How Should You Build Your Data Team?!

3 Principles all data products share | How To Get Value From Data | Data Journeys from Vodafone, Lufthansa, CNA Insurance, Deutsche Bank, Snap, Wizard and more!

Oct 09, 2022

1 — Customers Galore!

Deutsche Bank, Snap Inc. and Wizard: My Customer Of The Week award goes to 4 amazing leaders! Deutsche Bank’s Scott Condit, Snap Inc.’s Bo Chen, Ciprian Gerea and Wizard’s Rich Archer prepared a GOOGLE NEXT panel that reveals Lakehouse best practices you’ll want to know about. More here.

CNA Insurance

You heard about it at #GartnerDA and we have a great session at Google Next on the details of CNA Insurance incredible data journey. Below what CNA’s SVP & CDAO at CNA has to say about the #datajourney!

Reduced migration timelines by nearly 50% thanks to reusable data-migration patterns and automation.
Every few minutes, new real-time data feeds land in BigQuery. A radical improvement from the daily and weekly data loads that CNA did previously
Deploy forecasting models in hours, a process that previously took many days or longer (thanks to CNA’s “Model Factory”).
Using Looker, CNA can adopt a product-centric model where they work iteratively and develop insights quickly based on a continuous feedback cycle.

Engage here!

Lufthansa

How Lufthansa increases on-time flights with ML for wind forecasting

Wind can lead to flight delays and cancellations that cost millions in lost revenue for Lufthansa. THIS is how, using machine learning, the team accurately predicted BISE hours in advance, with more than 40% relative improvement in accuracy over internal heuristics, in days, not months.

Engage here

Exabeam

Want to Know How To Build Data Products?! There is no-one better than Exabeam’s VP of Product Management Sanjay Chaudhary to take you through how his team used Dataflow, BigQuery and Looker to solve some of the most complex analytics use cases in security. Subscribe to our DataJourney playlist to be the first to get access to the video interview (link in comment!).

Engage here

Vodafone

THANK YOU Vodafone’s Data Leader’s Alberto Marco Bahon
and Cengiz for their inspiring story in Data #Innovation. Some highlights:

Vodafone serves 300M users in 24 countries on 3 continents.
17 petabytes on 600 physical servers, and 1,300 pipelines, growing to 11,000 data pipelines going onto one central cloud-based platform powered together with Google Cloud.
Vodafone’s original platform had reached its physical capacity to grow, with more than 700 servers. Maintaining and renewing and updating it would take well over 12 months to even get new hardware in the data center…
Analysis that provides greater granularity on what’s affecting NPS, smart planning to optimize infrastructure, as well as running network anomaly detection, to catch problems before they can happen or grow and of course, using predictions to ensure customers have the best possible end-to-end experience and journeys.
2 — The 2022 Cloud Software Spending Survey is OUT.
Data and security remain top spending priorities for enterprises and here are the top 5 stats I took away from the report:
1. 31% of respondents named security as their number-one priority, and data warehouse and data operations together claimed another 31% of our respondents’ top-priority slot.
2. In the next 5 years, respondents reported strong indications of budget increase in all areas. Specifically, 92% of respondents expect their security budget to increase, 84% expect data budget to increase, 69% expect increased spending in dev tools and 79% expected budget increases in AI / ML.
3. Looking out over the next six months, fewer than 10% of respondents predicted decreasing their tech spending across four major budgetary areas–security, data, development tools and artificial intelligence/machine learning.
4. Less than 2% of the respondents expected their budgets to contract by more than 10%. All of those more-cautious buyers were at companies spending less than $100 million annually on technology.
5. About 75% of the companies we surveyed allow engineers to self-select and procure technology in a bottoms-up way and install it in a “sandbox” environment. But only 14% allow such procurement for the production environment
Credit: Battery
Engage here

3 — How Should You Structure Your Data Team?!

Every customer I talk to wants to build Data Products. Often, the discussion is about the modernization of their data infrastructure and analytics platform. AND it’s always about their organizational design. In this blog Eric Broda does an amazing job describing how to structure a data team and the types of interactions they should expect with producers, consumers, enabling teams and subsystems.

Engage here!

4 — Why Data Products?! The KISS Principle

Great blog by

Clayton Karges

on the history of ‘serving data solutions’ to the 3 principles of Data Products, namely:

All data products:

Serve a persona/s (specific target consumer/s)
Are owned by someone (xyz Data Product Manager)
Go through a product life cycle, just like any other product.

Engage here.

5 — 17 technologies to boost your Data Mesh strategy.

A great blog by Angelo Martelli. Love the list — I would add financial operations and data quality to his list. What else do you think might need to be added? Do you agree with the list?!

Engage here!

BONUS!

Ready for Google Next?!

I can’t wait for you to discover best practices from data leaders at Boeing, Twitter, CNA Insurance, Telus, L’Oreal, and Wayfair and many more! Below a quick preview…more links for you in comments!

What's New with Google's Unified, Open and Intelligent Data Cloud | Google Cloud Blog

We're fortunate to work with some of the world's most innovative customers on a daily basis, many of whom come to…

cloud.google.co

Adoption Trends: BI & Analytics.

A great piece of research by Eckerson and BARC.

The good news: 50% of data & analytics leaders say BI/analytics usage has “increased a lot.”
AND the primary technical drivers of increased usage are “self-service authoring tools” (73%), data preparation tools (48%), and “embedded BI/analytics” (38%).
BUT — the percentage of employees actively using BI/analytics tools is currently 25% on average, reflecting minimal growth in the past seven years we’ve been tracking this metric.