Want to Transform Your Data and Transform Your Business? Welcome to DIY Data from Alteryx!

Do-It-Yourself Data is all about practical data engineering to help data engineers and data analysts collaboratively profile, prepare, and pipeline your data

Want to Transform Your Data and Transform Your Business? Welcome to DIY Data from Alteryx!

Do-It-Yourself Data is all about practical data engineering to help data engineers and data analysts collaboratively profile, prepare, and pipeline your data

Upcoming Episodes: Coming soon!

 

Coming Soon!

Upcoming

Previous Episodes: Catch recordings of past webcasts

 
 
 

Paul Warburg

Sr. Professional, Product Marketing

Episode 11

How Anyone Can Work With Snowflake Data–Without Writing Code

Watch Recording
 
 
 

Paul Warburg

Sr. Professional, Product Marketing

Episode 10

Bridging the Analytics Gap: How to Eliminate the Chasm Between Analysts and IT

Watch Recording
 
 
 

Nitin Grewal

Lead Technical Product Manager

Episode 9

The Power of Unlimited Orchestration: How to Coordinate and Automate Complex Data Workflows Across the Cloud

Watch Recording
 
 
 
 

Misagh Jebeli

Senior Data Engineer

Paul Warburg

Data-Driven Product Marketer

Episode 8

Closing the Analytics Gap: How to Drive Collaboration Between Data Analysts and Engineers

Through two seasons of DIY Data, we’ve shown how Alteryx Designer Cloud (formerly Trifacta) enables self-service data engineering across several different use cases and architectures, while also demonstrating how Designer Cloud makes it easy to deliver enterprise-grade data pipelines.

Watch Recording
 
 
 

Amit Miller

Data Wrangling Engineer, Trifacta

Episode 7

Delivering Insights with Agility: How to Prepare and Deliver Data Without Writing Code

In this episode of DIY Data, we’ll demonstrate how data practitioners can build and orchestrate fully-functional data pipelines, from ingestion to delivery, without writing a single line of code.

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Eric Thomas

Sales Engineer, Alteryx

Episode 6

Clean Data, Clean Teeth with Brushing! How to Get Quick, Quality Data Insights from Complex JSON Files

How does brushing work in Designer Cloud? Let's dive deep into 3 core examples and talk about the scale of transformations with Designer Cloud

Watch Recording
 
 
 

David Sabater Dinter

Outbound Product Manager for Data Analytics, Google Cloud

Episode 5

Accelerating your Data Journey with Google Cloud Analytics Design Patterns

Designing a new data warehouse on Google Cloud can feel like choice overload. There’s a variety of analytic services to consider that will help build your data pipelines, BI, and AI outcomes.

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Steve Mitchell

Solutions Engineer

Episode 4

Faster Data Engineering from Designer Cloud powered by Trifacta With Pushdown Optimization

As data architectures evolve towards the modern data stack with ELT approaches, the difficult work of transformation (the T in ELT) is pushed onto the cloud data warehouses (CDW) to leverage the scale and power of these data repositories.

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Vijay Balasubramaniam

Director of Partner Solutions

Episode 3

How Designer Cloud Fits into Your Data Architecture - ETL, ELT, Custom Coding

Data engineering has evolved over the years to include various techniques such as ETL, ELT, or even custom code. Do you need to move your architecture to meet your data engineering needs? The answer is No. Find out why!

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Connor Carreras

Director of SaaS Adoption & Enablement

Episode 2

How to Clean, Prepare, and Transform Data for Marketing and Sales Analytics

Delivering high-quality analytics requires scale, ease of use, and accuracy. In episode 2 of DIY Data, learn to use pre-built templates from Designer Cloud that can get you started right away to generate the right analytics for marketing and sales.

Watch Recording
 
 
 

Misagh Jebeli

Senior Data Engineer, Alteryx

Episode 1

Analytics in the Cloud: Enabling the Modern Data Stack

Whether you are a Fortune 500 company or an emerging startup, data is the most relevant entity to build workflows and get advanced insights into your business. But, how do you build a data workflow that can be open, flexible, and scalable to keep up with the demands of the business and help obtain the required analytics?

Watch Recording