Alteryx & Tableau

Skill Goal:

Understand the modern analytics lifecycle and the roles of Alteryx and Tableau in solving business data problems.

Skills Developed:

• Explain the complete data analytics lifecycle

• Identify where data preparation fits in analytics workflows

• Understand the role of Alteryx in data preparation

• Explain Tableau’s role in analysis and visualization

• Recognize how data preparation and visualization tools work together in real-world analytics projects

Sprint Outcome:

Ability to clearly explain the analytics lifecycle and identify how Alteryx and Tableau support data-driven decision making.

Skill Goal:

Work confidently within the Alteryx Designer environment and build structured workflows.

Skills Developed:

• Navigate the Alteryx Designer interface

• Understand tool palettes and workflow canvas

• Create and organize Alteryx workflow

• Manage workflow files and project structures

Sprint Outcome:

Ability to build and manage structured workflows using the Alteryx Designer environment.

Skill Goal:

Connect Alteryx to multiple data sources and manage data movement within workflows.

Skills Developed:

• Connect to CSV, Excel, and other data sources

• Import datasets into Alteryx workflows

• Export prepared data outputs

• Apply best practices for data connectivity and data flow management

Sprint Outcome:

Ability to integrate multiple data sources and manage workflow inputs and outputs effectively.

Skill Goal:

Understand and manage data fields to ensure data consistency and usability.

Skills Developed:

• Interpret field metadata and data types

• Rename and format data fields

• Convert and standardize field types

• Use the Select tool to manage fields within workflows

Sprint Outcome:

Ability to structure and manage dataset fields for accurate downstream analysis.

Skill Goal:

Prepare raw datasets for accurate analysis and visualization.

Skills Developed:

• Handle missing or incomplete values

• Remove duplicate records

• Identify and manage outliers

• Standardize inconsistent data

Sprint Outcome:

Ability to clean and prepare datasets for reliable analytical use.

Skill Goal:

Integrate datasets from different sources to create unified analytical datasets.

Skills Developed:

• Perform joins using common keys

• Apply inner and outer joins

• Union multiple datasets with similar structures

• Validate integrated data outputs

Sprint Outcome:

Ability to combine multiple datasets into a single analytical dataset.

Skill Goal:

Reshape and transform datasets into structures suitable for analysis.

Skills Developed:

• Pivot and transpose datasets

• Apply transformation logic within workflows

• Prepare datasets for aggregation and analysis

• Understand when transformations are required in data preparation pipelines

Sprint Outcome:

Ability to restructure datasets for analytical workflows.

Skill Goal:

Prepare aggregated datasets for business analysis.

Skills Developed:

• Sort datasets for analytical clarity

• Group data based on business rules

• Apply aggregation techniques using the Summarize tool

• Generate summary outputs for analysis

Sprint Outcome:

Ability to generate grouped and aggregated datasets ready for reporting and analytics.

Skill Goal:

Enhance datasets through calculated fields and text processing techniques.

Skills Developed:

• Write expressions for custom calculations

• Apply common expression functions

• Parse and split text fields

• Improve data quality through text manipulation

Sprint Outcome:

Ability to apply expressions and parsing techniques to enhance dataset quality and analytical value.

Skill Goal:

Design reusable workflows that support interactive and scalable analytics processes.

Skills Developed:

• Use UI tools to create interactive workflows

• Build parameter-driven workflows

• Design reusable workflow structures

• Apply usability best practices for workflow design

Sprint Outcome:

Ability to build reusable and interactive data preparation workflows.

Skill Goal:

Understand how business intelligence tools support decision making.

Skills Developed:

• Explain the role of Business Intelligence in organizations

• Navigate the Tableau Desktop interface

• Understand Tableau’s analysis-first approach

• Identify common BI use cases solved with Tableau

Sprint Outcome:

Ability to understand the role of Tableau in business intelligence and analytics environments.

Skill Goal:

Connect Tableau to prepared datasets and prepare data for analysis.

Skills Developed:

• Connect Tableau to files and databases

• Manage data sources and refreshes

• Apply basic data cleaning techniques in Tableau

• Understand the role of Tableau Prep Builder

Sprint Outcome:

Ability to prepare and structure datasets within Tableau for analytical use.

Skill Goal:

Apply calculations to derive analytical insights.

Skills Developed:

• Create calculated fields

• Apply table calculations

• Use Level of Detail (LOD) expressions

• Build analytical metrics for dashboards

Sprint Outcome:

Ability to create calculations that support advanced analysis and reporting.

Skill Goal:

Control analysis using filters, parameters, and segmentation techniques.

Skills Developed:

• Apply filters and sorting techniques

• Use parameters for dynamic analysis

• Segment data using groups, sets, and bins

• Design flexible analytical views

Sprint Outcome:

Ability to control and customize analysis for different business perspectives.

Skill Goal:

Communicate insights through effective visualizations and dashboards.

Skills Developed:

• Create geographic maps and spatial visualizations

• Build charts and analytical views

• Design dashboards for business reporting

• Apply visualization best practices

Sprint Outcome:

Ability to design clear and impactful dashboards that communicate analytical insights effectively.

Project Goal:

Apply data preparation and visualization skills to transform raw datasets into a clean analytical dataset and develop an interactive Tableau dashboard that delivers actionable business insights.

Skills Demonstrated:

• Analyze a real-world business dataset provided in class

• Identify business objectives and required performance metrics

• Import and prepare raw datasets using Alteryx workflows

• Clean and standardize inconsistent or incomplete data

• Join, union, and transform datasets from multiple sources

• Apply expressions and calculations to improve data quality

• Build reusable and parameter-driven Alteryx workflows