January 13: Crowdsourcing Big Data creativity? Humans and machines collaborate co-dependently: http: //www.linkedin.com/groups/Crowdsourcing-Big-Data-creativity-Humans-3981538.S.5828479628192284673?qid=5d182aa4-d863-45e7-a15c-939099ba1cf9&trk=groups_most_recent-0-b-ttl&goback=.gmr_3981538
January 14: Internet of Things? Logs are the most fundamental storage abstraction for IoT: http: //www.linkedin.com/groups/Internet-Things-Logs-are-most-3981538.S.5828850870707593218?qid=cae76663-fa5e-49c4-8a76-ae6079044607&trk=groups_most_recent-0-b-ttl&goback=.gmr_3981538
January 15: Cognitive computing? Cloud cognition incorporates semantic technologies: http: //www.linkedin.com/groups/Cognitive-computing-Cloud-cognition-incorporates-35222.S.5829217423135375361?view=&gid=35222&type=member&item=5829217423135375361&trk=NUS_DISC_Q-ttle
January 16: Data-scientist skillsets? Learning how to squeeze the wrong out of the right: http: //www.linkedin.com/groups/Datascientist-skillsets-Learning-how-squeeze-3981538.S.5829566686088437762?view=&gid=3981538&type=member&item=5829566686088437762&trk=NUS_DISC_Q-ttle
January 17: Big Science? Overreliance on big data can stunt development of scientific rigor:
January 20: Advanced visualization? Using visuals to discriminate among machine-learning algorithms: http: //www.linkedin.com/groups/Advanced-visualization-Using-visuals-discriminate-3981538.S.5831043108116144130?view=&gid=3981538&type=member&item=5831043108116144130&trk=NUS_DISC_Q-ttle
January 21: Security of big data? Shoddy lifecycle management is ironic data security: http: //bit.ly/19KxeLU
January 22: NoSQL? The architecture that's still curiously absent: http: //bit.ly/1hiGE0g
January 23: Context accumulation? Narratives drive home relevance of statistical models : http: //bit.ly/1ipUXUF
January 27: Smarter planet? Intelligence for a self-healing landscape: http: //bit.ly/Mke7Ou
January 28: Data monetization? Pay the persons for their personal data: http: //bit.ly/1euQitq
January 29: Internet of Things? Instrument the birdies, bees, and other beasties: http: //bit.ly/1mXoBxZ
January 30: Recommendation engines? The untapped potential of video, image, and gesture analytics in retail showrooms: http: //www.linkedin.com/groups/Recommendation-engines-untapped-potential-video-3981538.S.5834652556705439745?view=&gid=3981538&type=member&item=5834652556705439745&trk=NUS_DISC_Q-ttle
January 31: Sexy statistics? The vintage kick of old data poured into fresh analytic bottles: http: //www.linkedin.com/groups/Sexy-statistics-vintage-kick-old-35222.S.5835021357993197570?trk=groups%2Finclude%2Fitem_snippet-0-b-ttl
February 3: Peta-governance? Bottom-line ROI from boosting the quality of experience data: http: //bit.ly/1k3tvfL
February 4: Smarter planet? Continuous crowdsourcing of quality-of-life data will power livable urban existence: http: //bit.ly/1e0j6td
February 5: Small data? Predicting rare events from limited data: http: //www.linkedin.com/groups/Small-data-Predicting-rare-events-35222.S.5836830634034634754?qid=c15580b4-ba76-468d-a30b-5ef4f9fe6755&trk=groups_most_recent-0-b-ttl&goback=.gmr_35222
February 6: Hadoop uber-alles? Climbing the slope of enlightenment, arriving at plateau of productivity: http: //bit.ly/1bth3hl
February 7: Machine learning? Maximum impact from bigger data & deeper learning: http: //bit.ly/1lG5jSB
February 10: Ambient analytics? Mobile data traces the contours of urban experience: http: //bit.ly/1eJjWRi
February 11: Data-scientist skillsets? Psychological insights key to modeling customer causation: http: //bit.ly/1eQhUxg
February 12: Meaty metadata? Extracting corpus omniscience from big data: http: //bit.ly/1lCii4h
February 13: Complex event processing? Plucking event graphs from the deep, dark, dynamic Web: http: //bit.ly/LXgp4W
February 14: Big data vision? Modern economy mills new value from its own digital exhaust : http: //bit.ly/1jgr2eP
February 17: Real-world experiments? Disrupting your enterprise while mitigating the risks of doing so: http: //bit.ly/1j4ob9p
February 18: Engaging customer as individual? Abandonment metrics as warnings and/or opportunities: http: //bit.ly/1jNwZDo
February 19: Graph analysis? Identifying the happy medium between the under- and overconnected influencers:
February 20: Cognitive computing? When biases cloud automated cognition: http: //bit.ly/1gnZORl
February 21: Hadoop uber-alles? Resist the new-age push to "all-in-one" database basket: http: //www.linkedin.com/groups/Hadoop-uberalles-Resist-newage-push-35222.S.5842657299339964420?qid=92547a60-e1aa-4da3-9866-7e0318e871d6&trk=groups_most_recent-0-b-ttl&goback=.gmr_35222
February 24: Geospatial analytics? Analytic surveillance in the cause of resource stewardship: http: //bit.ly/1bF4vZO
February 25: Healthcare analytics? Tuning the fusion of human physiology & machine physics: http: //bit.ly/1cjHl6h
February 26: Gamified analytics? Brownie points for consumers who share their brand love: http: //linkd.in/OColuT
February 27: Sexy statistics? Distinguishing hidden (but real) patterns from those that are real-seeming (but bogus): http: //www.linkedin.com/groups/Sexy-statistics-Distinguishing-hidden-but-3981538.S.5844799260897349634?view=&gid=3981538&type=member&item=5844799260897349634#commentID_null
February 28: Workload-optimized systems? HPC now mostly big data analytics with growing emphasis on small lots & asynchronous processing: http: //www.linkedin.com/groups/Workloadoptimized-systems-HPC-now-mostly-35222.S.5844801547774496768?view=&gid=35222&type=member&item=5844801547774496768#commentID_null
March 3: Big Media? The era of the exabyte is fast upon us: http: //www.linkedin.com/groups/Big-Media-era-exabyte-is-3981538.S.5846262024794841091?trk=groups%2Finclude%2Fitem_snippet-0-b-ttl
March 4: Storage optimization? Compress what you can, extract insights prior to purging the rest: http: //www.linkedin.com/groups/Storage-optimization-Compress-what-you-3981538.S.5846616501175480322?trk=groups%2Finclude%2Fitem_snippet-0-b-ttl
March 5: Data-scientist skillsets? Juggling visualizations, algorithms, and narratives: http: //bit.ly/1fGTvvS
March 6: Internet of Things? New measurement tools for candid ethnography: http: //bit.ly/MQirV0
March 7: Advanced visualization? Eyeballing the dark dimensions : http: //bit.ly/1geDBUw
March 10: Healthcare analytics? Sensing, mapping, and mining the mystery of the brain: http: //bit.ly/Od5pSt
March 11: Geospatial analytics? Statistical lenses strip darkness from the distant cosmos: http: //www.linkedin.com/groups/Geospatial-analytics-Statistical-lenses-strip-3981538.S.5849123432330969088?view=&gid=3981538&type=member&item=5849123432330969088#commentID_null
March 12: Experience optimization? Big data framing the engagement with art and culture: http: //bit.ly/PsBUNP
March 13: Business process optimization? Plugging a lean, mean analyzing machine into your manufacturing operations: http: //www.linkedin.com/groups/Business-process-optimization-Plugging-lean-3981538.S.5849857487125102596?view=&gid=3981538&type=member&item=5849857487125102596#commentID_null
March 14: Big-data development? Don't understaff and overstretch your analytics development team : http: //www.linkedin.com/groups/Bigdata-development-Dont-understaff-overstretch-35222.S.5850215090921426947?view=&gid=35222&type=member&item=5850215090921426947#commentID_null
March 17: Recommendation engines? Analytics grooving with whatever grooves groove you: http: //bit.ly/1hrL30v
March 18: Internet of Things? Storage and protection of thing data over time: http: //www.linkedin.com/groups/Internet-Things-Storage-protection-thing-3981538.S.5851659153147191299?qid=967f3274-65c0-425b-9097-7c296c526f6f&trk=groups_most_recent-0-b-ttl&goback=.gmr_3981538
March 19: Privacy and big data? Addressing the tricky contours of in-store privacy: http: //bit.ly/OBrMRH
March 20: Open data? The standards imperative: http: //www.linkedin.com/groups/Open-data-standards-imperative-3981538.S.5852405297074692097?view=&gid=3981538&type=member&item=5852405297074692097#commentID_null
March 21: Big BI? NoSQL's role in decision-support applications: http: //www.linkedin.com/groups/Big-BI-NoSQLs-role-in-35222.S.5852718851254411268?view=&gid=35222&type=member&item=5852718851254411268#commentID_null
March 24: Big-data hardcore use cases? Prioritizing the potentials when so many present themselves: http: //www.linkedin.com/groups/Bigdata-hardcore-use-cases-Prioritizing-3981538.S.5853835694631313410?view=&gid=3981538&type=member&item=5853835694631313410#commentID_null
March 25: Privacy and big data? The dangers of misplaced faith in tactical and technological quick-fixes: http: //bit.ly/ONqcfV
March 26: Graph analysis? Apache Spark begins to spark convergence of Hadoop, streaming, in-memory, & graph analysis:
March 27: Social sentiment? Our tweets implicitly encode our personalities: http: //www.linkedin.com/groups/Social-sentiment-Our-tweets-implicitly-3981538.S.5853844881448910848?view=&gid=3981538&type=member&item=5853844881448910848#commentID_null
March 28: Big data in production? Smoothing the workflows necessary for production-grade data science: http: //www.linkedin.com/groups/Big-data-in-production-Smoothing-35222.S.5853845085216587778?qid=1f595d4e-3b8b-406e-8a5c-9e12632d1eef&trk=groups_most_recent-0-b-ttl&goback=.gmr_35222
March 31: Healthcare analytics? Using advanced image analytics to spot hidden cancer patterns: https: //www.linkedin.com/groups/Healthcare-analytics-Using-advanced-image-3981538.S.5856360507702800386?trk=groups%2Finclude%2Fitem_snippet-0-b-ttl
April 1: Data journalism?: http: //bit.ly/PdIoQe
April 2: Peta-governance? Where trustworthiness is concerned, the proof is in the data-governance process: http: //bit.ly/1gnhICh
April 3: Prediction markets? Fostering open marketplaces for models and modelers: http: //bit.ly/1fOtjLb
April 4: Moneyball?: http: //bit.ly/1oxdG4l
April 7: Hadoop uber-alles? Hadoop beginning to stare newer big-data approaches in the face: http: //bit.ly/OrJMO3
April 8: Open data? Climate data should move as freely as the atmosphere that cloaks our warming planet: http: //linkd.in/1lNmWiB
April 9: Machine learning? When data scientists struggle to keep their foothold in ground truth : http: //linkd.in/1gHmoTC
April 10: Big Science? The rigid regimen of reproducible computational findings: http: //bit.ly/1lSDZQq
April 11: Big identity? The big data challenges of identity management in the Internet of Things : http: //bit.ly/1hy1IDQ
April 14: Machine learning? Automating log-data analysis through unsupervised and reinforcement learning algorithms: http: //bit.ly/RhVsVY
April 15: Internet of Things? The binocular vision and opposable thumb of cognitive computing : http: //bit.ly/1qDEqh5
April 16: Context accumulation? Grounding cognitive confidence in the probabilistic fabric of the real world : http: //linkd.in/1gAq6zk
May 19: Real-world experiments? The tricky business of A/B testing: http: //bit.ly/1hXgLCk
May 20: Storage optimization? Software-defined storage driving the demise of rip-and-replace: http: //linkd.in/TpNwDe
May 21: Experience optimization? Drilling into the messy gusher of web analytics data: http: //linkd.in/1tjgaSL
May 22: Machine learning? A melting pot for today's leading-edge advanced analytics: http: //linkd.in/1lVjajx
May 23: Sexy statistics? Big-data's correlations and cautionary tales: http: //bit.ly/1n9H3a0
May 27: Big-data discovery? The power of Bayesian search: http: //linkd.in/1kk1gti
May 28: Open data? The democratization of standardized data in civic governance: http: //linkd.in/1k0AVkK
May 29: Big Data's optimal deployment model? Deeply embedded in the cloud: http: //linkd.in/1iv0BAA
May 30: Machine learning? Deep learning to filter text for the known, unknown, and unknowable unknowns: http: //bit.ly/TZImxW
June 2: Engaging customer as individual? Cognitive computing, conversational engagement, & customer confidence: http: //bit.ly/1gYy0Z2
June 3: Internet of Things? Digitally fingerprinting the trusted endpoint: http: //bit.ly/1kto6yj
June 4: Big identity? Using big data analytics to identify & shut down slippery cyberscammers: http: //linkd.in/1oVH8At
June 5: Experience optimization? Internet of Things, next best actions, & the downside of the technological cocoon: http: //linkd.in/1njMJOf
June 6: Healthcare analytics? Remaining skeptical about the data science behind dietary research: http: //linkd.in/1mjb6Ij
June 9: Open data? The promise and privacy implications of open access to energy data: http: //linkd.in/1l09xOl
June 10: Big data's optimal deployment model? The niche role for graph databases in hybrid architectures: http: //linkd.in/1jitJLB
June 11: Quantified self?: http: //linkd.in/1uWGaV1
June 12: Information economics? The shifting economic role of official government statistics in the era of social listening: http: //linkd.in/1lc2guX
June 13: Hadoop uber-alles? Implementing an extensible library of statistical algorithms & models to serve big-data developers: http: //linkd.in/SSHD0u
June 16: Storage optimization? Data deduplication improves cuts IT costs, boosts data scientist productivity, & bolsters data quality: http: //linkd.in/1lHxn6r
June 17: Engaging customer as individual? Mapping the customer journey through the seemingly irrational : http: //bit.ly/1uAr99c
June 18: Data-scientist skillsets? The delicate art of project prioritization and triage: http: //bit.ly/1nP1CZ3
June 19: Healthcare analytics? Health data brokers and the arms race in intrusive target marketing: http: //bit.ly/1qheM1T
June 20: Big identity? Nonintrusive strong authentication through never-ending behavioral fingerprinting: http: //bit.ly/SXo6M6
June 23: Big Media? The narrative power of video content analytics: http: //bit.ly/1qEqlCz
June 24: Quantified self? The social physics of a quantified society: http: //bit.ly/1mize1W
June 25: Open data? The front line of grass-roots consumer protection: http: //bit.ly/Vn738i
June 26: Recommendation engines? Fancy math to illuminate stabs in the dark: http: //bit.ly/1qeoiFz
June 27: Data journalism? Using real-time analytics to identify who scooped whom online: http: //bit.ly/1o91jsg
June 30: Internet of things? The potential for sensor-driven hyperlocalized weather forecasting: http: //bit.ly/1lJ0vuv
July 1: Healthcare analytics? Big data as a factor in life-or-death decisions: http: //bit.ly/1o3xtng
July 2: Ambient analytics? The advent of big-data wearables and "unaware-ables": http: //bit.ly/1rWYRG5
July 3: Engaging customer as individual? Parrying the double-edge of customer sarcasm: http: //bit.ly/1t0PJVo
July 7: Moneyball? Pitcrew analytics and within-race data-driven decision support: http: //bit.ly/VSlh17
July 8: Big Media? The shifting art of audience measurement in the era of all-online media: http: //bit.ly/1n3tg0G
July 9: Big-data development? The agile imperative and the risk of data scientists "boiling the lake": http: //bit.ly/1qjs39b
July 10: All in memory? Scaling in-memory infrastructures up and out : http: //bit.ly/1mCsko8
July 11: Healthcare analytics? Keeping patients from straying off the path to recovery: http: //bit.ly/1nekOvo
July 14: Real-world experiments? Dissecting the Facebook controversy over mood manipulation: http: //bit.ly/1ygxTgi
July 15: Security of big data? The imperative and issues surrounding whole-population security analytics: http: //bit.ly/1n6atb0
July 16: Data-scientist skillsets? Data science in the new product development repertoire: http: //bit.ly/1oYclAP
July 17: Open data? Open correlations in the common cause: http: //bit.ly/1zMiW77
July 18: Analytic acceleration in the cloud? The new era of big data as a service: http: //linkd.in/1oZV2Q4
July 21: Recommendation engines? Predicting the exquisitely nonlinear shifts of customer taste: http: //bit.ly/1nZKmwM
July 22: Big-data ethics?: http: //bit.ly/1k9PBiJ
July 23: All in memory? Transitional patterns on the road to the "all-and-only-in-memory cloud": http: //linkd.in/1tzrbzf
July 24: Security of big data? The self-protecting big-data honeypot: http: //linkd.in/1kXnoGI
July 25: Advanced analytics?: http: //bit.ly/1nohOld
July 28: Internet of Things? The walls have ears, eyes, noses, and every other sense organ: http: //bit.ly/1zlUk4e
July 29: Data-scientist skillsets? A polymathic grasp of myriad disciplines and applications: http: //bit.ly/1poazcr
July 30: Big data's optimal deployment model? The core principles of scalability: http: //bit.ly/1qKFyDA
July 31: Peta-governance? The challenges of probabilistic data-matching in the Internet of Things: http: //bit.ly/1uKFF3s
August 1: Open data? Monetizing your existence as a crowdsourced data scientist: http: //bit.ly/1nRtSM0
August 4: Big data on the move? The emergence of the mobile back-end as a service: http: //bit.ly/XxKrCK
August 5: Geospatial analytics? Ammunition against pestilence: http: //linkd.in/1oaviS4
August 6: Decision automation? Retraining and restraining the long-data arm of the law: http: //bit.ly/1oc065N
August 7: Advanced analytics? Pick an algorithm, any algorithm: http: //bit.ly/1lDvAfB
August 8: Conversation optimization? The delicate dance of accessorizing your lifestyle online: http: //bit.ly/1kO3xzf
August 11: Cognitive computing? Wrestling the myriad definitions down to manageable size: http: //bit.ly/1pKNXTN
August 12: Big Science? The open-sourcing of scientific inquiry throughout the world: http: //linkd.in/XeRtwh
August 13: Data-scientist skillsets? Articulating the advantages of analytics over intuition: http: //bit.ly/1p5hCaY
August 14: Healthcare analytics? Wearable cognition-assist analytics as the new prosthetics: http: //linkd.in/1BgJNZT
August 15: Big Science? The staggering resource requirements of computational megascience: http: //bit.ly/1oOCyhT
August 18: Service-oriented analytics? Big-data analytics consulting as a service: http: //linkd.in/1kO6Ups
August 19: Big-data hardcore use cases? Assessing when bigger data truly is better: http: //bit.ly/1p9uZr3
August 20: Data-scientist skillsets? Girding yourself for the commoditization of your profession: http: //bit.ly/VFgajK
August 21: Advanced analytics? The converged and accelerated machine learning of ensemble methods: http: //linkd.in/VGlS5v
August 22: Data-scientist skillsets? Teaming within the open expertise communities: http: //bit.ly/1oYqG2K
August 25: Data-scientist skillsets? Introducing evidence-driven computational approaches into the public-policy arena: http: //bit.ly/XLRrwi
August 26: Meaty metadata? The analytic potency of the ontology: http: //bit.ly/1qnBQxa
August 27: Hadoop uber-alles? Dredging the "data lake" metaphor down to its muddy bottom: http: //bit.ly/VQzURR
August 28: Machine learning? Distinguishing deep learning from its opposite: http: //bit.ly/1vSKyED
August 29: Big-data-driven TV experience? Serving both active and passive audiences equally: http: //bit.ly/1qmLr6y
September 2: Machine learning? Delving into the depths of deep learning: http: //linkd.in/1lG2Loq
September 3: Advanced visualization? The analytical value of data-provenance tracking within big-data visualizations: http: //bit.ly/1r0Zmg0
September 4: Healthcare analytics? Unstructured analytics powering pandemic early-warning systems: http: //bit.ly/1xfhgEo
September 5: Data journalism? Deep learning threatens to deep-six journalism's faith in the factuality of the photograph: http: //bit.ly/YhllJ2
September 8: Decision scientists? Data scientists challenged to sway the hearts and minds of public policymakers: http: //bit.ly/1lN8iZY
September 9: Big Science? The insight-acceleration potential of elastic storage clouds: http: //bit.ly/WDtINe
September 10: Sexy statistics? The tricky serendipity of data-lake fishing expeditions: http: //linkd.in/1qEIhwA
September 11: Big data's optimal deployment model? "Fog" clouds optimized for Internet of Things analytics: http: //bit.ly/1AC9oJy
September 12: Big-data single version of the truth? The practical limits of clue-googling: http: //bit.ly/1xSUS4i
September 15: Big Science? The analytical challenges that frustrate use of data science in global studies: http: //bit.ly/1qEaJiZ
September 16: Internet of Things? Revisiting Metcalfe's Law in the era of everything networking: http: //bit.ly/1BIMlPQ
September 17: Recommendation engines? Black art of benchmarking against the past and pending: http: //linkd.in/1u0I9da
September 18: Advanced analytics? Please avoid interpreting "advanced" as "hipper than thou": http: //linkd.in/1s8qyQp
September 19: Healthcare analytics? Mining hospital data for nonobvious infection and contagion patterns within their facilities: http: //bit.ly/1u6eiQz
September 22: Peta-governance? Timing means everything for establishing accountability: http: //bit.ly/1DCx3xS
September 23: Advanced analytics? Monte Carlo simulation when the past is an uncertain prologue to prediction: http: //linkd.in/1ugVga7
September 24: Cognitive computing? Acing the Turing test is the least of it : http: //linkd.in/1uGk6g6
September 25: Data-scientist skillsets? Immersion in probabilistic programming languages: http: //linkd.in/1peyKrC
September 26: Open data? Equitably distributing data-science brainpower among the haves and have-nots: http: //bit.ly/1t1VtZf
September 29: Stream computing? Converging in-motion, in-memory, and in-process analytics: http: //bit.ly/1qO34sH
September 30: Engaging customer as individual? The blurry boundary between engagement, influence, and manipulation: http: //bit.ly/1ByegQp
October 1: Healthcare analytics? Big data's "4 Vs" drive advances in computational bioinformatics: http: //linkd.in/1pqghIC
October 2: Open data? The emergence of the urban data scientist: http: //linkd.in/1nQFfWP
October 3: Big Media? Video and image analytics for extracting real-time actionable insights: http: //bit.ly/1sReRy5
October 6: Quantified self? Healthy self-monitoring vs. narcissistic self-obsession: http: //bit.ly/1oJNWgx
October 7: Machine data analytics? Man & machine data becoming indistinguishable: http: //bit.ly/1uwMcwL
October 8: Hadoop uber-alles? The challenge of staying current on an ever-shifting technology landscape: http: //linkd.in/ZsPV2q
October 9: Talent analytics?: http: //bit.ly/1oU32Af
October 10: Big-data discovery? Shining analytical light deeply into dark data: http: //bit.ly/1vbigrC
October 13: Smarter cities?: http: //bit.ly/1to5je1
October 14: Hadoop uber-alles? Data modeling will endure and you'll still need to pay the ETL piper somewhere sometime: http: //bit.ly/1v8dBW6
October 15: Big identity? Facial recognition, deep learning, and the end of anonymity in public spaces: http: //bit.ly/11nclmT
October 16: Big-data ethics? The difference between targeted segmentation and discriminatory profiling: http: //bit.ly/1u9Yyal
October 17: Engaging customer as individual? Quantification of student performance in the new education industry order: http: //bit.ly/1sX1JWr
October 20: Workload-optimized systems? Pushing MapReduce's efficiency envelope: http: //bit.ly/ZCzMr1
October 21: Machine learning? Need a decision tree for data scientists to choose among machine-learning statistical frameworks: http: //bit.ly/1whTG6m
October 22: Business process optimization? The limits of disintermediation in the cognitive era: http: //bit.ly/1t4NhM5
October 23: Talent analytics? Non-obvious patterns of who knows what, does what, and gets what done: http: //bit.ly/1rlTDSK
October 24: Machine learning? An evolving grab-bag of magic tricks that still lacks a unifying framework: http: //linkd.in/1DHG4EX
October 27: Big data on the move? The evolving data fabric of the travel experience: http: //linkd.in/1txHhga
October 28: Marketing campaign optimization? Continuous campaigning for mass-market blockbusters: http: //bit.ly/1tePe8M
October 29: Data-scientist skillsets? Getting up to speed on machine learning: http: //bit.ly/1nPZJP6
October 30: Quantified self? The delicious demon of self-awareness: http: //linkd.in/13ejbvR
October 31: Chief Data Officer?: http: //bit.ly/1sG5oD5
November 3: Data monetization? Nabbing the counterfeiters behind fake online reviews: http: //bit.ly/1wXVX85
November 4: Geospatial analytics? Predictive risk mitigation and retrofitting for disaster preparedness: http: //linkd.in/1x1KCnq
November 5: Cognitive computing? Programming the artificial mind: http: //linkd.in/1ut41z1
November 6: Internet of Things? Behavioral analytics in the era of wearables: http: //linkd.in/10ygR1e
November 7: Peta-governance? The potential of graph analytics in master data management: http: //bit.ly/1orNVD8
November 10: Big-data single version of the truth? Curation vs. stewardship in the era of multistructured data: http: //bit.ly/1ATkrnc
November 11: Prescriptive analytics? Massive-scale prediction and real-time interdiction in the fight against cybercrime: http: //linkd.in/1uZFIc9
November 12: Big Media? Standards-based object-storage platforms are key to streaming media: http: //bit.ly/1wTa7aW
November 13: Transactional analytics? Channels cull continuous customer expertise from cognitive cloud: http: //linkd.in/1wX9GMX
November 14: Analytic acceleration in the cloud? The next evolution in self-service business analytics: http: //linkd.in/1xo34Zb
November 17: Modeling automation? Machine learning shapes the material world: http: //bit.ly/1u1nXlL
November 18: Workload-optimized systems? The challenges of scaling to Facebookian proportions: http: //bit.ly/1t1B4UU
November 19: Social sentiment as valuable market intelligence? The utility or futility of weeding out bogus online reviews: http: //bit.ly/1xpfY89
November 20: Influence analytics?: http: //bit.ly/1Hqe77A
November 21: Big Media? Sentiment data may suffer as social networks evolve into broadcasting media platforms: http: //bit.ly/1xGttl6
December 1: Cognitive computing? Fathoming photos at algorithmic speed: http: //bit.ly/12jWzt1
December 2: Healthcare analytics? The possibility of appliance-enabled whole-body self-diagnosis: http: //bit.ly/1ybYi1v
December 3: Healthcare analytics? The electrified “third rail” of deep psychographic customer engagement: http: //bit.ly/1vnhuXS
December 4: Experience optimization? Assessing big data’s role in the grand scheme of human happiness: http: //linkd.in/1FSoUFF
December 5: Internet of Things? IoT insights that can best be revealed through graph analysis: http: //linkd.in/1vn1HU4
December 8: Crowdsourcing Big Data creativity? Intersection of interest graphs with the Internet of Things: http: //bit.ly/1yt32Qx
December 9: Geospatial analytics? Managing the land more effectively to protect the rainforest: http: //linkd.in/1yLcZYt
December 10: Smarter planet? Remote sensing the globe from every possible viewpoint: http: //bit.ly/1AevZwt
December 11: Marketing campaign optimization? Using pervasive analytics to drive a sustainable food chain: http: //bit.ly/1zb5b15
December 12: Smarter cities? The infrastructure silo-busting imperative: http: //linkd.in/1zYrBlv
December 15: Advanced visualization? Seeing the spaces where numbers and words seamlessly join: http: //bit.ly/1wzCZ6Y
December 16: Business process optimization? The statistics that shape manufacturing: http: //bit.ly/133aO65
December 17: Cognitive computing? Undecidable problems and the limits of algorithmic cognition: http: //bit.ly/1AEZSGw
December 18: Cognitive computing? Learning through associational population of sparse experiential matrices with fresh clues: http: //linkd.in/1AiM1I7
December 19: Social sentiment as valuable market intelligence? Black swans and the predictive challenge surrounding concocted controversy: http: //bit.ly/1zEuWam