Friday, December 19, 2014

Kobielus' Quick-Hits in 2014

January 17:  Big Science? Overreliance on big data can stunt development of scientific rigor: 
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 24:  Meaty metadata? Data variety leads to metadata viscosity:  http:  //bit.ly/1hRVEmI
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 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 11Data-scientist skillsets? Psychological insights key to modeling customer causationhttp:  //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 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 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 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 17:  Recommendation engines? Analytics grooving with whatever grooves groove you:  http:  //bit.ly/1hrL30v
March 19:  Privacy and big data? Addressing the tricky contours of in-store privacy:  http:  //bit.ly/OBrMRH
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 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 22Data-scientist skillsets? Teaming within the open expertise communitieshttp:  //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 10Smarter planet? Remote sensing the globe from every possible viewpointhttp:  //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

Thursday, December 18, 2014

Kobielus big-data evangelization blogging output in 2014 (not including LinkedIn quick-hits, presentations, & tweets)

December 18, 2014

December 11, 2014

Peeling back the layers of the smarter city

The Challenges of Master Data Management in the Internet of Things

Optimized object storage is key to streaming media

Big Data Ethics for Targeted Segmentation

Cognitive computing: Programming the artificial mind

November 20, 2014

Chief data officer: My mixed and nuanced musings on the need for one

November 13, 2014

Behavorial analytics in the era of wearables


Cognitive computing as a wearable prosthetic


Five Ways To Move Your Big Data into the Cloud

Bringing cloud-based modernization to data warehousing and analytics

October 28, 2014

Big Data Is Not the Death Knell of ETL

What's keeping data science from playing a more central role in public policy?

October 23, 2014

Self-Service Analytics, Data Warehousing, and Information Management in the Cloud

Collaborations and correlations in the common cause

Distributing data science brainpower more equitably among the haves and have-nots

Governance, Stewardship, and Quality of Temporal Data in a Data Warehousing Context

Converging in-motion and in-memory analytics

Using analytics to help hospitals avoid inadvertently sickening patients and their caregivers

October 2, 2014

The Challenges of Deploying Big Data Analytics to the Cloud

Data science's limitations in addressing global warming

September 25, 2014

September 19, 2014

IBM Watson: Core of the cognitive revolution

September 18, 2014

Immunizing your business against toxic customer relationships

September 11, 2014
Who's afraid of the big (data) bad wolf?

When big data is truly better

The analytic potency of the ontology

Raising real-time transaction and analytic processing to the next power

September 2, 2014

Consolidating and migrating to an in-memory analytics cloud

August 27, 2014

Doing something about the weather

August 21, 2014

The Larger Stakes Behind Big Data Ethics

Explore New Frontiers in Business Analytics

Using real-time analytics to identify who's scooping whom in online journalism

August 14, 2014


August 7, 2014

Algorithms are not magic

Empowering athletes with real-time, data-driven decision support

July 31, 2014

The Power of Behavioral Fingerprinting

Can a machine detect sarcasm? Yeah, right

Real-time healthcare compliance analytics can keep patients alive and well

July 24, 2014

Big algorithm libraries breathe life into big data

Real-world experiments and the Facebook controversy over mood manipulation

July 17, 2014

Big data as a factor in life-or-death decisions

July 10, 2014

Transforming the agile data warehouse in the age of the in-memory cloud

July 9, 2014
James Kobielus: Cualquiera se beneficia del big data

Streaming media and narrative power of video content analytics

IBM Watson and the power of conversation in the cognitive fabric

June 26, 2014
Data De-Duplication Should Be the Heart of all Big Data Strategies

What's machine learning? It depends on who you ask

The delicate art of data science project prioritization and triage

June 19, 2014

Big data log analysis thrives on machine learning


The Ground Truth in Agile Machine Learning

The democracy of open data

Scientists beginning to tap the research potential of the quantified self

June 12, 2014

Hadoop, whither goest thou?

Too big, too small, or just right? Balancing your social connections


Grounding cognitive computing in probabilistic data analytics



Practical Data Science and the Tricky Business of A/B Testing

Evolving the binocular vision and opposable thumbs of cognitive computing

May 29, 2014

Whipping Web Analytics into Shape to Glimpse True Customer Experience

In Data Science, Take Nothing on Faith

Big data's bogus correlations

May 22, 2014

IBM Data Magazine: Its Value and Its Vision

Don’t Understaff and Overstretch Your Analytics Development Team


Never put everything in one database basket, even if it’s Hadoop

Open climate data will focus humanity on solutions to global warming

May 15, 2014

Sports Teams: Smack That Ol’ Moneyball Right Out of the Park

Hidden Biases That May Cloud Cognitive Computing

Using advanced image analytics to spot hidden cancer patterns

May 9, 2014

Data confidence: The proof's in the process

May 1, 2014

Hadoop is Beginning to Stare Newer Big Data Approaches in the Face


April 28, 2014

Nurturing open marketplaces for predictive models and modeling expertise

April 24, 2014

Moneyball is the true game-changing application of data analytics

April 17, 2014

The embryonic days of the data journalism industry are upon us


April 10, 2014

IBM big data roundtable: The transformative power of big data


April 4, 2014

Big data powers the practical know-it-all in us all

April 3, 2014
Extract maximum insights before you purge your data

Rules of thumb for identifying and prioritizing big data applications

The Irreducibly Human Center of Streaming Music Algorithmics

Saving the Planet

Plugging a lean, mean big-data-analyzing machine into manufacturing

March 21, 2014

Using big data to tune the fusion of human physiology and machine physics

March 13, 2014
Detecting the Signs of Drama and Drift in Customer Loyalty

Caveat on use of the Internet of Things in behavioral analytics


March 6, 2014

The exabyte era is rapidly streaming our way

The cloud now has a BLU lining and BLU has a cool hub


February 28, 2014

Machine learning floats all boats on big data's ocean

Mobile data traces the contours of urban experience


Mitigating the Disruption of Real-World Experiments

Data scientists need psychological insights to tune customer analytics

February 20, 2014

Big data drives the daisy chain of value in today's economy


February 13, 2014

Pay Your Customers What They’re Worth to You

Customer experience data is too important to foul with shoddy governance


February 6, 2014

IBM Patterns and Platforms for Business Intelligence (BI): Choosing What’s Best for You



When and When Not to Have Faith in Statistical Models – Part 2

Cognitive computing can take the semantic Web to the next level

Autonomic planet: Distributed intelligence for a self-healing ecosystem

When and When Not to Have Faith in Statistical Models – Part 1

Big data overkill can stunt scientific rigor


January 23, 2014

The Beauty Metric: Choosing the Best-Fit Advanced Analytic Algorithms

Next best expert: Collaboration of people and machines on big data and analytics

January 16, 2014

Log data is pivotal to analytics on Internet of Things

Koby's predictions for the Internet of Things in 2014 and beyond

January 10, 2014

Foretelling 2014 Trends In Big Data, Hadoop, Data Science & More

What Koby's tea leaves foretell for big data in 2014


January 2, 2014