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Big Data for International Development

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Alex Rascanu delivered the "Big Data for International Development" presentation at the International Development Conference that took place on February 7, 2015 at University of Toronto Scarborough.

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Big Data for International Development

  1. 1. BIG DATA FOR INTERNATIONAL DEVELOPMENT Alex Rascanu Digital marketing strategist Founder of EVENTS& and Marketers Without Borders February 7, 2015 International Development Conference at University of Toronto Scarborough
  2. 2. AGENDA 1. What is big data? 2. How can we better understand and use big data? 3. How to work with big data (human and technical requirements) 4. Challenges & considerations when working with big data 5. Opportunities to use big data in the development sector 6. Conclusion & useful resources (reports, books, events)
  3. 3. 1. WHAT IS BIG DATA? Big Data = large amounts of digital data continually generated by the global population 40% is the amount of available digital data is projected to increase annually
  4. 4. 2. HOW CAN WE BETTER UNDERSTAND AND USE BIG DATA? 1) Start with questions, not with data. 2) Figure out what resources and process you need. 3) Create actionable insights with the objective of influencing behaviour inside your organization or within the society at large.
  5. 5. 2. HOW CAN WE BETTER UNDERSTAND AND USE BIG DATA? (continued)
  6. 6. 3. HOW TO WORK WITH BIG DATA Software: MS Access is good for basic analysis but will scale poorly in the face of dozens of gigabytes of data. For complex analysis, use Hadoop (free, Java- based programming framework), Google Could Platform, Microsoft Azure, or Amazon’s EC2. You should feel comfortable using APIs (Application Programming Interfaces). Collect the following info. to ensure that your analysis is transparent regarding its assumptions: “the type of information contained in the data”, “the observer or reporter”, “the channel through which the data was acquired”, “whether the data is quantitative or qualitative,” and “the spatio-temporal granularity of the data, i.e. the level of geographic disaggregation (province, village, or household) and the interval at which data is collected”
  7. 7. Your staffing needs: a good data scientist needs to have computer science and math skills as well as a “deep, wide-ranging curiosity, is innovative and is guided by experience as well as data”. Other necessary skills include the ability to clean and organize large data sets, particularly those that are unstructured, and to be able to communicate insights in actionable language. An intimate knowledge of the real world situation of interest is also critical. Limited budget? Get help from volunteer technical communities through initiatives such as hackatons. 3. HOW TO WORK WITH BIG DATA (continued)
  8. 8. 4. CHALLENGES & CONSIDERATIONS WHEN WORKING WITH BIG DATA 1. Privacy (most sensitive issue) 2. Access & sharing (some new data sources are openly available on the web, but most of it is privately held by corporations) 3. Analysis & interpretation (what type of data is being analyzed? who is the representative sample of the population? realize that correlation doesn’t necessarily mean causation) 4. Anomaly detection (figuring out (ab)normaly in human ecosystems is very difficult, you need to come up with ways to characterize and detect socioeconomic anomalies in their context)
  9. 9. 4. CHALLENGES & CONSIDERATIONS WHEN WORKING WITH BIG DATA (continued) It’s hard to collect household data in real-time, so development progress is difficult to track Correlation does not necessarily equal causation
  10. 10. 5. OPPORTUNITIES TO USE BIG DATA IN THE DEVELOPMENT SECTOR
  11. 11. 5. OPPORTUNITIES TO USE BIG DATA IN THE DEVELOPMENT SECTOR (continued) Timeframe to intervene is relative to the context: Twitter-based vs. Official Influenza Rate in the U.S.
  12. 12. 5. OPPORTUNITIES TO USE BIG DATA IN THE DEVELOPMENT SECTOR (continued)
  13. 13. 5. OPPORTUNITIES TO USE BIG DATA IN THE DEVELOPMENT SECTOR (continued) Detailed reports for these projects are available at www.unglobalpulse.org/research/projects.
  14. 14. 6. CONCLUSION & USEFUL RESOURCES How can Big Data achieve its potential in international development? 1. Incentives need to be created for private sector to share data 2. Create opportunities for academic researchers to collaborate 3. New partnerships and technologies for the safe and responsible sharing and use of data for the public good
  15. 15. 6. CONCLUSION & USEFUL RESOURCES (continued) This thread on This thread on
  16. 16. THANK YOU Alex Rascanu alex@alexrascanu.com @alexrascanu
  17. 17. Sources: 1. http://live.worldbank.org/sites/default/files/Big%20Data%20for%20Development%20Report_fina l%20version.pdf 2. http://www.unglobalpulse.org/sites/default/files/Primer%202013_FINAL%20FOR%20PRINT.pdf 3. http://www.slideshare.net/unglobalpulse/un-global- pulsebigdatafordev10july2012?qid=75e9e919-00b7-4b72-b80d- c64604c06eb6&v=default&b=&from_search=7 4. http://www.unglobalpulse.org/sites/default/files/BigDataforDevelopment- UNGlobalPulseJune2012.pdf 5. https://www.flickr.com/photos/ict4d/3058524421/in/photolist-5EgJKF-9oRtRC-fSQFBk-5F7UNL- nNB6WD-5soUMT-nKRuGL-ecWYu6-dyZdMb-bc3ejv-7MBXf2-nuk883-nuk8qN-edmbCo- 7MFXfd-f5RdPT-7MFXcJ-aXfyNz-6Un1H6-5du11Z-b77MPa-5bkNpc-3PbYW7-d7N3Bh- 8uHH1w-ecUq8m-2Jswc3-ecV6UF-9NoyWS-DkYze-nukCq8-nuksVg-nJM1Tj-nLPxvV-6Yfqmg- 5EvE4Q-4cBZpq-7MBX8K-9PAHGi-7MFX9j-5ErnCH-7MBX3M-j1Auxn-6giuSF-5VnpVH-T6HG- bD5u4u-4zYBUG-92T4GS-6obnWJ

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