Monitoring with Grafana Training Course

This instructor-led, live training in Moldova (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.

This instructor-led, live training in Moldova (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 Moldova (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.

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

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

• 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.

About This Course

This course will discuss the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will also show how to access and process data from a range of data sources including both relational and non-relational data. This course will also explore how to implement proper security standards and policies across the Power BI spectrum including datasets and groups. The course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution.

Audience Profile

The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises.

Skills gained

• Ingest, clean, and transform data
• Model data for performance and scalability
• Design and create reports for data analysis
• Apply and perform advanced report analytics
• Manage and share report assets

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 customized training for this course, please contact us to arrange.

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 Moldova, 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.

Apache Druid is an open-source, column-oriented, distributed data store written in Java. It was designed to quickly ingest massive quantities of event data and execute low-latency OLAP queries on that data. Druid is commonly used in business intelligence applications to analyze high volumes of real-time and historical data. It is also well suited for powering fast, interactive, analytic dashboards for end-users. Druid is used by companies such as Alibaba, Airbnb, Cisco, eBay, Netflix, Paypal, and Yahoo.

In this instructor-led, live course we explore some of the limitations of data warehouse solutions and discuss how Druid can compliment those technologies to form a flexible and scalable streaming analytics stack. We walk through many examples, offering participants the chance to implement and test Druid-based solutions in a lab environment.

Format of the Course

• Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding

eCharts is a free JavaScript library used for interactive charting and data visualization.

In this instructor-led, live training, participants will learn the fundamental functionalities of ECharts as they step through the process of creating and configuring charts using ECharts.

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

• Understand the fundamentals of ECharts
• Explore and utilize the various features and configuration options in ECharts
• Build their own simple, interactive, and responsive charts with ECharts

Audience

• Developers

Format of the course

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

Embedding Projector is an open-source web application for visualizing the data used to train machine learning systems. Created by Google, it is part of TensorFlow.

This instructor-led, live training introduces the concepts behind Embedding Projector and walks participants through the setup of a demo project.

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

• Explore how data is being interpreted by machine learning models
• Navigate through 3D and 2D views of data to understand how a machine learning algorithm interprets it
• Understand the concepts behind Embeddings and their role in representing mathematical vectors for images, words and numerals.
• Explore the properties of a specific embedding to understand the behavior of a model
• Apply Embedding Project to real-world use cases such building a song recommendation system for music lovers

Audience

• Developers
• Data scientists

Format of the course

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

The objective of the course is to enable participants to gain a mastery of the fundamentals of R and how to work with data.

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