Alteryx Advanced from Coursera

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Syllabus

Data Cleansing and Manipulation

In this module, we will explore the foundational skills necessary for effective data cleansing and manipulation in Alteryx. You'll start with an introduction to the course and Alteryx's features, move through handling multiple files and sampling techniques, and learn advanced grouping, cleaning, and parsing methods. This section sets the stage for building robust data workflows.

Working In-Database

In this module, we will delve into the power of in-database processing with Alteryx. You'll learn to perform complex data operations directly within your database environment, enhancing efficiency and scalability. Topics include in-database blending and using select and summarize tools to streamline your data workflows.

Apps and Macros

In this module, we will elevate your skills in creating and optimizing apps and macros within Alteryx. You'll gain insights into advanced techniques, batch processing, error handling, and customization. By the end, you'll be able to design sophisticated, efficient workflows and share them with others.

Intelligence Suite

In this module, we will journey through the comprehensive landscape of machine learning using Alteryx's Intelligence Suite. From foundational concepts to advanced techniques, you'll learn to build, train, deploy, and operationalize machine learning models, tackling real-world business problems with cutting-edge analytics.

Exercises and Course Close

In this module, we will put your knowledge to the test with hands-on exercises designed to consolidate your learning. You'll tackle real-world datasets, apply advanced Alteryx tools, and solve complex data problems. The course concludes with a final thank-you note and a recap of your journey through advanced data analytics with Alteryx.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Offers hands-on exercises and real-world examples, which allows learners to immediately apply their knowledge to practical scenarios

Covers data cleansing, handling multiple files, sampling, and regex for parsing XML, which are essential skills for data manipulation

Explores Alteryx's machine learning capabilities, from building models to deploying them for fraud detection and customer segmentation

Requires basic Alteryx knowledge, so learners without this background may need to acquire it before taking this course

Teaches in-database processing, blending, and selecting data efficiently, which enhances efficiency and scalability

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Alteryx Advanced with these activities:

Review Basic Alteryx Concepts

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Refresh your understanding of basic Alteryx concepts to ensure a solid foundation for the advanced topics covered in this course.

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Review Alteryx's interface and core tools.
Practice building simple workflows.
Complete introductory Alteryx tutorials.

Review 'Practical Data Analysis - Second Edition'

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Review a book on data analysis to gain a broader understanding of the concepts and techniques used in Alteryx.

View Putting Knowledge to Work on Amazon

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Read the chapters on data cleansing and manipulation.
Study the examples and case studies.
Relate the concepts to Alteryx workflows.

Practice Regex Parsing

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Practice regular expression parsing to improve your ability to extract data from XML and other text formats.

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Find online regex exercises.
Use Alteryx to test regex expressions.
Parse sample XML files using regex.

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Follow Advanced Alteryx Tutorials

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Follow advanced Alteryx tutorials to deepen your understanding of in-database processing, app creation, and macro development.

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Search for tutorials on Alteryx's website.
Replicate the steps in the tutorials.
Adapt the tutorials to your own data.

Write a Blog Post on Alteryx Best Practices

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Create a blog post summarizing best practices for using Alteryx, focusing on topics like workflow optimization, error handling, and data governance.

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Research Alteryx best practices.
Outline the blog post's structure.
Write the blog post with clear examples.
Edit and publish the blog post.

Build a Data Cleansing App

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Start a project to build an Alteryx app that automates data cleansing and manipulation tasks.

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Define the app's input and output.
Design the app's user interface.
Implement the data cleansing logic.
Test and refine the app.

Create a Machine Learning Model Workflow

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Create a complete Alteryx workflow that builds, trains, and deploys a machine learning model using the Intelligence Suite.

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Select a relevant dataset.
Choose an appropriate machine learning algorithm.
Build the workflow in Alteryx.
Evaluate the model's performance.
Document the workflow and results.

Career center

Learners who complete Alteryx Advanced will develop knowledge and skills that may be useful to these careers:

Data Analyst

A Data Analyst uses data to understand business trends and provide insights. This role involves collecting, cleaning, and analyzing data, often using tools like Alteryx. This course helps build a foundation in data cleansing, handling multiple files, sampling, and using regular expressions, which are essential for preparing data for analysis. Additionally, this course covers in-database processing and blending, allowing a Data Analyst to handle larger datasets more efficiently. The modules focused on apps and macros are useful for automating complex data processes, and the machine learning section allows a Data Analyst to provide more advanced analyses and predictions.

See salaries and explore the career path for Data Analyst

Business Intelligence Analyst

A Business Intelligence Analyst focuses on using data to create reports and dashboards that help businesses make strategic decisions. To do this well, this role requires a strong understanding of data manipulation and analysis techniques, including data cleansing and blending. This course introduces techniques for handling multiple files and in-database processing which can help an analyst work with a variety of data sources. The advanced modules on app and macro customization help with automating report generation, and familiarity with machine learning aids in uncovering deeper trends. Further, this helps a Business Intelligence Analyst go beyond simple reporting to provide predictive insights. Such analytical capabilities are crucial in this field.

See salaries and explore the career path for Business Intelligence Analyst

Data Scientist

A Data Scientist uses statistical and machine learning techniques to derive actionable insights and predictions from data. This role demands a thorough understanding of data manipulation, preprocessing, and model development. This Alteryx course introduces a variety of machine learning capabilities, including building and deploying models for use cases like fraud detection and customer segmentation. The course also begins with data cleaning, blending, and parsing with regex, all essential steps in the machine learning pipeline. The course also covers in-database processing and app customization. All of this helps a Data Scientist work with diverse data sets and develop efficient processes.

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Analytics Consultant

An Analytics Consultant works with clients to solve business problems using data analysis and insights. This role requires both technical proficiency and the ability to translate data into business strategies. This course provides training in data cleansing, in-database processing, and machine learning, all of which are core competencies for an Analytics Consultant. The ability to customize apps and macros equips consultants with the skills to automate processes and deliver efficient solutions. Furthermore, expertise in these skills enables an Analytics Consultant to approach complex client problems with a toolkit of powerful analytical techniques, leading to better insights and more effective strategies.

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Marketing Analyst

A Marketing Analyst uses data to measure the effectiveness of marketing campaigns and identify opportunities for improvement. This role benefits significantly from the data manipulation and machine learning skills this course provides. The course's focus on data cleansing, handling multiple files, and using regular expressions for parsing helps prepare marketing data for analysis. The machine learning capabilities help with customer segmentation and campaign optimization. A Marketing Analyst benefits from the ability to develop predictive models and automate analysis through the creation of customized apps and macros.

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Financial Analyst

A Financial Analyst analyzes financial data to provide insights and recommendations that are useful in making investment decisions or improving business performance. This role needs strong analytical skills as well as the ability to process and interpret large datasets efficiently. This course provides the tools to perform effective data cleansing, in-database processing, and blending. These are all crucial for dealing with financial data. The advanced machine learning skills can be used to create predictive models for forecasting and risk management. This course can help a Financial Analyst work with complex datasets, providing more sophisticated analyses and better investment advice.

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Operations Analyst

An Operations Analyst analyzes operational data to identify areas for improvement in efficiency and cost-effectiveness. This role requires the ability to handle large datasets and produce actionable insights. This course provides training in data cleansing, handling multiple files, and in-database processing. These capabilities are important for preparing operational data for analysis. The course also covers app and macro customization, which are useful for creating automated workflows and dashboards. In addition, expertise in machine learning techniques can help an Operations Analyst create predictive models to optimize operational processes. All of this supports informed decision-making. This course may be useful to an Operations Analyst.

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Risk Analyst

A Risk Analyst assesses and mitigates risks to an organization. This role requires strong analytical skills and the ability to work with large datasets to evaluate potential threats. This course builds a foundation in data cleansing, blending, and in-database processing, which are all useful for handling risk data. The machine learning components of the course enable a Risk Analyst to develop predictive models for risk assessment and mitigation. Additionally, the course's modules on app and macro customization help automate the data handling and analysis. This course may be useful to a Risk Analyst.

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Supply Chain Analyst

A Supply Chain Analyst focuses on optimizing the flow of goods and services within a supply chain. This role requires the ability to analyze large datasets to identify bottlenecks and inefficiencies. This course may be useful to a supply chain analyst as it introduces workflows for data cleansing and in-database processing. These are useful for preparing supply chain data for analysis. Alteryx's machine learning capabilities can help a Supply Chain Analyst create predictive models to optimize inventory management and delivery times. The customization of apps and macros can further automate routine tasks and create more efficient workflows. This course may be useful to a Supply Chain Analyst.

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Database Administrator

A Database Administrator manages and maintains databases, ensuring data integrity and accessibility. This course introduces in-database processing techniques within Alteryx, enhancing a database administrator's ability to handle data within databases. While this course is not solely focused on database administration, skills such as data cleansing and manipulation are relevant to a Database Administrator. The ability to perform in-database blending and use select and summarize tools, as covered in the course, can help a Database Administrator streamline data workflows. This course may be useful to a Database Administrator.

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Market Research Analyst

A Market Research Analyst studies market conditions to evaluate the potential for a product or service. This role requires skills in data collection and analysis along with the ability to draw useful conclusions. This course emphasizes data cleansing, handling multiple files, sampling, and using regular expressions for parsing, which may assist in preparing market research data for analysis. The skills in in-database processing and machine learning may also be helpful in this role, as these enable more sophisticated analysis. This course may be useful to a Market Research Analyst.

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Actuary

An Actuary assesses and manages financial risks using mathematical and statistical modeling. This role requires a deep understanding of data analysis and predictive modeling. Although this course focuses on Alteryx, the machine learning and data handling components may be useful to an Actuary. The course covers data cleansing, processing, and building predictive models, which are all relevant to this field, albeit through the lens of a specific software package. This course may be useful to an Actuary. Actuaries typically hold an advanced degree.

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Statistician

A Statistician designs and conducts statistical studies, analyzing data to draw conclusions. This role requires a strong foundation in statistics, as well as the ability to work with data using various tools. This course familiarizes statisticians with data cleansing, in-database processing, and machine learning within the Alteryx environment. While the focus is on the software, some of the underlying principles of data handling and modeling may be useful to a Statistician. This course may be useful to a Statistician. Statisticians typically hold an advanced degree.

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Software Engineer

A Software Engineer designs, develops, and maintains software applications. This role may require some familiarity with data handling and machine learning concepts. This course may be useful to a software engineer who wants to learn more about data processing with Alteryx, data cleansing, and in-database processing. The modules on app and macro customization may provide helpful skills for improving and integrating Alteryx with existing workflows. While this is not typically the main job function of a Software Engineer, some overlap may occur. This course may be useful to a Software Engineer.

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Management Consultant

A Management Consultant provides strategic advice to businesses on how to improve their performance. While this role is not typically focused on technical data analysis, certain elements of this course may be relevant. A Management Consultant might benefit from the ability to understand data and use it for decision-making. This course introduces data cleansing, in-database processing, and basic machine learning concepts. These elements may help a consultant make more informed recommendations. This course may be useful to a Management Consultant.

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Reading list

We've selected one books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Alteryx Advanced.

Putting Knowledge to Work

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Provides a practical guide to data analysis techniques, including data cleansing, manipulation, and visualization. It offers real-world examples and case studies that complement the Alteryx course material. The book is particularly helpful for understanding the underlying principles behind the Alteryx tools and how to apply them effectively. It serves as a valuable reference for data professionals looking to enhance their analytical skills.

Putting Knowledge to Work

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Alteryx Advanced

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