book

Data Engineering with Alteryx

Name: Data Engineering with Alteryx
Author: Paul Houghton
ISBN: 9781803236483

by Paul Houghton

June 2022

Beginner to intermediate

366 pages

7h 57m

English

Packt Publishing

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Data Engineering with Alteryx
ContributorsAbout the authorAbout the reviewer
Preface
Who this book is forWhat this book coversTo get the most out of this book Download the example workflow filesDownload the color imagesConventions usedGet in touchShare Your Thoughts
Part 1: Introduction
Chapter 1: Getting Started with Alteryx
Understanding the Alteryx platformThe software that makes the Alteryx platformUsing the Alteryx platform in a business scenarioHow Alteryx benefits data engineersUsing Alteryx DesignerWhy is Alteryx Designer suitable for data engineering?Building a workflow in DesignerWhat can the InDB tools do?Best practices for Designer workflowsLeveraging Alteryx Server and Alteryx Connect How can you use Alteryx Server to orchestrate a data pipeline?How does Connect help with discoverability?Using this book in your data engineering workHow does the Alteryx platform come together for data engineering?Examples where Alteryx is used for data engineeringSummary
Chapter 2: Data Engineering with Alteryx
What is a data engineer?Using Alteryx products as a data engineer Creating with Designer for data engineersAutomating with Server for data engineersConnecting end users with Alteryx ConnectApplying DataOps as an Alteryx data engineerSummary
Chapter 3: DataOps and Its Benefits
The benefits the DataOps framework brings to your organization Faster cycle timesFaster access to actionable insightsImproved robustness of data processesProvides an overview of the entire data flow Strong security and conformanceUnderstanding DataOps principlesThe People pillarThe Delivery pillarThe Confidence pillarApplying DataOps to AlteryxSupporting the People pillar with AlteryxUsing Alteryx to deliver data pipelinesBuilding confidence with AlteryxUsing Alteryx software with DataOpsAlteryx DesignerAlteryx ServerAlteryx ConnectGeneral steps for deploying DataOps in your environmentSummary
Part 2: Functional Steps in DataOps
Chapter 4: Sourcing the Data
Technical requirementsAccessing internal data sourcesData source typesUsing the Alteryx Input Data toolIntegrating public data sources with Download tool useIdentifying whether the data structure has changedCreating our first validation testLeveraging external data sources from authenticated APIsConnecting to an API with URL parametersConnecting to an API in call headersInitial cleansing of datasets A simple cleansing processA consolidated cleansing processConstructing a data pipeline in Alteryx DesignerConfiguring the annotations and namesAdding initial documentation in the workflowCalculating the first set of statistical valuesSaving the processed datasetSummary
Chapter 5: Data Processing and Transformations
Technical requirementsThe data cleansing processSelecting columnsFiltering to relevant rowsGenerating features and modifying columns with formulasSummarizing the datasetProfiling data with summary and statistical aggregationsInvestigating the variation and size range of your datasetInvestigating distributions in your datasetCorrecting missing values in your datasetTransforming our data pipelineTransforming the downloaded dataProfiling our datasetSummary
Chapter 6: Destination Management
Technical requirementsWriting to destinationsWriting to filesManaging database connectionsUsing standard connectionsHow to load data faster with bulk loadersLeveraging a database's custom toolsAccessing more data sources with custom connectionsIntegrating data pipelines across environmentsUsing a secrets file or environment variableCreating a DSN in the Windows ODBC managerGetting the most from a connectionPublishing the external data to a Snowflake destinationInstalling the driversCreating the Snowflake ODBC DSNSummary

Chapter 7: Extracting Value
Technical requirementsExploratory data analysis in Alteryx and surfacing the datasets for BI toolsIdentifying missing values and summarizing fieldsUnderstanding your value distributionFinding relationships between fieldsIdentifying any outliers in the datasetUnderstanding the difference between the Interactive Chart tool and the Insights toolMaking our datasets available for other BI toolsUsing Alteryx to deliver standard reportsCreating a formatted tableAdding visualizations to the reportAdding styling to the reportOutputting the report for consumptionSummary
Chapter 8: Beginning Advanced Analytics
Technical requirementsImplementing spatial analytics with AlteryxCreating a spatial pointGeocoding addresses to make spatial pointsGenerating trade areas for analysisCombining data streams with spatial informationSummarizing spatial informationBeginning the ML process in AlteryxUsing the Intelligence SuiteBuilding workflows with R-based predictive toolsCreating a custom Python or R script in a workflowSummary
Part 3: Governance of DataOps
Chapter 9: Testing Workflows and Outputs
Technical requirementsWorkflow tests and messagesMonitoring workflows with the Message toolMonitoring workflows with the Test toolUsing the Community CREW test macrosValidating data outputsAutomating the result monitoring actionsRunning tests on the output datasetConfirming the country of our place searchCentralizing the monitoring outputs with InsightsBuilding a control chart monitoring systemUsing insights on your Alteryx serverSummary
Chapter 10: Monitoring DataOps and Managing Changes
Technical requirementsUsing the Alteryx Server monitoring workflowAccessing and installing the server monitoring workflowReading the PDF reportUsing the data outputCreating an insight dashboard for workflow monitoringCreating a monitoring dashboardExporting the data output for external reportsExporting the MongoDB database for custom analysisThe MongoDB schemaModifying the Server Monitoring workflowUsing Git and GitHub Actions for continuous integrationSaving workflow changes with GitVerifying the XML workflowApplying standards with GitHub ActionsSummary
Chapter 11: Securing and Managing Access
Technical requirementsOrganizing content on Alteryx ServerMy WorkspaceCollectionsDistrictsManaging collectionsCreating collectionsSecuring the data environmentAlteryx Server architectureSummary
Chapter 12: Making Data Easy to Use and Discoverable with Alteryx
Technical requirementsWhat is Alteryx Connect, and how does it help DataOps?What is Connect?Areas of the Connect interfaceUsing Connect for DataOpsPublishing the data lineage to Alteryx ConnectLoading metadata directly from ConnectUsing the prebuilt workflow appsCreating a custom-built data source with the Connect APIsData nexusSyncing the Connect data dictionary with other data catalogs Using the Connect API methodsTableau Data Dictionary API exampleSummary
Chapter 13: Conclusion
The Alteryx data engineerThe functional steps in DataOpsSourcing the dataData processing and transformationsDestination managementExtracting value from dataBeginning advanced analyticsGovernance of DataOps with AlteryxTesting workflows and outputsMonitoring DataOps and managing changesSecuring and managing accessMaking data easy to use and discoverable with AlteryxOur Alteryx data pipelineFinal summary
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Data Engineering with Alteryx

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ISBN: 9781803236483

Cloud Computing