Visão Geral

Curso Alteryx Overview, Introdução ao Alteryx ensina os participantes a usar o Alteryx Designer para preparar, combinar, analisar, dinamizar, analisar, moldar e transformar seus dados.

Objetivo

Após realizar este Curso Alteryx Overview, você será capaz de:

• Trabalhar com a interface do Alteryx Designer
• Conectar e atualizar fontes de dados
• Limpar e solicitar registros
• Renomeie e altere o tipo de dados dos campos
• Filtrar registros
• Combine dados de fontes diferentes
• Analisar, manipular e dinamizar dados
• Dados agregados
• Domine as melhores práticas de fluxo de trabalho e armazene partes de fluxos de trabalho em cache
• Dados de saída para vários formatos
• Realize uma preparação avançada em seus dados

Materiais

Conteúdo Programatico

1. Introduction
2. Understand Alteryx Designer terminology
3. Easily navigate the Alteryx Designer Interface
4. Become familiar with Designer User and Workflow Settings
5. Be able to share and save workflows
6. Understand how Designer processes data
7. Connect to and update data sources
8. Clean unwanted characters in records
9. Order records
10. Rename fields manually and dynamically
11. Detect and change field data types manually and automatically
12. Filter records and use a conditional expression to update/add fields
13. Identify unique records
14. Blend data from disparate sources
15. Append records from different sources
16. Merge records from different sources on key fields
17. Add fields from one data set to all records in another
18. Parse data
19. Work with date/time fields
20. Build expressions to add and update fields by performing basic calculations
21. Replacing text within a field
22. Using string length and positions
23. Parse data from one field into multiple fields
24. Pivot data
25. Group and Bin Records
26. Aggregate data
27. Workflow best practices
28. Cache a portion of your workflow
29. Output data to different file formats
30. Advanced Preparation
31. Filtering and cleaning "messy data"
32. Utilizing formulas to reference multiple rows and fields
33. Binning data into respective groups
34. Creating sample sets to prepare data for predictive analytics
35. Conclusion