Elevator Pitch
Join us as we walk through the modernization and eventual rebirth of a data strategy. Selected highlights include spelunking data of old, diagnosing data sickness and the quest for business value. Bovard will share experiences learned in data strategy and give concrete advice for revitalizing yours.
Description
The floor hummed with the electric energy of passion poured into code, quickly packaged and shipped to the customers in bold, shiny applications. Our story begins squeezed into the corner of this room - the data team. Analytics requirements were pushed out of the critical path for launches slowly and then all at once. The data team is fighting against prioritization, cooperation, and soon, relevance. This is sadly the state of many organizations, to a lesser or greater degree. How can we fix this? How can we bring our data strategy back from the dead?
Over the course of this talk Bovard will draw upon his experience in a successful startup (Workiva) and Google to bring you a case study on an effective data strategy in the modern computing environment in three acts. Act I finds us venturing into the depths of data dungeon to diagnose our data malaise. Act II begins us upon the quest for business value and the many pitfalls encountered along the way. Finally Act III we scale up and resurrect our data strategy. Will it be a glorious phoenix or Frankenstein’s monster? Tune in to find out!
Notes
Submission Details
Overview
- Type: 30 minute experience report (45 is possible if needed)
- Subject: Data Analytics / Big Data
- Topics: architecture, tools, infrastructure, case study
Technical Requirements
To get the most out of it, some familiarity with data warehousing and ETL concepts along with understanding of NoSQL databases and streaming. However the talk is designed so that people of all levels should walk away with something actionable.
My Qualifications
I’ve got a deep background in setting and delivering on data strategy at both Workiva and Google. Though both of these experiences were different, they had quite a few similarities. At Workiva I reported directly the CTO after he asked me to “get our data strategy” back on track and over the course of 3 years I led a team of 4-12 developers to do exactly that - ending in us directly positively impacting sales. At Google, I’ve been working on setting our data strategy for success in an upcoming initiative. This talk is the best of what I’ve learned in these experiences as well as my Masters.
Conference Experience
Speaking
- Talked to MT DevFest in 2013 about Node.js (video has been taken down, unfortunately)
- Presented at two internal developer conferences at Workiva (not public)
Attendance
- Google IO
- JSConf
- Strata Hadoop World
- DataEDGE
- MT Dev Fest
Experience
- Analytics Lead at Workiva - Reported directly to CTO, charged with revitalizing company data operations. Grew a catalog of 1000s of events and TBs of data. Directly effected product sales
- Data Tech Lead at Google - Set data strategy for upcoming initiatives in the hardware product area.
Education
- Master of Information and Data Science from UC Berkeley - topics included applying data decisions to organization, data ethics, big data, ML
Outline
Act I: The Problem
- What is holding us back from getting value from our data?
- How to we get quality data? (discoverable, standardized, correct)
- How to think about data architecture problems
Act II: The Quest for Business Value
- What NOT to do (a lot of things)
- Investing a lot in new work AND getting business value
- Start with the problems and questions
- Invest in data strategically
- Show value early and often
Act III: Scaling up
- After initial success, how do you make headway?
- How to get buy-in from other teams and executives
- Pheonix or Frankenstein? Integrating with legacy data infrastructure without polluting your system