Tableau Explorer: Interactive Data Analysis and Dashboard Navigation Training Course

This instructor-led, live training Kenya (online or on-site) is tailored for data scientists and developers who aim to utilize and integrate SQL, Python, and Tableau to perform complex data analysis, processing, and visualization.

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

• Set up the necessary environment to perform data analysis with SQL, Python, and Tableau.
• Understand the key concepts of software integration (data, servers, clients, APIs, endpoints, etc.).
• Get a refresher on the fundamentals of Python and SQL.
• Perform data pre-processing techniques in Python.
• Learn how to connect Python and SQL for data analysis.
• Create insightful data visualizations and charts with Tableau.

Upon completion of this training, participants will be equipped with the ability to:

This instructor-led, live training Kenya (available online or onsite) is tailored for data scientists who wish to programme in R for Tableau.

• Execute Tableau analytics by integrating R.
• Return values to Tableau using learning algorithms developed in R.
• Organise and visualise R functions within the Tableau interface.
• Drive business operational decisions through data insights.

This guided, live training in Kenya (online or onsite) is designed for beginner to intermediate data analysts looking to use Tableau Desktop to turn raw data into meaningful insights through visual representations such as charts, graphs, maps, and tables.

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

• Connect to multiple data sources (Excel, CSV, databases, cloud-based) and understand the differences between live and extract connections.
• Prepare and clean data for analysis, including renaming fields, handling null values, and combining datasets via joins and blends.
• Create basic visualizations like tables, bar charts, line charts, and maps, and apply filters to refine data presentation.
• Develop intermediate visualizations including geographic maps, dual-axis charts, and utilize hierarchies, groups, and sets to enhance analysis.
• Build calculated fields and parameters to create dynamic and customized visualizations based on user inputs and logic functions.
• Design interactive dashboards and stories, incorporating multiple visualizations and filters to tell a cohesive narrative.

Upon completing this training, participants will have acquired the ability to:

This instructor-led, live training in Kenya (online or onsite) is aimed at intermediate-level digital forensic and cybersecurity professionals who wish to have a comprehensive understanding and practical skills in using Tableau Forensic Imager for digital forensic purposes.

• Understand the role and importance of digital forensic imaging in investigations.
• Operate Tableau Forensic Imager to acquire forensically sound images.
• Apply best practices in handling and preserving digital evidence.
• Navigate the software interface to configure, execute, and manage imaging tasks.
• Analyze and validate forensic images to ensure integrity and admissibility in court.

This instructor-led, live training in Kenya (available online or onsite) is designed for data analysts and data scientists looking to search, analyze, and visualize data using Tableau.

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

• Connect to your data.
• Edit and save a data source.
• Understand Tableau terminology.
• Use the Tableau interface / paradigm to effectively create powerful visualizations.
• Create calculations including arithmetic calculations, custom aggregations and ratios, date math, and table calculations.
• Represent your data using different visualization types.
• Build dashboards to share visualizations.

This instructor-led, live training in Kenya (online or onsite) is aimed at beginner-level to intermediate-level data analysts who wish to gain practical knowledge of Tableau Prep Builder and the essential mapping functionalities in Tableau to address data preparation and visualization challenges.

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

• Connect to a variety of data sources, including cloud-based and local files, and manage live and extracted data connections.
• Perform data fusion and combination using advanced joining techniques to merge multiple datasets from different sources for better analysis.
• Create calculated fields and perform operations to manipulate and analyze data dynamically.
• Publish and update prepared data to Tableau Server or Tableau Online, enabling automated updates and scheduling.
• Create basic and advanced maps with geographic data, including filled maps, density maps, and dual-axis maps.
• Apply mapping techniques to solve real-world business problems by creating interactive, detailed geographic visualizations.

This live, instructor-led training in Kenya (available online or onsite) is designed for advanced data professionals who want to utilize Tableau for building complex visualizations, optimizing dashboards, and performing advanced data analysis.

By the end of the course, participants will be able to install and configure Tableau for advanced use, create advanced calculations, design interactive dashboards, and optimize performance.

This engaging 4-day course is designed for Tableau beginners. Participants will gain comprehensive familiarity with all Tableau features and learn how to create and share data visualizations effectively. The curriculum guides you through every step, including connecting to data sources, creating calculations, selecting appropriate charts, building dashboards, and publishing your work.

The course is structured into lectures dedicated to each topic, followed by practical exercises. The session concludes with a 30-minute test and a 60-minute project assignment.

Course milestones:

• Get accustomed to the Tableau interface.
• Connect to and manipulate your data.
• Utilize Tableau features.
• Construct insightful visualizations.
• Distribute your work to a wider audience.

Format of the Course:

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