzed and discussed to exemplify how data visualization solutions are being applied in the real world to derive meaning out of data and answer crucial questions.

By the end of this training, participants will be able to:

• Write reports with captivating titles, subtitles, and annotations using the most suitable highlighting, alignment, and color schemes for readability and user friendliness.
• Design charts that fit the audience's information needs and interests.
• Choose the best chart types for a given dataset (beyond pie charts and bar charts.)
• Identify and analyze the most valuable and relevant data quickly and efficiently.
• Select the best file formats to include in reports (graphs, infographics, references, GIFs, etc.)
• Create effective layouts for displaying time series data, part-to-whole relationships, geographic patterns, and nested data.
• Use effective color-coding to display qualitative and text-based data such as sentiment analysis, timelines, calendars, and diagrams.
• Apply the most suitable tools for the job (Excel, R, Tableau, mapping programs, etc.)
• Prepare datasets for visualization.

This course teaches you about human perception and how to leverage it to deliver the best insights. You will get familiar with design theory, including Gestalt Laws, pre-attentive attributes, and inclusivity. You will also understand the similarities and differences between exploratory and explanatory analysis. You will discover the usage of the charts and learn how to choose the most suitable one. At the end of the course, you will know how to implement the design principles is visualizations created using Tableau software.

This instructor-led, live training in Oxford is aimed at system administrators who wish to set up an ELK stack (Elasticsearch, Logstash, Kibana). Note that a minimum of 3 delegates is needed for this course to run.

The training starts with a discussion of ELK architecture and functionality, then moves on to live lab implementation and practice. Hands-on exercises make up an important part of the training and give participants a chance to put into practice their knowledge while receiving feedback on their progress.

This instructor-led, live training in Oxford (online or onsite) is aimed at beginner-level professionals who wish to gain a mastery of the fundamentals of R and how to work with data.

By the end of this training, participants will be able to:

• Understand the R programming environment and RStudio interface.
• Import, manipulate, and explore datasets using R commands and packages.
• Perform basic statistical analysis and data summarization.
• Generate visualizations using both base R and ggplot2.
• Manage workspaces, scripts, and packages effectively.

This instructor-led, live training in Oxford (onsite or remote) is aimed at data analysts who wish to use Grafana for monitoring and visualizing data.

By the end of this training, participants will be able to:

• Set up the necessary development environment to start creating visualizations in Grafana.
• Set up Grafana for high availability.
• Customize panels and dashboards with data.
• Configure a reverse proxy for fast loading speeds.

This instructor-led, live training in Oxford (online or onsite) is aimed at web developers and DevOps engineers who wish to visualize and monitor data with Grafana and Graphite.

By the end of this training, participants will be able to:

• Aggregate and visualize metrics about systems and applications.
• Create a StatsD client for gathering application metrics.
• Build informative and dynamic dashboards with Grafana.
• Gather insights from back-end performance.

This training introduces Kibana to the users of Elasticsearch.

Kibana is an open source analytics and visualization platform designed to work with Elasticsearch. You use Kibana to search, view, and interact with data stored in Elasticsearch indices. You can easily perform advanced data analysis and visualize your data in a variety of charts, tables, and maps.

Kibana makes it easy to understand large volumes of data. Its simple, browser-based interface enables you to quickly create and share dynamic dashboards that display changes to Elasticsearch queries in real time.

Course is dedicated for those who would like to know an alternative program to the commercial MATLAB package. The three-day training provides comprehensive information on moving around the environment and performing the OCTAVE package for data analysis and engineering calculations. The training recipients are beginners but also those who know the program and would like to systematize their knowledge and improve their skills. Knowledge of other programming languages is not required, but it will greatly facilitate the learners' acquisition of knowledge. The course will show you how to use the program in many practical examples.

Learn how to Get & Transform Data to Prepare Interactive Dashboards

Power BI is one of the most popular Data Visualization tool, and a Business Intelligence Tool. Power BI is a collection of data connectors, apps, and software services, which are used to get data from different source, transforms data, and produce beautiful reports.

Power BI also allows you to publish them for your organization so that you can access them using mobiles, tablets etc. In this Power BI Tutorial, we will show you the step by step approach to connect with multiple data sources, data transformations, and creating reports like charts, tables, matrix, maps, etc

Microsoft Power BI transforms your company data into rich visuals that facilitate new ways of thinking about and organizing your data, so that you can focus on what is important to achieving your goals. This course covers both Power BI on Line and Power BI desktop.

Audience:

This course is intended for Business Managers, Report Developers, Analysts, Project Managers and Team Leads.

At Course Completion

Upon completing this course, students will have a basic understanding of the topics below, as well as an ability to utilize and implement the concepts learned.

• Power BI
• Power BI Desktop
• Working with CSV, TXT, and Excel Worksheets
• Connecting to Databases
• Merging, Grouping, Summarizing, and Calculating Data
• Reporting
• Power BI Online

Microsoft Power BI is a free Software as a Service (SaaS) suite for analyzing data and sharing insights. Power BI dashboards provide a 360-degree view of the most important metrics in one place, updated in real time, and available on all of their devices.

This instructor-led, live training (online or onsite) is aimed at business managers, business analysts, data analysts, report developers, and team leads who wish to design a perfect Power BI dashboard.

By the end of this training, participants will be able to:

• Design beautiful and efficient dashboards following the critical rules.
• Choose the right charts based on the kind of data for display.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

In this instructor-led, live training in Oxford (onsite or remote), participants will learn how to use Microsoft Power BI to analyze and visualize data using a series of sample data sets.

By the end of this training, participants will be able to:

• Create visually compelling dashboards that provide valuable insights into data.
• Obtain and integrate data from multiple data sources.
• Build and share visualizations with team members.
• Adjust data with Power BI Desktop.

This instructor-led, live training in Oxford (online or onsite) is aimed at data analysts and data scientists who wish to use Python to build interactive data visualizations directly from the code.

By the end of this training, participants will be able to:

• Set up the necessary development environment to start creating data visualizations with Python.
• Understand the data visualization core concepts, use cases, and tools.
• Explore the different libraries (Matplotlib, Seaborn, Bokeh, and Folium) available in Python.
• Learn how to create line plots, statistical graphs, geo-spatial, and other complex data visualizations with Python.
• Know the best practices and techniques for presenting and interpreting data.

This instructor-led, live training in Oxford (online or onsite) is aimed at data analysts and web developers who wish to develop associative models in Qlik Sense.

By the end of this training, participants will be able to:

• Apply Qlik Sense in data science.
• Use and navigate the Qlik Sense interface.
• Build a data literate workforce with AI interaction.
• Create a data-driven enterprise with Qlik Sense.

In this instructor-led, live training in Oxford (online or onsite), participants will learn how to start developing with QlikView.

By the end of this training, participants will be able to:

• Install and configure QlikView.
• Transform data from various sources through QlikView scripting.
• Build data models with QlikView.

Tableau is a business intelligence and data visualization tool. Python is a widely used programming language which provides support for a wide variety of statistical and machine learning techniques. Tableau's data visualization power and Python's machine learning capabilities, when combined, help developers rapidly build advanced data analytics applications for various business use cases.

In this instructor-led, live training, participants will learn how to combine Tableau and Python to carry out advanced analytics. Integration of Tableau and Python will be done via the TabPy API.

By the end of this training, participants will be able to:

• Integrate Tableau and Python using TabPy API
• Use the integration of Tableau and Python to analyze complex business scenarios with few lines of Python code

Audience

• Developers
• Data scientists

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

This course is designed for the learner who has never used Tableau before, or who may need a refresher.  It will guide you through the steps necessary to create your first visualization from the beginning. You will also learn how to apply essential design principles to your Tableau visualizations. By the end of the course, you will be able to create and share your insights with the broader audience.

This instructor-led, live training in Oxford (online or onsite) is aimed at intermediate-level data professionals who wish to use Tableau to create advanced visualizations and dashboards for data-driven decision-making.

By the end of this training, participants will be able to: build advanced charts, use calculated fields and parameters, design interactive dashboards, and share insights effectively.

This instructor-led, live training in Oxford (online or onsite) is aimed at developers who wish to use BusinessEvents and ActiveMatrix Service Bus to develop, deploy, and manage event driven applications.

By the end of this training, participants will be able to:

• Set up the necessary development environment to start developing.
• Build distributed, stateful, rule-based event-processing systems.
• Manage business events data and execute proper business rules.
• Reduce the event response time in large-scale, data driven applications.
• Build applications for fraud detection, track-and-trace, real-time customer offer generation, etc.

This instructor-led, live training in Oxford (online or onsite) is aimed at engineers, researchers, and data analysts who wish to use TIBCO Statistica features to create analytic workflows and models.

By the end of this training, participants will be able to:

• Install and navigate the TIBCO Statistica program to build and manage data analysis projects.
• Understand statistics basics to analyze data and generate useful insights for the business.
• Explore advanced topics to work with big data and machine learning using TIBCO Statistica.

Audience

Format of the course

By the end of this training, participants will be able to:

In this instructor-led, live training, participants will learn how to manipulate and visualize data using the tools included in the Tidyverse.

The Tidyverse is a collection of versatile R packages for cleaning, processing, modeling, and visualizing data. Some of the packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

• Beginners to the R language
• Beginners to data analysis and data visualization

• Part lecture, part discussion, exercises and heavy hands-on practice

• Perform data analysis and create appealing visualizations
• Draw useful conclusions from various datasets of sample data
• Filter, sort and summarize data to answer exploratory questions
• Turn processed data into informative line plots, bar plots, histograms
• Import and filter data from diverse data sources, including Excel, CSV, and SPSS files

This is a compelling 4-day course for Tableau beginners. During this course, you will get familiar with all Tableau features and learn how to create and share data visualization with others. The course will guide you through all of the steps, including connecting to data, creating calculations, choosing a chart, building the dashboard, and publishing your work.

The course is divided into lectures dedicated to each topic, followed by practical exercises. The course will end with 30 minutes test and 60 minutes project assignment.

Course milestones:

• Get familiar with Tableau interface.
• Connect to and work with your data.
• Use the Tableau features.
• Build an insightful visualization.
• Share your work with a broader audience.

Format of the Course:

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.
• Knowledge test and hands-on project at the end of the course