pages.databricks.com Open in urlscan Pro
104.17.73.206  Public Scan

URL: https://pages.databricks.com/202212-amer-ve-dlt-live-workshop_dlt-workshop-128.html?utm_source=databricks&utm_medium=emai...
Submission: On December 05 via api from US — Scanned from DE

Form analysis 3 forms found in the DOM

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visits, average time spent on the website and what pages have been loaded, with
the purpose of displaying targeted ads.399 daysHTTP_mkto_trkMarketoContains data
on visitor behaviour and website interaction. This is used in context with the
email marketing service Marketo.com, which allows the website to target visitors
via email. 399 daysHTTP_rdt_uuidRedditUsed to track visitors on multiple
websites, in order to present relevant advertisement based on the visitor's
preferences. 3 monthsHTTP_session_id [x3]Databricks.com
databricks.pathfactory.com
jukebox.pathfactory.comStores visitors' navigation by registering landing pages
- This allows the website to present relevant products and/or measure their
advertisement efficiency on other websites. 399 daysHTTP_uetsidMicrosoftCollects
data on visitor behaviour from multiple websites, in order to present more
relevant advertisement - This also allows the website to limit the number of
times that they are shown the same advertisement. 1
dayHTML_uetsid_expMicrosoftContains the expiry-date for the cookie with
corresponding name. PersistentHTML_uetvidMicrosoftUsed to track visitors on
multiple websites, in order to present relevant advertisement based on the
visitor's preferences. 1 yearHTML_uetvid_expMicrosoftContains the expiry-date
for the cookie with corresponding name.
PersistentHTMLsnowplowOutQueue_#_post2Databricks.comCollects statistical data
related to the user's website visits, such as the number of visits, average time
spent on the website and what pages have been loaded. The purpose is to segment
the website's users according to factors such as demographics and geographical
location, in order to enable media and marketing agencies to structure and
understand their target groups to enable customised online
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Build and Deploy ETL pipelines with Delta Live Tables

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As data volumes and their complexity continue to rapidly grow, the tools to
process that data have not kept pace. The burden is put primarily on data
engineering teams, who need to stitch together and maintain many different
elements of code and supporting infrastructure to process data from source to
destination, which is repeated across dozens of data sources and multiple stages
of data processing. Data engineers develop ETL pipelines as individualized
tasks, making it difficult to “stitch” together multiple sequences of the ETL
pipeline.

 

With Delta Live Tables (DLT), data teams have an ETL framework that uses a
simple declarative approach to building reliable data pipelines. DLT
automatically manages your infrastructure at scale so you can spend less time on
tooling and focus on getting value from data. 

 

In this session, you will learn how to build and deploy a declarative streaming
ETL pipeline at scale with DLT, how DTL automates complex and time-consuming
tasks like task orchestration, error handling, recovery and auto-scaling with
performance optimizations.  Finally, we will show you how DLT enables data teams
to deliver fresh, up-to-date data with built-in quality controls and monitoring
ensuring accurate and useful BI, Data Science and ML.

 * Get started with Delta Live Tables (DLT)
 * Create DLT pipelines with SQL, using a Twitter stream and Hugging Face
   example
 * Create Workflows with DLT
 * Use DLT from Python with data ingestion from OSS Apache Kafka or Confluent
   Cloud

Agenda (PT)

 * 9:00 – 9:15 AM: Introduction to Delta Live Tables
 * 9:15 – 10:30 AM: Delta Live Tables demo
 * 10:30 – 10:35 AM: Q&A and Wrap up

Register today and reserve your spot!

 

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