My Digital FootPrint

Image. It is an algorithm: globalimaging.com/images/modis-atmos.jpg Algorithms     are the foundation of your computing interactions. An algorithm is the means by which a computer program can make decisions about you, for you, or decisions that affect you.  Algorithms are the translation of what you do into rules and policies that a computer understands (i.e. 0s and 1s). Like it or not, you are influenced by them as much as you influence them. Algorithms need data, they use digital data that you give, leave or have tracked about you (willingly or not).  This input into an algorithm is your digital footprint, which comes from Facebook, Twitter, text messages, email, key stokes, swipes, gestures, play lists, payment records, your routes, navigation – indeed anything you do which is an interaction with an electronic device. This is the basis of what an algorithm knows about you. It is how an algorithm can model you, it takes input and predicates based on what you have done and

Researchers at Massachusetts Institute of Technology (MIT) and the Catholic University of Louvain studied 15 months' worth of anonymised mobile phone records for 1.5 million individuals. Here's  the full study. With no real surprise they found from the "mobility traces" - the evident paths of each mobile phone - that only four locations and times were enough to identify a particular user. We are predictable and so Dan Ariely Work comes true.  In their own words “ They studied fifteen months of human mobility data for one and a half million individuals and find that human mobility traces are highly unique. In fact, in a dataset where the location of an individual is specified hourly, and with a spatial resolution equal to that given by the carrier's antennas, four spatio-temporal points are enough to uniquely identify 95% of the individuals. We coarsen the data spatially and temporally to find a formula for the uniqueness of human mobility traces given their resol

The question I have is what data are you giving off (right now) that is giving me the feedback about your state of mind (how you feel about work).  If I combine your data with the data I get from the wider team (and social norms) and how it has changed over time – can I tell how well you are managed?  Probably Seeking insights from digital footprint data – we just need to know what to look for.

Gartner Predictions for Big Data from Bruno Aziza

source : http://www.google.com/transparencyreport/userdatarequests/ Google has released new data for the   Transparency Report , showing that the steady increase in government requests for our users’ data continued in the second half of 2012, as usage of our services continued to grow. They have shared figures like this   since 2010   because it’s important for people to understand how government actions affect them. For the first time they are including   a breakdown of the kinds of legal process that government entities in the U.S. use when compelling communications and technology companies to hand over user data. From July through December 2012: 68 percent of the requests Google received from government entities in the U.S. were through subpoenas. These are requests for user-identifying information, issued under the Electronic Communications Privacy Act (“ECPA”), and are the easiest to get because they typically don’t involve judges. 22 percent were through ECPA search

The Value of our Digital Identity report recently published by   Boston Consulting Group , based on a new empirical consumer research, offers a new perspective. The most important takeaway from this research is that it quantifies the current and potential economic value of digital identity: "The report shows that the value created through digital identity can indeed be massive: €1 trillion in Europe by 2020, or roughly 8 percent of the combined GDP of the EU-27. For European businesses and governments, the use of personal data will deliver an annual benefit of €330 billion by 2020—bringing growth to an otherwise stagnant economy. For individuals, the value will be more than twice as large: €670 billion. Much of that will be due to online services such as Facebook and Google that can be offered free of charge—thanks to business models that monetize personal data—yet are highly valued by consumers"

What can we do to make data more human in 2013? Executives need to understand and experience data ownership.   We generate data but we cannot visualise it.  Why not provide tools to visualize and explore data, and show the worth and utility of the information that you can derive.  Could make for an interesting board meeting. Executive lead transparent, open and balanced conversations about data and ethics.   I start with asking questions that help form models for thinking about data and how leadership teams come to their own opinions on data, based on personal experience and therefore have different perspectives about data.  Differences and gaps in thinking leads to friction about how to treat their own personal data, how to treat customer data and gaps between company branding messaging and expectations.  These gaps can lead to frictions which mean teams cannot move forward with a common approach on how to treat customer data. Here are previous blog that bring these models together. H

This infographic from  Zendesk shows that consumers rank quality (88%) and customer service (72%) as the two biggest drivers of loyalty.  The infographic also looks at the importance of first impressions, how loyal customers share their brand experiences and the impact of loyalty schemes.

THE HUMAN FACE OF BIG DATA APP Sign up here http://hfobd.metalayer.com?lrRef=5bz7G The Human Face of Big Data metaLayer Download the free mobile app and learn about yourself, how you compare to others, and what your phone can tell you about your life. Compare answers about yourself, your family, trust, sleep, sex, dating, and dreams with millions of others around the world. Find your Data Doppelganger. Map your daily footprint, share what brings you luck, and get a glimpse into the one thing people want to experience during their lifetime. We'll donate $1 per download to charity: water for the first 50,000 downloads, as a way to say thank you for participating in The Human Face of Big Data. charity: water uses 100% of public donations to directly fund clean water projects. Guardian article : http://www.guardian.co.uk/news/datablog/2012/oct/02/human-face-of-big-data-smartphone-app-launch

Source : http://smartdatacollective.com/rautsan/74631/so-what-prescriptive-analytics?

Steam from  http://stream.krm.com/Mediasite5/Viewer/?peid=4463bdefbf6b40ec9bdd5c69a0e406e5 Historically, companies have decided which markets to focus on and have allocated sales resources based on looking at past results and using gut instincts. But today, "big data" and deep analytical capabilities give sales and marketing leaders a better way to make decisions. Managers now have the ability to use data to precisely identify lucrative micromarkets and better align sales resources to maximize opportunities. Companies that use analytics to pursue a micromarket strategy are dramatically increasing sales without spending more. In this HBR webinar, McKinsey partners Manish Goyal and Homayoun Hatami describe how to use data to drive sales — without increasing costs.

Source http://blogs.hbr.org/cs/2012/09/predicting_customers_unedited_behavior.html And http://blogs.hbr.org/cs/2012/10/big_datas_biggest_obstacles.html by ALEX "SANDY" PENTLAND   Big Data provides objective information about people's behavior. Not their beliefs or morals. Not what they would like their behavior to be. Not what they tell the world their behavior is, but rather what it really is, unedited. With Big Data, current limitations on the interpretation of human behavior mostly go away. We can know whether you are the sort of person who will pay back loans. We can see if you're a good leader. We can tell you if you're likely to get diabetes. Scientists can do all this because Big Data is beginning to expose us to two facts. One, your behavior is largely determined by your social context. And two, behavior is much more predictable than you suspect. Together, these facts mean that all I need to see is some of your behaviors, and I can infer the rest, just by

Source : http://musicdatascience.com/emi-million-interview-dataset/ Using this data set : http://musicdatascience.com/music-data-science-hackathon/

Source : http://musicdatascience.com/emi-million-interview-dataset/ Using this data set : http://musicdatascience.com/music-data-science-hackathon/

Source : http://musicdatascience.com/emi-million-interview-dataset/ Using this data set : http://musicdatascience.com/music-data-science-hackathon/

Source : http://musicdatascience.com/emi-million-interview-dataset/ Using this data set : http://musicdatascience.com/music-data-science-hackathon/

report download : http://www.elon.edu/docs/e-web/predictions/expertsurveys/2012survey/PIP_Future_of_Internet_2012_Big_Data_7_20_12.pdf Pew Internet/Elon University survey , 53% of a handpicked group of “Internet experts, observers and stakeholders“ said big data would produce an overall positive effect by the year 2020. Meanwhile, 39% said it would have an overall negative effect (8% didn’t answer). Many who said big data would have a positive influence on the future pointed to its potential to solve diverse problems.

Source Martin Pasquier : How to value big data ? Methodological issues and a glance at the future Good blog in summary…. Data needs Method = valuable Data needs Context = information/ knowledge/ insights Data needs safeguards = not sure if it is the data or the access to it Half of the value of data is down to the use/ abuse from the supply side The new half of the value from data comes from demand side (VRM) – you and me publishing intentions.