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Quantum’s training courses

Tableau Training

Kickstart Tableau

Tableau Desktop Tableau Training Tableau SchulungThis 1-day Tableau course is designed to help 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 technical or analytical 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. Use the Tableau interface effectively to create powerful visualizations. Create basic calculations including string manipulation, basic arithmetic calculations, 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, sorts, sets, and filters to create focused and effective visualizations. Use Measure Name and Measure Value fields to create visualizations with multiple measures and dimensions. Share your visualizations with others. Combine your visualizations into interactive dashboards, share with others and publish them to the web.

Download flyer (pdf) en de   |    Download free trial of Tableau Desktop    |    Check out some of our Tableau vizzes


Get the Most Out of Tableau

Tableau Ausbildung Tableau EducationThis 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.

Download flyer (pdf) en   |    Download free trial of Tableau Desktop    |    Check out some of our Tableau vizzes


Secrets of Tableau Server Administration

Tableau Server admin trainingThis 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.

Download flyer (pdf) en   |    Download free trial of Tableau Server    |    Check out some of our Tableau vizzes


Master Tableau Server Architecture

Tableau Server configurationThis 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.

Download flyer (pdf) en   |    Download free trial of Tableau Server    |    Check out some of our Tableau vizzes

KNIME Training

Automate Your Work with KNIME

KNIME training KNIME SchulungFree up your creative energy – no more repetitive work in Excel. This 2-day hands-on course is designed to provide you with the knowledge necessary to automate MS Excel work using KNIME. Entirely visual with no programming required, KNIME allows users to visually create data flows, selectively execute some or all analysis steps, and later inspect the results, models, and interactive views.

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. There are no specific 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 simple and complex joins across data sources. Workflow synchronisation / Automate send emails. Case studies (Swiss Chocolate Factory, Super Shoes). Working with KNIME as a team. Node naming convention / KNIME Team Space / KNIME Server / Metanodes.

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Data Science

Tools for Data Scientists

Data Science ToolsThis 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. Each section includes an abundance of real-life examples and practical exercises.

Target Audience Anyone who works with data for analysis purposes, predictive and descriptive. There are no specific technical knowledge prerequisites. This training is the ideal preparation for the “Big Data Analytics” course.

Content Work with data in relational databases: select, link, update, retrieve with ease the data you need. R: the most popular, standard, integrated, and non-proprietary software for 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 for data science: an easy-to-understand, general-purpose programming language for integrating your data work into a production environment, such as web apps or a corporate database. Visual data exploration: learn how intuitive, fast, modern in-memory visualisation helps data scientists, analysts and business people alike to get the most out of their data.

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Data Science Boot Camp

Data Data Science CourseThis 5-day intensive course is focused on many aspects of Data Science, including quantitative analysis, data modeling, data management, and visualization. The course can be tailored depending on your interests and experience. For example, introduction to Python if you’re new to this programming language and an advanced lesson in machine learning if you’re already familiar with this topic.

Target Audience Anyone works with software and has an interest and ambition to master data science.

Content Four components: 1) Modeling and Mapping, 2) Visualization, Reporting & Storytelling, 3) Quantitative Analysis, and 4) Data Management. 1) Modeling and Mapping: Create descriptions of activity landscapes that are the context for the data science; formulate and prioritize relevant questions; mapping of the available data onto the landscape. 2) Visualization, Reporting & Storytelling: Visualize the information hidden in the data; develope story points and lines; communicate facts through the effective use of layout and graphics. The “journalism” part of data science. 3) Quantitative Analysis: Statistics, machine learning, simulation, predictive analysis. Use quantitative methods in support of summarizing facts, pattern recognition and generating realistic scenarios based on what we know. 4) Data Management: Prepare data so that the above activities can be executed efficiently and with as little interruption as possible; logical and technical structuring and handling of information for performant visual and algorithmic analysis. Tools: R, Python, Tableau, SQL database, Key/Value database (Hadoop, MongoDB), graph database (Neo4j, igraph). Work mode: A mix of lectures, hands-on exercises directly related to the lectures, and cases.


Hands-on Data Modeling

Data Modeling Data ModellingThis 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.

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Data Warehouse Concepts & Design

Data Warehouse DWH DatenbankThis 1-day hands-on course is designed to provide attendees with a complete overview of the concepts and the design methodologies of a Data Warehouse. Each section includes an abundance of real-life examples and of 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.

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Introduction to SQL

Intro SQLThis 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 of practical exercises.

Target Audience Anyone who works with data in relational databases. There are no specific technical knowledge prerequisites. This training is the ideal preparation for Quantum’s “Advanced SQL and database tuning” course.

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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Digital Transformation Program

Digitale Transformation

A company’s transition from traditional to digital requires a change of mindset and an updating of processes and skills. This program is designed to provide attendees with the understanding of the business potential of data-driven processes, as well as the knowledge and the practical skills needed to implement, run and evaluate them. The program is offered in two tracks:

Download flyer (pdf)    Executives and Managers (en)    Specialists and Data Scientists (en)

Customize Your Training Program

Paints NotebookMix and match our existing courses and create a training program that fits your schedule and professional development needs. Contact us to request more info about the many options for a customized training program.

For example, data visualization with Tableau and graph databases with Neo4j or introductions to Python, R, and SQL.

Practical Information


Library

For each course listed above, the following applies:

Price         

CHF 990.– per person per day excl. VAT. Pricing can vary depending on number of days and participants. Please enquire directly.

Language  

Available in English and German.

Location  

At our facilities at Technopark Zürich or at your company’s site.

Duration   

Sessions can be full or half days.