Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Analytics and Big Data:
A Quick Overview
H Frank Cervone, PhD, CPHIMS
School of Public Health, University of Illinois at C...
Image courtesy of Forbes.com
Results from IBM survey of “Driving More Results from Data” 2013
Image courtesy of Penn State
Hidden patterns
Submission network picture. Credit: (c)
Science, DOI: 10.1126/science.1227833
Hidden correlations
Image courtesy of PracticalAnalytics
Image courtesy of thebigdatablog
Image courtesy of canspirit.net
Tools for analysis
CRS_SUBJ_CDCRS_NBRCRN CRS_TITLE PREREQUISITES
BSTT 400 BSTT 400 Biostatistics I
BSTT 401 BSTT 401 Biostatistics II BSTT 40...
Issues and concerns
Image courtesy of eCampusNews
Image courtesy of ZDNet
Indiscriminate data collection and mining
Image courtesy of the City of Morgantown
Neither snake oil nor silver bullet
Thank you
H Frank Cervone
fcervone@uic.edu
Analytics and Big Data: A Quick Overview
Analytics and Big Data: A Quick Overview
Analytics and Big Data: A Quick Overview
Analytics and Big Data: A Quick Overview
Analytics and Big Data: A Quick Overview
Analytics and Big Data: A Quick Overview
Analytics and Big Data: A Quick Overview
Upcoming SlideShare
Loading in …5
×

Analytics and Big Data: A Quick Overview

609 views

Published on

This is a presentation given at the Metrics in Libraries symposium held at the University of Toronto on Monday, May 11, 2015

Published in: Data & Analytics
  • Be the first to comment

  • Be the first to like this

Analytics and Big Data: A Quick Overview

  1. 1. Analytics and Big Data: A Quick Overview H Frank Cervone, PhD, CPHIMS School of Public Health, University of Illinois at Chicago School of Information, San Jose State University
  2. 2. Image courtesy of Forbes.com
  3. 3. Results from IBM survey of “Driving More Results from Data” 2013
  4. 4. Image courtesy of Penn State Hidden patterns
  5. 5. Submission network picture. Credit: (c) Science, DOI: 10.1126/science.1227833 Hidden correlations
  6. 6. Image courtesy of PracticalAnalytics
  7. 7. Image courtesy of thebigdatablog
  8. 8. Image courtesy of canspirit.net
  9. 9. Tools for analysis
  10. 10. CRS_SUBJ_CDCRS_NBRCRN CRS_TITLE PREREQUISITES BSTT 400 BSTT 400 Biostatistics I BSTT 401 BSTT 401 Biostatistics II BSTT 400 BSTT 494 BSTT 494 Intro to Data Analysis w/R BSTT 505 BSTT 505 Logist Regr & Survivl Analysis BSTT 400 BSTT 505 BSTT 505 Logist Regr & Survivl Analysis BSTT 401 BSTT 506 BSTT 506 Design of Clinical Trials BSTT 400 BSTT 506 BSTT 506 Design of Clinical Trials BSTT 401 BSTT 507 BSTT 507 Sampling/Est Methods in PH BSTT 401 BSTT 507 BSTT 507 Sampling/Est Methods in PH BSTT 502 BSTT 523 BSTT 523 Biostatistics Methods I BSTT 524 BSTT 524 BSTT 524 Biostatistics Laboratory BSTT 523 BSTT 525 BSTT 525 Biostatistics Methods II BSTT 523 BSTT 525 BSTT 525 Biostatistics Methods II BSTT 524 BSTT 535 BSTT 535 Categorical Data Analysis BSTT 525 BSTT 535 BSTT 535 Categorical Data Analysis STAT 411 BSTT 536 BSTT 536 Survival Analysis BSTT 525 BSTT 536 BSTT 536 Survival Analysis STAT 411 BSTT 537 BSTT 537 Longitudinal Data Analysis BSTT 525 BSTT 537 BSTT 537 Longitudinal Data Analysis STAT 411 BSTT 538 BSTT 538 Biostatistical Consulting BSTT 525 BSTT 550 BSTT 550 Biostatistical Investigations BSTT 535 BSTT 550 BSTT 550 Biostatistical Investigations BSTT 536 BSTT 550 BSTT 550 Biostatistical Investigations BSTT 537 BSTT 550 BSTT 550 Biostatistical Investigations BSTT 538
  11. 11. Issues and concerns Image courtesy of eCampusNews
  12. 12. Image courtesy of ZDNet
  13. 13. Indiscriminate data collection and mining
  14. 14. Image courtesy of the City of Morgantown Neither snake oil nor silver bullet
  15. 15. Thank you H Frank Cervone fcervone@uic.edu

×