Today we’re back with another guest from the Netherlands. I’m not sure what it is about the Dutch, but they’ve been on a roll with some helpful thought leadership when it comes to data. My guest is Rick van der Lans, a highly-respected analyst, consultant, author, and international lecturer specializing in data warehousing, business intelligence, big data, and database technology.
I came across one of Rick’s whitepapers a few months ago on data virtualization. We got in touch and sat down to talk more in depth about the topic. Rick has a lot of data street cred. For many years, he has served as the chairman of the annual European Enterprise Data and Business Intelligence Conference in London and the annual Data Warehousing and Business Intelligence Summit in The Netherlands. He has written tons of articles, blogs, and several books, including the first book on SQL. There will be links to some of the places and things Rick has written and other info in the show notes below.
Topics: Rick’s background: author, blogger, consultant – worked on data virtualization (DV) for last 6-7 years
How did Rick get interested in DV?
Classical data warehouses vs. logical data warehouses
What is bi-modal BI? (term introduced by Gartner in 2014) Agile/Self-Service vs. longer, more cautious approach
Bi-modal BI vs. the Data Quadrant
Comparison of major Data Virtualization Vendors Denodo
Tibco DV Manager (bought from Cisco recently)
Red Hat
Data Virtuality Ultrarep
Others (AtScale, Cero, StoneBond, IBM – new entry acquired from Rocket Software)
Some are more mature, some are newer (Denodo vs. Tibco = green apples vs. red apples)
Companies rolling their own DV (in-memory / views vs. a dedicated tool)
DV products are not DB views on steroids
Lineage / impact analysis and other features
Caching vs. materialization – can store cached data in a virtual table in an intermediary data store. Can be help performance or prevent interference from a transactional source (keeping results consistent for an entire week).
How DV can help organizations that are struggling
How DV may not be a silver bullet
How are different industries embracing these principles?
What patterns do you see in companies embracing these principles?
What companies should not use this? DV not great at this time on unstructured audio / video, auto-tagging of images
Why a classical DWH experienced person may fail at DV
What are the warning signs that a DV is going off the rails? Fuzzy logic needed to combine disparate sources
Not an integration cureall
How you deploy these with projects
How to get started? (pick a single, sexy report as a starting point)
Where do you go next? (how to unify other data delivery systems, data marketplaces, API gateways)
How to avoid misconceptions about DV (it is slow, only about integration, etc.)
How to contact Rick
The first book on SQL
Places to find Rick’s work: He has published blogs for the following websites:
TechTarget.com
B-eye-Network
Business-analytics.biz
He has written the following books:
Data Virtualization for Business Intelligence Systems
Introduction to SQL (has sold over 100,000 copies and has been translated in many languages)
SQL for MySQL Developers
The SQL Guide to SQLite
The SQL Guide to Ingres
The SQL Guide to Pervasive PSQL
Music: Deep Sky Blue by Graphiqs Groove via FreeMusicArchive.org
Sources: https://www.denodo.com/en/system/files/document-attachments/rick_van_der_lans_bimodal_ldw.pdf
https://solutionsreview.com/data-integration/4-data-virtualization-vendors-to-watch-in-2017/
https://reprints.forrester.com/#/assets/2/545/’RES133042’/reports (Forrester Wave for Data Virtualization)
http://www.datavirtualizationblog.com/achieving-lightning-fast-performance-logical-data-warehouse/
http://www.r20.nl/rick_f__van_der_lans1.htm
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