Data for Good, Data for Evil and the Aggregation of Everything

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Bill Boorman will lead a discussion about the data that surrounds us, that can be used for different things and how we can aggregate data from different sources in order to see the big (or at least bigger) picture. What does data mean? Why is the recruiter experience vitally important? How can you distinguish coincidence from cause? Attendees will learn the answers to these questions and more in this webinar.

Personalbeschaffung & Personalwesen

Data for Good, Data for Evil
& the Aggregation of Everything
@BillBoorman, MD Innovation Technology
#truFounder

“Dataclysm by Christian Rudder”
"Because we can doesn't mean we should"

“You are who you interact with.”
"Because we can doesn't mean we should"

“Because we can doesn’t mean we should.”
"Because we can doesn't mean we should"

“Business Data v Personal Data”
"Because we can doesn't mean we should"

“Privacy by Design”
"Because we can doesn't mean we should"

“A Shift in Favor of Privacy-By-Design”
As we recently saw with the fall-out from #UberGate, where Uber openly touted their
‘God View’ application that enabled employees to track the location of Uber riders.
Without safeguards around data usage, data joining, access and anonymization – the
unintended consequences of big data can be destructive to not just the reputation of a
single business, but potentially an entire ecosystem.
Nick Halstead: Founder Datasift

“Involuntary Data in the Internet of Things”
"Because we can doesn't mean we should"

“Cause v Coincidence”
"Because we can doesn't mean we should"

“Coincidence - A coincidence is a sequence of events
that, although accidental, seem to have been
planned, arranged, or correlated.”

“Cause = Effect”
"Because we can doesn't mean we should"

“Your EVP: We are going to spy on your personal
data.”
"Because we can doesn't mean we should"

Find me, friend me, follow me, poke me.
Let’s stay connected.

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How To Optimize Your Tech Recruiting Stack Patrick Christell, Senior Sourcer at Hire4ce, meets all the qualifications of “MASTER.” We’re talking a Full-Lifecycle Recruiter, Project Manager and Agile sourcing pod-builder with seven-plus years of progressive experience recruiting for technology companies across the boards. He also has a rather impressive tech stack, which is what this is all about. Patrick is here to give you 60-minutes of training and live Q&A that will help you learn to recruit top talent. In this webinar we will cover: - How to search. Tools like Hiretual, Seekout, AmazingHiring (and their plusses and minuses). The difference between searching for senior-level engineers, how to know if you are on a purple squirrel hunt, and what to with a BONUS live demo that iterates a single string. - How to run a sourcing pod. Learn how Patrick creates his own CRM that can do outreach and reporting - How to understand tech without being a techie. What a software stack even is, understanding how it fits together, learning what each part of the stack technologies are associated with. - How to engage talent. Why a mixture of broad spectrum outreach and personalized outreach is best. What cadence works best in 2019. Why only using inmails screws you, and how to leverage the phone even if you hate using it (TextNow). Nobody’s got time for a floppy stack. Let Patrick show you how to build in functionality and results.

Master Technical Recruiting Workshop: How to Recruit Top Tech Talent

RecruitingDaily.com LLC

Buying TA technology can be complex and often daunting. We feel ya. For this special occasion, we're pulling out our "Short-List of Things That Annoy the Heck Out Of Us When Trying to Find TA Tech." Long title, yes, but it fits. Variety of tools. Infinite categories of tools. Burning bridges TA Leaders face on a near-daily basis. An explosion of solution providers. Over-marketing of tools. Sound familiar? We thought so. As a buyer, you need a way to approach the market and find the right tools at the right time. This webinar is here to help. Martin Burns is VP of Consulting Services for HireClix, founder of the Facebook TA tech group “Talent Product Plays”, and an experienced practitioner in corporate talent acquisition. He has led multiple recruitment organizations, selected, purchased, and implemented technology for firms ranging from 50 employees to over 50,000, as well as built products for the industry. He brings a practical, informed view of TA technologies to the table and a rational blueprint for what can seem an overly complex challenge.

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Data for Good, Data for Evil and the Aggregation of Everything

1. Data for Good, Data for Evil & the Aggregation of Everything @BillBoorman, MD Innovation Technology #truFounder

2. This is not me.

3. “Dataclysm by Christian Rudder” "Because we can doesn't mean we should"

5. “You are who you interact with.” "Because we can doesn't mean we should"

6. Data for Good

7. “Because we can doesn’t mean we should.” "Because we can doesn't mean we should"

8. Data for Evil

9. The Data Miners

10. “Business Data v Personal Data” "Because we can doesn't mean we should"

11. “Privacy by Design” "Because we can doesn't mean we should"

12. “A Shift in Favor of Privacy-By-Design” As we recently saw with the fall-out from #UberGate, where Uber openly touted their ‘God View’ application that enabled employees to track the location of Uber riders. Without safeguards around data usage, data joining, access and anonymization – the unintended consequences of big data can be destructive to not just the reputation of a single business, but potentially an entire ecosystem. Nick Halstead: Founder Datasift

13. “Involuntary Data in the Internet of Things” "Because we can doesn't mean we should"

14. The Rise of The Guess Machines

15. “Cause v Coincidence” "Because we can doesn't mean we should"

16. “Coincidence - A coincidence is a sequence of events that, although accidental, seem to have been planned, arranged, or correlated.”

17. “Cause = Effect” "Because we can doesn't mean we should"

18. The Aggregation of Everything

19.

20. “Your EVP: We are going to spy on your personal data.” "Because we can doesn't mean we should"

21. Find me, friend me, follow me, poke me. Let’s stay connected.

Data for Good, Data for Evil and the Aggregation of Everything

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