Course Introduction
The Alteryx for Data Preparation and Analytics Automation Training Course provides practical, hands-on training for professionals who need to automate repetitive data preparation, blending, transformation, and analytics workflows. Alteryx Designer provides a visual environment where users connect tools to construct workflows for data preparation, blending, and analytics, allowing complex processing tasks to be represented as repeatable and maintainable workflows rather than lengthy manual procedures.
Participants learn how to connect Alteryx to common business data sources and develop structured workflows that move data through extraction, cleansing, transformation, joining, aggregation, validation, and output stages. The training covers core preparation tools such as Filter, Formula, Data Cleansing, Data Cleanse Pro, and Auto Field, giving learners practical techniques for handling nulls, unwanted characters, inconsistent formats, field types, and other common data-quality problems.
A major focus of the course is data blending and transformation. Participants learn how to combine datasets using joins, unions, lookups, and other workflow techniques while controlling data granularity and ensuring that the resulting analytical dataset accurately reflects business requirements. They also learn how to create calculated fields, reshape information, aggregate records, parse complex values, and build repeatable transformation logic that can replace manual spreadsheet-based preparation processes.
The course then progresses from individual transformations to complete analytics automation workflows. Participants learn how to organize workflows into logical stages, use annotations and configuration standards, manage dependencies, troubleshoot errors, validate intermediate results, and improve workflow efficiency. Alteryx provides workflow configuration, dependency management, reusable templates, and workflow optimization capabilities that support the development and maintenance of repeatable analytical processes.
Advanced automation is an important component of the program. Learners develop reusable macros that package frequently repeated analytical processes into single tools, including standard, batch, and iterative macros. They also learn how analytic apps can provide user interfaces that allow users to supply their own data or parameters without rebuilding the underlying workflow. These capabilities enable organizations to convert individual data-preparation solutions into reusable analytical assets that can support broader teams and recurring business processes.
The final part of the course focuses on operationalizing automated workflows through scheduling, packaging, dependency management, quality controls, and production-oriented design. Participants learn how workflows can be scheduled through supported Alteryx environments and how workflow packages can include dependencies for execution and sharing. By completing an end-to-end project, learners gain practical experience transforming raw business data into validated analytical outputs while automating the repetitive processes required to produce them.
Duration
5 days
Who Should Attend
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Data analysts responsible for preparing, transforming, combining, and validating business datasets.
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Business intelligence professionals seeking to automate repetitive data preparation and reporting processes.
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Analytics professionals who want to replace manual spreadsheet-based workflows with reusable Alteryx processes.
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Data engineers who need practical experience with visual data preparation, transformation, blending, and workflow automation.
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Business analysts working with multiple data sources that require recurring cleansing and transformation.
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Reporting specialists who want to automate recurring data preparation before producing analytical reports.
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Operations analysts responsible for consolidating and standardizing data from multiple business systems.
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Finance, sales, marketing, and supply-chain analysts working with recurring data integration and preparation tasks.
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Data quality professionals who need repeatable workflows for cleansing, validation, standardization, and exception handling.
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Analytics engineers developing reusable preparation workflows for self-service analytics and business intelligence teams.
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BI developers who want to incorporate Alteryx workflows, macros, analytic apps, and automated processes into analytics solutions.
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Professionals seeking hands-on training in Alteryx Designer for scalable data preparation and analytics automation.
Course Objectives
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Develop practical proficiency in Alteryx Designer for connecting, preparing, transforming, blending, validating, and automating business data workflows.
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Build repeatable workflows that replace manual data preparation processes with structured, documented, and maintainable analytical automation.
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Apply data-quality techniques to identify and correct null values, inconsistent formats, unwanted characters, incorrect data types, and other common preparation issues.
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Combine multiple datasets using joins, unions, lookups, and related techniques while maintaining appropriate data granularity and analytical accuracy.
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Create calculated fields and transformation logic using Formula and related tools to derive business attributes and analytical measures.
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Design workflows that incorporate filtering, parsing, aggregation, reshaping, sampling, validation, and output processes for diverse analytical requirements.
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Develop reusable macros and analytic apps that allow recurring analytical processes to be standardized and executed with user-defined inputs or parameters.
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Apply workflow organization, documentation, dependency management, troubleshooting, and optimization practices to improve maintainability and execution efficiency.
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Implement scheduling and operational practices that support recurring workflow execution and reliable delivery of prepared analytical datasets.
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Complete an end-to-end Alteryx automation project that integrates multiple sources, performs data-quality improvements, generates analytical outputs, and demonstrates reusable automation.
Comprehensive Course Outline
Module 1: Alteryx Designer Fundamentals and Workflow Automation
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Understanding Alteryx Designer architecture, the workflow canvas, tool palette, configuration panels, results window, workflow settings, and the overall visual approach to analytics automation.
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Building a first workflow by connecting input, preparation, transformation, analytical, and output tools into a logical sequence of repeatable processing steps.
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Understanding how connected tools pass data through a workflow and how workflow configuration affects layout, execution, annotations, and overall maintainability.
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Establishing workflow-development standards around naming, annotations, organization, documentation, testing, and separation of preparation, transformation, analysis, and output stages.
Module 2: Data Connections and Input Management
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Connecting Alteryx workflows to spreadsheets, delimited files, databases, cloud sources, and other supported data sources while evaluating source structure and data quality.
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Configuring Input Data workflows and understanding how connection settings, field definitions, file paths, and source dependencies affect repeatable processing.
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Working with multiple input sources and designing workflows that accommodate recurring files, changing source locations, and standardized input structures.
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Managing input and output dependencies so workflows remain portable, maintainable, and suitable for sharing or execution in supported Alteryx environments.
Module 3: Data Cleaning and Quality Improvement
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Using Data Cleansing and Data Cleanse Pro techniques to address null values, unwanted characters, inconsistent capitalization, punctuation, and other common data-quality issues.
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Applying Filter, Formula, Select, Auto Field, and related preparation tools to standardize field structures, remove unwanted records, and improve data consistency.
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Detecting duplicate records, incomplete values, invalid categories, inconsistent identifiers, unexpected formats, and other issues that can compromise downstream analytics.
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Building repeatable quality-control stages that validate cleaned data before it proceeds to transformation, analysis, reporting, or automated output processes.
Module 4: Data Transformation and Preparation Workflows
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Creating formulas and derived fields to calculate business metrics, classify records, standardize values, create flags, and implement reusable transformation logic.
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Parsing complex text and structured values into analytical fields while maintaining consistent data types, naming conventions, and downstream usability.
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Reshaping and aggregating datasets to appropriate analytical granularity using summarize, transpose, cross-tab, and related transformation techniques.
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Designing multi-stage preparation workflows that transform raw operational datasets into structured, analysis-ready tables suitable for reporting and business intelligence.
Module 5: Data Blending, Joins, and Integration
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Combining datasets through Join, Union, Find Replace, and related tools while selecting appropriate keys and understanding how different integration methods affect the resulting data.
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Diagnosing duplicate records, unmatched rows, missing keys, unexpected row multiplication, and other integration problems caused by inconsistent source structures.
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Building workflows that integrate customer, product, financial, operational, transactional, reference, and external datasets into unified analytical outputs.
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Applying data-granularity and relationship checks to ensure that blended datasets preserve the intended business meaning and do not introduce misleading analytical results.
Module 6: Advanced Workflow Design and Analytics Automation
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Designing complex workflows with logical branches, reusable transformation stages, validation points, analytical calculations, and multiple output pathways.
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Applying workflow annotations, comments, containers, templates, constants, and configuration standards to improve readability and simplify long-term workflow maintenance.
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Using workflow execution results and intermediate outputs to validate transformations, diagnose unexpected results, and identify processing bottlenecks.
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Developing automation patterns that allow recurring data preparation and analytical tasks to execute consistently with minimal manual intervention.
Module 7: Macros and Reusable Analytics Components
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Understanding how Alteryx macros package workflows or groups of tools into reusable components that can be inserted into other workflows.
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Building standard macros to encapsulate frequently repeated data preparation and analytical processes while creating appropriate macro inputs and outputs.
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Developing batch and iterative macros for scenarios where a reusable process must execute repeatedly based on incoming records, control parameters, or iterative conditions.
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Creating maintainable macro repositories and managing dependencies so reusable analytical components can be shared consistently across workflows and development teams.
Module 8: Analytic Apps and Parameter-Driven Automation
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Understanding how Alteryx analytic apps combine workflows with user interfaces so users can execute predefined analytical processes using their own inputs and parameters.
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Designing Interface Designer components that allow users to provide file paths, selections, thresholds, filters, or other parameters without modifying the underlying workflow.
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Building parameter-driven analytical solutions that standardize recurring business processes while allowing controlled flexibility for different departments, periods, regions, or datasets.
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Testing analytic apps and interface behavior to ensure user inputs are correctly passed into workflow tools and produce reliable, understandable results.
Module 9: Workflow Optimization, Scheduling, and Production Practices
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Applying workflow optimization principles to reduce unnecessary processing, improve data-flow efficiency, and structure complex workflows for reliable recurring execution.
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Managing workflow dependencies, packages, input paths, output paths, reusable components, and deployment considerations for collaborative analytics environments.
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Scheduling workflows, apps, or packages through supported Alteryx environments and designing recurring automation around appropriate execution frequencies and business requirements.
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Establishing production practices covering validation, logging, error handling, documentation, versioning, dependency management, testing, and controlled workflow deployment.
Module 10: End-to-End Alteryx Data Preparation and Automation Project
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Designing a complete automated workflow that combines multiple business data sources and applies structured cleansing, transformation, integration, validation, and analytical preparation.
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Implementing advanced calculations, aggregation, filtering, data-quality controls, and output processes to create a reliable business-ready analytical dataset.
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Converting a repeated workflow component into a reusable macro or analytic app and configuring appropriate inputs, parameters, dependencies, and user controls.
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Presenting the completed automation solution while demonstrating workflow architecture, data-quality improvements, performance considerations, reusable components, scheduling strategy, and recommendations for production deployment.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
