Agile Data Warehousing Today
with Kent Graziano
a full day training event
with a hosted happy hour the evening before at On Deck Sports Bar
by DAMA – Portland Metro Chapter
October 5th, 2017
Montgomery Park Ballroom
sponsored by Snowflake & WhereScape
Session 1 – Agile Methods and Data Warehousing: How to Deliver Faster
Session 2 – Agile Data Engineering: Introduction to Data Vault 2.0
Session 3 – Case Study: Data Warehousing in the Real World
Session 4 – Demystifying Data Warehousing as a Service (DWaaS)
Full abstract below
$129 members or employees of corporate members
$159 non-members
$99 students with valid institutional ID (contact vp_finance@damapdx.org)
About the Speaker
Kent Graziano is a Senior Technical Evangelist with Snowflake Computing and the author of The Data Warrior blog. He is a Data Vault Master and certified Data Vault 2.0 Practitioner. Kent has given hundreds of presentations, nationally and internationally and in 2014, he was voted one of the best presenters at OUGF14 in Helsinki, Finland.
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Member Registration – $129
Non-member Registration – $159
$129 members
$159 non-members
$99 students with valid institutional ID (contact vp_finance@damapdx.org)
RSVP for the hosted happy hour the evening before the event
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DAMA Portland Metro Chapter
P.O. Box 2343
Portland, Oregon 97208
RSVP for the hosted happy hour the evening before the event
Full Abstract
This all day workshop will provide you the background and principles to use agile in your data warehouse and business intelligence projects. It will introduce you to a modern method for agile data modeling, Data Vault 2.0, and provide you with a detailed, real world case study. At the end we will talk about how the cloud has changed everything and how you can enable your agile data warehouse by using a modern data warehouse as a service (DWaaS) built in the cloud, for the cloud.
Session 1- Agile Methods and Data Warehousing: How to Deliver Faster
Most people will agree that data warehousing and business intelligence projects take too long to deliver tangible results. Often by the time a solution is in place, the business needs have changed. With all the talk about Agile development methods like SCRUM and Extreme Programming, the question arises as to how these approaches can be used to deliver data warehouse and business intelligence projects faster. This presentation will look at the 12 principles behind the Agile Manifesto and see how they might be applied in the context of a data warehouse project. The goal is to determine a method or methods to get a more rapid (2-4 weeks) delivery of portions of an enterprise data warehouse architecture. Real world examples with metrics will be discussed.
Session 2 – Agile Data Engineering: Introduction to Data Vault 2.0
As we move more and more towards the need for everyone to do Agile Data Warehousing, we need a data modeling method that can be agile with us. Data Vault Data Modeling is an agile data modeling technique for designing highly flexible, scalable, and adaptable data structures for enterprise data warehouse repositories. It is a hybrid approach using the best of 3NF and dimensional modeling. It is not a replacement for star schema data marts (and should not be used as such). This approach has been used in projects around the world (Europe, Australia, USA) for over 15 years but is still not widely known or understood. The purpose of this presentation is to provide attendees with an introduction to the components of the Data Vault Data Model, what they are for and how to build them. The examples will give attendees the basics:
- What the components of a DV model are
- How to build, and design structures incrementally, without constant refactoring
Session 3 – Case Study: Data Warehousing in the Real World
At a former health-care client, we were not able to implement a pure Data Vault 2.0 architecture. Instead, we had to evolve a hybrid solution that uses Type 2 persistent stage tables that we tie together using standard Hub and Link structures along with a Key Map table. While we were able to utilize DV 2.0 concepts such as MD5 hash keys, in order to avoid joins in loading the stage tables we had to come up with a way to resolve the Business Keys further into the process. In addition, we were able to build a BI reporting layer using virtual dimensions that were hybrid type 1 and 2 combined. I will show you our solution with examples of real working code.
Session 4 – Demystifying Data Warehousing as a Service (DWaaS)
We all know that data warehouses and best practices for them are changing dramatically today. As organizations build new data warehouses and modernize established ones, they are turning to Data Warehousing as a Service (DWaaS) in the cloud, in hopes of taking advantage of the performance, concurrency, simplicity, and lower cost of a SaaS solution or simply to reduce their data center footprint (and the maintenance that goes with that).
But what is a DWaaS really? How is it different from traditional on-premises data warehousing? How can a cloud-native data warehouse help enable your agile data warehouse practice?
In this talk I will:
- Demystify DWaaS by defining it and its goals
- Discuss the real-world benefits of DWaaS
- Discuss some of the features in a DWaaS solution as exemplified by the Snowflake Elastic Data Warehouse.
- Show example how these features can make your data warehouse more agile
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