How Big Data is Leveraged for Recruiting

Join our upcoming #DataTalk on Twitter as we talk about ways big data can detect and prevent fraud. Our big data tweet chats are hosted by @ExperianDataLab and occur every other Thursday at 5 p.m. ET.
TOPIC: How Big Data is Leveraged for Recruiting
WHEN: Thursday, July 30, 2015 at 5 p.m. ET
Easy ways to chat with us on Twitter: Twubs or Tchat
If you have questions or suggestions for future topics and guests, please tweet @MikeDelgado.
Questions We’ll Discuss:
- Q1: What does big data have to do with recruiting?
- Q2: How is big data changing how recruiters find qualified candidates?
- Q3: What are benefits of using big data for recruiting?
- Q4: What kind of data is analyzed for recruitment? Any social data?
- Q5: What are some of the risks of using big data for recruiting?
- Q6: What are ways big data is reducing costs and increasing efficiency in recruiting?
- Q7: What are some successful examples of how big data has been used for recruiting?
- Q8: What challenges do recruiters have with big data?
- Q9: What should recruiters know about hiring algorithms and equal opportunity laws?
- Q10: What final tips do you have for recruiters and HR professionals for using big data?
Past Video Chats:
- The Legal Aspects of Managing & Using Big Data [VIDEO]
- Using Data for User Engagement & Product Development [VIDEO]
- Data Mining for Dummies [VIDEO]
Past Twitter Chats:
- How Big Data Can Detect & Prevent Fraud
- How to Improve Customer Experiences with Big Data
- How to Leverage Data for Good
- Predictive Data Analytics to Help Your Customers
- Trends in Big Data & Challenges
- What is a Data Scientist
- Why Does Big Data Matter
- Ways to Be Data Driven
- Data Science for Dummies
Highlights from Past Tweet Chats:
Analyzing data is one thing – leveraging it to drive transformational changes to your business is really what’s critical. [Retweet]

Without data, decisions are opinions rather than facts. As engineers, we want to make decisions based on fact. [Retweet]

Instincts aren’t scalable, data science is. [Retweet]
