Introduction to Tableau Desktop

This 1-day course is designed to help you understand and use the main concepts and techniques in Tableau, to move from simple to complex visualizations and to combine them in interactive dashboards. It will be taught on the latest Tableau Desktop version, or the version in use at your organisation.

Target Audience Anyone who works with data, regardless of background. Tableau users: beginner to intermediate level.

Content Connect to your data in a variety of formats and sources. Edit and save data sources; handle changes such as field addition, deletion or name changes. Create basic calculations including string manipulation, custom aggregations and ratios, logic statements and quick table calculations. Represent your data with a variety of visualization types (cross tabs, maps, dual axis / combo charts, heat maps, box plots, distribution charts, tree maps, scatter plots, etc.). Use reference lines to highlight elements of your data. Use groups, bins, hierarchies, sets, and filters to create focused and effective visualizations with multiple measures and dimensions. Finally, combine your visualizations into interactive dashboards, share with others and publish online.

Practical info (e.g., cost) | Download flyer (pdf) en de | Download free trial of Tableau Desktop | Dates of our scheduled courses

Advanced Tableau Desktop

This 2-day course is designed to provide the skills required to become a Tableau power user. It is meant for the professional who has solid working experience with Tableau and wants to take it to the next level. The course will be taught on the latest Tableau Desktop version.

Target Audience Users with a good understanding of all the fundamental concepts of building worksheets and dashboards.

Content Build advanced chart types and visualizations such as Bar in bar charts, Pareto Charts and Bullet Graphs. Build complex calculations to manipulate data. Prep data for analysis and use statistical techniques to analyse it. Use parameters and input controls. Implement advanced geographic mapping techniques and use custom images and geocoding to build spatial visualizations of non-geographic data. Combine data sources and data from multiple tables in the same data source. Make your visualizations perform as well as possible with the Data Engine, extracts, and efficient connection methods. Build better dashboards for guided analytics, interactive dashboard design, and visual best practices. Learn efficiency tips and tricks. Use Tableau Server in a basic way to share your visualizations.

Practical info (e.g., cost) | Download flyer (pdf) en | Download free trial of Tableau Desktop | Dates of our scheduled courses

Tableau Server Administration

This 1-day course provides in-depth coverage of Tableau Server administration, including managing content, users, and permissions. The course includes hands-on activities to reinforce the skills and knowledge attained.

Target Audience The expertise and skills acquired are best geared towards those who will be administering the Tableau Server installation. There are no Tableau-specific knowledge prerequisites.

Content User interactions with Tableau Server / Tableau Server components. Single-server installation / Content administration. Authorization and permissions / Users, groups, and sites. Data sources and extracts / Schedules, tasks, and subscriptions. Monitoring server status / Command-line utilities and REST API. Upgrading a single-server installation to a new version. Modifying the authentication method.

Practical info (e.g., cost) | Download flyer (pdf) en | Download free trial of Tableau Server | Check out some of our Tableau vizzes

Tableau Server Architecture

This 1-day course provides in-depth coverage of Tableau Server architecture and configuration. You will need it if your responsibilities include the architecture and administration of a large deployment of Tableau Server, typically in an enterprise environment.

Target Audience The expertise and skills acquired are best geared towards those architecting and administering a large deployment of Tableau Server. There are no knowledge prerequisites.

Content In-depth analysis of Tableau Server architecture. Installing and configuring Tableau Server in an enterprise environment. Command-line utilities. Monitoring server status. Licensing models. Migrating a system to new hardware. Scalability and distributed installations. High availability. Analysis of authentication methods. Embedding and APIs.

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Visual Analytics & Data Storytelling with Tableau

This 2-day course is designed to equip participants with the necessary conceptual and technical skillset to create compelling visualizations. Attendees will learn about effective data visualization techniques and how to apply these concepts in practice with Tableau. A variety of simple and complex visualizations will be created, discussed, and subsequently combined in interactive dashboards.

Target Audience Anyone who works with data, regardless of technical or analytical background. Tableau users: beginner to intermediate level.

Content Learn how to connect to, edit, and save data in a variety of formats and sources, create calculations, discover the effective uses for various chart types, review existing visualizations and discuss alternatives, why statistical summaries and visualizations are complements and not substitutes, explore data journalism to tell a story with your data and more.

Practical info (e.g., cost) | Download flyer (pdf) en | Download free trial of Tableau Desktop

Automate Your Work with KNIME

Target Audience Anyone who works with MS Excel to produce reports and any other kind of repetitive task, including formulas, pivot tables, I/O from and to a variety of data sources. No technical knowledge prerequisites.

Content Introduction to KNIME. What is KNIME? Who uses it? What can we do with it? How does it compare to Excel? Installation and technical details. Demo. Hands-On KNIME Workflows. Reading and writing data from and to Text Files, Excel and Databases. Sorting, Columns Renaming. Filtering: Numerical, String and NULL filtering. Basic operations / Pivot tables / Text manipulation / File manipulation. Date/Time: Conversion, Field Extraction. Data quality: messy input data; implement basic and advanced verifications. Reproduce Excel’s V and HLookup. Implement joins across data sources. Workflow synchronisation / Automate send emails. Two case studies. Working with KNIME as a team. Node naming convention / KNIME Team Space / KNIME Server / Metanodes.

Practical info (e.g., cost) | Download flyer (pdf) en | Dates of our scheduled courses

Data Science Bootcamp

This 5-day intensive course focuses on the many aspects of modern Data Science, such as visual analytics, machine learning, data modeling, and data management. The course can be tailored depending on your interests and experience. For example, an
extensive introduction NoSQL databases if you are new to this concept, paired with advanced sessions in Machine Learning if you’re already familiar with this topic.

Target Audience Anyone who has a scientific or technical background, an ability to work with software, and a keen interest and ambition to master data science and apply it to real-life challenges.

Content Quantum proposes a 5-day course program with the following indicative content:
Modeling and Mapping, Visualization, Reporting & Storytelling, Quantitative Analysis and Data Management.The work mode is a mix of lectures, hands-on exercises directly related to the lectures, and use cases.

Practical info (e.g., cost) | Download flyer (pdf) en

Social Media Listening

This 2-day hands-on course is designed to provide you with the knowledge necessary to extract key insights from social media conversations and apply them in your company, going beyond simple monitoring of hashtags and explicit mentions of brands or products.
With 500 million tweets each day, 2.2 billion users on Facebook, 95 million new photos on Instagram, and 3.5 billion Snaps per day, social media has become a dominant channel for marketing and customer care. Users leverage this channel to get their voices heard by companies. They post customer service enquiries, actively give feedback, and recommend products to their followers. This results in a lot of unstructured data that companies can mine for customer and product insights. Many companies are merely scratching at the surface of this rich source of information. It’s more than just replying to questions or comments about your company (social media monitoring). Through social media listening, the more advanced companies capture and understand the big picture behind all these conversations, and then apply their learnings strategically and tactically. Without social media listening, your company misses out on actionable insights from real people who are actively talking about you and your industry online.

Target Audience Anyone who has an interest to keep the finger on the pulse of social media conversations about their company, brand and products. There are no specific technical knowledge prerequisites.

Content Collect data from social media: REST APIs and their usage. Prepare your data with Python, a powerful, easy-to-learn, widely used programming language. Understand your data through visual exploration. Identify types of customers: preferences, habits, purchasing behavior, interaction with social media & communities. Categorise and extract meaning from words: text mining and sentiment analysis. Pictures not words: image and brand/logo recognition on social media and e-commerce sites. How to apply social media listening in a company: tips and tricks.

Practical info (e.g., cost) | Download flyer (pdf) en

Data Science in Practice

This 1-day course is intended to give you the knowledge to capitalize on your company’s data to optimize processes, save time and money, and maintain quality standards. Sharpen your awareness about the value of data in your enterprise. With a focus on your company’s digital footprint and the variety of available data sources, you will learn where opportunities lie to start the digital transformation process and expand it step by step.

Target Audience Managers and executives with operational and strategic tasks who want to actively tackle the issue of digitization in their companies.

Content Extracting core processes and elements. Key questions and necessary data. Understand the company’s digital footprint (internal and external). How much makes sense? ROI of the data. Systematic modeling of an activity landscape: small steps to big destinations. Data visualization. Data throughout the product life cycle. Development of analytics teams and skills within the company. You will be able to better determine: 1) how digitalization affects your organization, 2) how data-driven processes affect your business areas and influence them, 3) how to make informed decisions, and 4) how historical data can help guide your company’s future.

Practical info (e.g., cost) | Download flyer (pdf) de en

Tools for Data Scientists

This 2-day hands-on course is designed to provide data scientists and analysts with a comprehensive overview and the knowledge of a complete set of tools necessary for today’s modern work with data and Big Data.

Target Audience Anyone who works with data for analysis purposes, predictive and descriptive. There are no specific technical knowledge prerequisites.

Content Work with data in relational databases. R: data manipulation, statistical analysis, predictive modeling, calculation and graphical display. Elements and techniques for linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering with R. Python: programming language for integrating your data work into a production environment, such as web apps or a corporate database. Visual data exploration: learn how modern in-memory visualisation helps you get the most out of their data.

Practical info (e.g., cost) | Download flyer (pdf) en

Data Warehouse Concepts & Design

This 1-day hands-on course is designed to provide attendees with a complete overview of the concepts and design methodologies of a Data Warehouse. Each section includes an abundance of real-life examples and practical exercises. For data analysts, data scientists and IT specialists.

Target Audience Anyone who works with data in a Data Warehouse or with data from different data sources, and wishes to understand advantages and costs of having a Data Warehouse. There are no specific technical knowledge prerequisites.

Content Data Warehouse history and background. Reference Architecture. Data Warehouse key users: Data Provider / Data Consumer. On-Line Analytical Processing (OLAP) concepts. Data Warehouse analytical tasks. Business Intelligence maturity. Landing and Staging Area. The Datawarehouse Core Concept of data historisation. Data Marts. Extract, Transform, Load: concept and tools. Data Quality and Data Governance. Metadata and its role in a Data Warehouse; Data Warehouse administration.

Practical info (e.g., cost) | Download flyer (pdf) en

Introduction to SQL

This 2-day hands-on course is designed to provide attendees with the knowledge necessary to work with data in relational databases. Each section includes an abundance of real-life examples and practical exercises.

Target Audience Anyone who works with data in relational databases. There are no specific technical knowledge prerequisites.

Content History and background. Types of SQL statements. SQL SELECT; Oracle vs. ANSI syntax. Clauses (WHERE, HAVING, …). How to deal with NULL values. Aggregate functions. How to assess the results of your queries. Joining database tables. Subqueries. Working with temporal data; record historisation. Useful functions; Set operations. Database objects.

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Hands-on Data Modeling

This 1-day hands-on course is designed to help you understand and use the main concepts and techniques of managing a company’s data for purposes of reporting and analysis. Each section includes an abundance of practical exercises.

Target Audience Anyone who works with data in databases or with data extracts for analysis purposes. There are no specific technical knowledge prerequisites.

Content Link between business and data: how structure and processes of your business reflect on data modeling. Levels, types and contexts of data modeling. Overview of data modeling notation and concepts. Meaning and usage of logical and physical data modeling. Data normalisation: pros and cons, techniques. Dimensional modeling: what it is and when to use it. Modeling for analytics: what to look for and how to optimise it. Data historisation: concepts and best practices. Good database design. Reference data.

Practical info (e.g., cost) | Download flyer (pdf) en