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jerryking : data_mining   65

To Survive in Tough Times, Restaurants Turn to Data-Mining
AUG. 25, 2017 | The New York Times | By KAREN STABINER.

“Silicon Valley looks at inefficiencies in the world, and they aim to disrupt the food space,” said Erik Oberholtzer, a founder and the chief executive of Tender Greens, a quick-service chain based in Los Angeles that is using data to guide its East Coast expansion.
data  data_mining  hard_times  inefficiencies  restaurants 
august 2017 by jerryking
Prepare for a New Supercycle of Innovation - WSJ
By John Michaelson
May 9, 2017

Things are about to change. Consider information technology. Today’s enterprise IT systems are built on platforms dating from the 1970s to the 1990s. These systems are now horrendously expensive to operate, prone to catastrophic crashes, and unable to ensure data security. The cloud only made this worse by increasing complexity.

Corporate CEOs complain that they are unable to get the data they need. These rickety systems cannot easily accommodate data mining and artificial intelligence. Evidence of their deficiencies is seen daily. The New York Stock Exchange stops trading for hours. Yahoo acknowledges the compromise of one billion user accounts. Airline reservation systems go down repeatedly. The pain level for users is becoming intolerable.

Each decade for the past 60 years, we have seen a thousand-fold increase in world-wide processing power, bandwidth and storage. At the same time, costs have fallen by a factor of 10,000. Advances in these platforms, in themselves, do not produce innovation. But they facilitate the development and deployment of entirely new applications that take advantage of these advances. [jk: The Republican intellectual George F. Gilder taught us that we should husband resources that are scarce and costly, but can waste resources that are abundant and cheap] Amazing new applications are almost never predictable. They come from human creativity (jk: human ingenuity). That is one reason they almost never come from incumbent companies. But once barriers to innovation are lowered, new applications follow.
10x  artificial_intelligence  CEOs  creativity  cyber_security  data_mining  economic_downturn  flash_crashes  George_Gilder  Gilder's  Law  innovation  history  human_ingenuity  incumbents  IT  legacy_tech  Moore's_Law  NYSE 
may 2017 by jerryking
At BlackRock, a Wall Street Rock Star’s $5 Trillion Comeback - The New York Times
SEPT. 15, 2016 | NYT | By LANDON THOMAS Jr.

(1) Laurence Fink: “If you think you know everything about our business, you are kidding yourself,” he said. “The biggest question we have to answer is: ‘Are we developing the right leaders?’” “Are you,” he asked, “prepared to be one of those leaders?”

(2) BlackRock was thriving because of its focus on low-risk, low-cost funds and the all-seeing wonders of Aladdin. BlackRock sees the future of finance as being rules-based, data-driven, systematic investment styles such as exchange-traded funds, which track a variety of stock and bond indexes or adhere to a set of financial rules. Fink believes that his algorithmic driven style will, over time, grow faster than the costlier “active investing” model in which individuals, not algorithms, make stock, bond and asset allocation decisions.

Most money management firms highlight their investment returns first, and risk controls second. BlackRock has taken a reverse approach: It believes that risk analysis, such as gauging how a security will trade if interest rates go up or down, improves investment results.

(3) BlackRock, along with central banks, sovereign wealth funds — have become the new arbiters of "flow.“ It is not about the flow of securities anymore, it is about the flow of information and indications of interest.”

(4) Asset Liability and Debt and Derivatives Investment Network (Aladdin), is BlackRock's big data-mining, risk-mitigation platform/framework. Aladdin is a network of code, trades, chat, algorithms and predictive models that on any given day can highlight vulnerabilities and opportunities connected to the trillions that BlackRock firm tracks — including the portion which belongs to outside firms that pay BlackRock a fee to have access to the platform. Aladdin stress-tests how securities will respond to certain situations (e.g. a sudden rise in interest rates or what happens in the event of a political surprise, like Donald J. Trump being elected president.)

In San Francisco, a team of equity analysts deploys data analysis to study the language that CEOs use during an earnings call. Unusually bearish this quarter, compared with last? If so, maybe the stock is a sell. “We have more information than anyone,” Mr. Fink said.
systematic_approaches  ETFs  Wall_Street  BlackRock  Laurence_Fink  asset_management  traders  complacency  future  finance  Aladdin  risk-management  financiers  financial_services  central_banks  money_management  information_flows  volatility  economic_downturn  liquidity  bonds  platforms  frameworks  stress-tests  monitoring  CEOs  succession  risk-analysis  leadership  order_management_system  sovereign_wealth_funds  market_intelligence  intentionality  data_mining  collective_intelligence  risk-mitigation  rules-based  risks  asset_values  scaling  scenario-planning  databases 
september 2016 by jerryking
The lost art of political persuasion - The Globe and Mail
KONRAD YAKABUSKI
The Globe and Mail
Published Saturday, Apr. 25 2015

Talking points are hardly a 21st century political innovation. But they have so crowded out every other form of discourse that politics is now utterly devoid of honesty, unless it’s the result of human error. The candidates are still human, we think, though the techies now running campaigns are no doubt working on ways to remove that bug from their programs.

Intuition, ideas and passion used to matter in politics. Now, data analytics aims to turn all politicians into robots, programmed to deliver a script that has been scientifically tested...The data analysts have algorithms that tell them just what words resonate with just what voters and will coax them to donate, volunteer and vote.

Politics is no longer about the art of persuasion or about having an honest debate about what’s best for your country, province or city. It’s about microtargeting individuals who’ve already demonstrated by their Facebook posts or responses to telephone surveys that they are suggestible. Voters are data points to be manipulated, not citizens to be cultivated....Campaign strategists euphemistically refer to this data collection and microtargeting as “grassroots engagement” or “having one-on-one conversations” with voters....The data analysts on the 2012 Obama campaign came up with “scores” for each voter in its database, or what author Sasha Issenberg called “a new political currency that predicted the behaviour of individual humans.
Konrad_Yakabuski  persuasion  middle_class  politicians  massive_data_sets  political_campaigns  data_scientists  data_driven  data_mining  microtargeting  behavioural_targeting  politics  data  analytics  Campaign_2012 
april 2015 by jerryking
It’s a Whole New Data Game for Business - WSJ
Feb. 9, 2015 | WSJ |

opportunistic data collection is leading to entirely new kinds of data that aren’t well suited to the existing statistical and data-mining methodologies. So point number one is that you need to think hard about the questions that you have and about the way that the data were collected and build new statistical tools to answer those questions. Don’t expect the existing software package that you have is going to give you the tools you need....Point number two is having to deal with distributed data....What do you do when the data that you want to analyze are actually in different places?

There’s lots of clever solutions for doing that. But at some point, the volume of data’s going to outstrip the ability to do that. You’re forced to think about how you might, for example, reduce those data sets, so that they’re easier to move.
data  data_collection  datasets  data_mining  massive_data_sets  distributed_data  haystacks  questions  tools  unstructured_data 
february 2015 by jerryking
Data-mining retailers prove it’s hip to use Square - The Globe and Mail
SHANE DINGMAN - TECHNOLOGY EDITOR
The Globe and Mail
Published Thursday, Aug. 21 2014

...Forrester Research has predicted the global mobile payments market could be worth $90-billion by 2017. But Square makes very little revenue per purchase, and has long acknowledged that customer data was the real value centre in its business. The convenience and “wow factor” of turning a smartphone into a cash register is appealing to sellers, but for them, too, Square’s data tools let them identify new or returning customers, average spend and those critical customer preferences.
data  data_driven  data_mining  retailers  Square  customer_insights  payments 
august 2014 by jerryking
Twitter Acquires Gnip, Bringing a Valuable Data Service In-House - NYTimes.com - NYTimes.com
April 15, 2014 | NYT | By ASHWIN SESHAGIRI.

In 2010, Gnip was the first company to work with Twitter to gain access to the social network’s so-called fire hose, which contains all publicly available tweets since 2006. Brands, advertisers and, recently, academics could use that stream of data to analyze and parse activity on the social network....Last year, Apple acquired Topsy Labs, a similar provider of data of Twitter activity. The terms of that deal were also not disclosed, though The Wall Street Journal, citing people familiar with the matter, estimated the deal to be worth more than $200 million.

“We believe Gnip has only begun to scratch the surface,” Jana Messerschmidt, Twitter’s vice president of global business development and platform, wrote in a blog post announcing the deal. “Together we plan to offer more sophisticated data sets and better data enrichments, so that even more developers and businesses big and small around the world can drive innovation using the unique content that is shared on Twitter.”
Twitter  Gnip  massive_data_sets  mergers_&_acquisitions  data  data_mining  sentiment_analysis  social_media  social_data 
april 2014 by jerryking
New software allows insurers to track driving habits and personalize premiums - The Globe and Mail
OMAR EL AKKAD

The Globe and Mail

Published Monday, Aug. 19 2013,

The ability to monitor and adapt to the behaviour of individual customers, for example, was part of the rationale for last month’s announcement by Loblaw Cos. Ltd. that it will acquire Shoppers Drug Mart Corp. for $12.4-billion. Shoppers’ Optimum loyalty program will give Loblaw purchasing information on some 10 million customers.
Omar_el_Akkad  telematics  insurance  personalization  massive_data_sets  pattern_recognition  data_mining  sensors  meat_space  SAP  Shoppers  loyalty_management  Loblaws 
january 2014 by jerryking
Big Data Is A Big Factor In 2012                     
Mar 30 2012 | Campaigns & Elections | By Brett Bell.

But as the social media industry continues to mature, so too does the level of sophistication in which campaigns and organizations apply social media tools and techniques. Campaigns are moving away from merely having a social media presence to leveraging social activity to inform and fuel campaign machines....For their part, the Obama campaign is focusing significant attention and resources towards data management. In a series of telling job postings this summer, Obama For America put out the call for data mining and predictive modeling analysts, appealing to the startup community, private sector and data managers within their own Party. One particular job description stated that successful candidates would assist in developing statistical and predictive models to assist in fundraising, digital media and other areas of the campaign....the Obama For America Campaign 2012 launched a Facebook application which requested permission to access your location, name, picture, gender, list of friends and other information that would be valuable to the campaign team
Campaign_2012  massive_data_sets  political_campaigns  data_scientists  data_driven  data_mining  microtargeting  behavioural_targeting  data_management 
january 2014 by jerryking
Palantir Reloads for the Corporation - NYTimes.com
December 5, 2013, 10:00 am Comment
Palantir Reloads for the Corporation
By QUENTIN HARDY

Palantir Technologies is a big data software company whose roots in government security mask a growing corporate presence. It is also getting a larger war chest to go with that growth....The company’s initial customers included several United States defense and intelligence agencies. But today, more than 60 percent of its revenue is from commercial sources, according to the Palantir executive, who spoke on the condition on anonymity.

While most big data companies create databases that gather large and diverse information sources, then apply pattern-matching software to see if something interesting pops up, Palantir’s technology tries to encode a human element. It has worked on augmenting the way humans in a given field parse information by studying specialists in such areas as fraud spotting, or doctors who isolate outbreaks of food poisoning. The software then augments those human pattern-finding skills.

While this has proved effective for finding insurgent bomb makers and missing children, it also seems to work in finance, health care and other industries.
Palantir  data  data_mining  artificial_intelligence  large_companies  massive_data_sets  security_&_intelligence  pattern_recognition  information_sources 
december 2013 by jerryking
Bell planning to use customers' data to target ads - The Globe and Mail
Oct. 22 2013 | The Globe and Mail | SUSAN KRASHINSKY.

Bell Canada is planning to use information about its customers’ accounts and Internet use to target ads to them.

The information Bell will be using includes Internet activity from both mobile devices and computers, including Web pages customers have visited and search terms they have entered; customers’ location; use of apps and other device features; television viewing habits; and “calling patterns.” Account information shared will include product use including type of device, payment patterns, language preferences, postal codes, and demographic information.
Susan_Krashinsky  Bell_Canada  data  data_driven  data_mining  demographic_information  massive_data_sets  target_marketing  behavioural_targeting  online_behaviour  metadata 
november 2013 by jerryking
Start-Ups Are Mining Hyperlocal Information for Global Insights - NYTimes.com
November 10, 2013 | WSJ | By QUENTIN HARDY

By analyzing the photos of prices and the placement of everyday items like piles of tomatoes and bottles of shampoo and matching that to other data, Premise is building a real-time inflation index to sell to companies and Wall Street traders, who are hungry for insightful data.... Collecting data from all sorts of odd places and analyzing it much faster than was possible even a couple of years ago has become one of the hottest areas of the technology industry. The idea is simple: With all that processing power and a little creativity, researchers should be able to find novel patterns and relationships among different kinds of information.

For the last few years, insiders have been calling this sort of analysis Big Data. Now Big Data is evolving, becoming more “hyper” and including all sorts of sources. Start-ups like Premise and ClearStory Data, as well as larger companies like General Electric, are getting into the act....General Electric, for example, which has over 200 sensors in a single jet engine, has worked with Accenture to build a business analyzing aircraft performance the moment the jet lands. G.E. also has software that looks at data collected from 100 places on a turbine every second, and combines it with power demand, weather forecasts and labor costs to plot maintenance schedules.
start_ups  data  data_driven  data_mining  data_scientists  inflation  indices  massive_data_sets  hyperlocal  Premise  Accenture  GE  ClearStory  real-time  insights  Quentin_Hardy  pattern_recognition  photography  sensors  maintenance  industrial_Internet  small_data 
november 2013 by jerryking
Twitter's Lucrative Data Mining Business - WSJ.com
October 6, 2013 | WSJ | By ELIZABETH DWOSKIN.

Twitter's Data Business Proves Lucrative
Twitter Disclosed It Earned $47.5 Million From Selling Off Information It Gathers

Twitter's data business has rippled across the economy. The site's constant stream of experiences, opinions and sentiments has spawned a vast commercial ecosystem, serving up putative insights to product developers, Hollywood studios, major retailers and—potentially most profitably—hedge funds and other investors....Social-data firms spot trends that it would take a long time for humans to see on their own. The United Nations is using algorithms derived from Twitter to pinpoint hot spots of social unrest. DirecTV DTV +0.99% uses Twitter data as an early-warning system to spot power outages based on customer complaints. Human-resources departments analyze the data to evaluate job candidates....While estimates of the market value of the social-data industry are hard to come by, one research firm, IDC, estimates that the entire "big data" market has grown seven times as quickly as the information technology sector as a whole. It may be valued at $16.9 billion in two years....Each social-data firm boasts proprietary dating-mining tools that go beyond basic keyword searches. Some can zoom in on a subset of people—say, women in a certain ZIP Code—and monitor phrases that show emotion. Then they can create a heat map or a sentiment score that measures how that subset feels about a topic. They have trained natural language processing algorithms to look at slang and broken grammar and to highlight tweets that indicate urgency because of words like "BREAKING."

"We don't just count the volume of these trends. That's naïve," says Nova Spivak, CEO of the Los Angeles-based firm Bottlenose. Rather, his firm looks at the momentum of trends....Many smaller analytics startups are now turning to four companies that Twitter has dubbed "certified data resellers." These brokers, Gnip, Data Sift, Topsy and the Japanese firm NTT Data, 9613.TO -2.04% account for the bulk of Twitter's data revenue. Last year, they paid Twitter monthly fees of about $35.6 million.

Twitter's exponential growth has meant its influence extends well beyond marketing and crisis PR. Nonprofits, human-resource managers and politicians have found Twitter data useful, too.
data  data_mining  Twitter  massive_data_sets  sentiment_analysis  social_media  social_data  trend_spotting  Gnip  Data_Sift  Topsy  NTT_Data  Bottlenose  NLP  hotspots  UN  human_resources  insights  Hollywood  hedge_funds  momentum  product_development 
october 2013 by jerryking
Why Big Ag Likes Big Data - NYTimes.com
October 2, 2013, 3:02 pm 1 Comment
Why Big Ag Likes Big Data
By QUENTIN HARDY
massive_data_sets  agriculture  agribusiness  farming  data_mining  databases  GE  Climate_Corporation  Monsanto 
october 2013 by jerryking
Beyond loyalty: Why retailers track your every purchase - The Globe and Mail
OMAR EL AKKAD AND JOSH KERR

The Globe and Mail

Published
Friday, Jul. 19 2013,

Using variants of the same tools that banks and insurance companies use to detect patterns of account fraud, retail chains in Canada and the U.S. mine their customers’ shopping patterns looking for opportunities to personalize the shopping experience. For example, earlier this year, Shoppers began rolling out a personalized e-mail brochure to each of its loyalty card customers. The e-mails often contain offers not found in their general flyers, as well as limited-time discounts on the sorts of products that individual customers have purchased in the past.

“We’ve had the data for a while now and it has allowed us to make improvements within the store format, but now we’re taking it to the next level,” says Tammy Smitham, vice president of communications and corporate affairs at Shoppers. “We’re giving them exactly what they’re shopping for.”
retailers  customer_loyalty  Omar_el_Akkad  SAS  data_mining  massive_data_sets  store_footprints  Loblaws  Shoppers  personal_data  loyalty_management  Turnstyle 
august 2013 by jerryking
Diamonds in the Data Mine
May 2003 | HBR | By Gary Loveman.

Harrah's Entertainment has outplayed its competition and won impressive gains, despite being dealt a weak hand by the economy The secret? Mining the company's rich database to develop compelling customer incentives. in the Las Vegas Strip, and all of the neighbors are making spectacles of themselves. The $750 million Mirage boasts a Vesuvian volcano that erupts...
HBR  predictive_modeling  Las_Vegas  databases  gaming  CEOs  Harrah's  casinos  yield_management  data_mining  incentives 
january 2013 by jerryking
Era Of The Super Cruncher
September 15, 2007 | - Newsweek and The Daily Beast | by Jerry Adler
data_mining  data  competingonanalytics  books  intuition  decision_making  Yale  data_driven 
january 2013 by jerryking
Data Definitions
Definitions of a data warehouse, database marketing, data mining software, scoring, campaign management software, customer segmentation, dynamic scoring, attrition/churn. What about unstructured data, batch data versus real-time data?
definitions  data  data_driven  databases  data_mining  attrition_rates 
july 2012 by jerryking
From Harvard Yard To Vegas Strip Article
10.07.02 | Forbes.com - Magazine | Carol Potash.

Through branding, cross-casino marketing, loyalty cards, and technology, CEO Gary Loveman has made Harrah's Entertainment, the most diversified of the big four gaming companies, a model of effective customer feedback. In an industry accustomed to relying on intuition, Harrah's has built a database of 25 million customers that drills down through all its activities. Digital profiles are based not on observed behavior of what customers have spent but on analysis of what they are capable of spending. The technology includes built-in marketing interventions designed to close the gap between actual and potential spending. In this new world of computer-generated predictions, the customers are willing participants. Harrah's may be the best example of this kind of ongoing feedback system that could be applied to theme parks, ski resorts, cruise lines, retailers, and subscription businesses such as AOL and satellite TV.
predictive_modeling  Las_Vegas  databases  theme_parks  gaming  CEOs  Harrah's  casinos  yield_management  data_mining  customer_profiling  loyalty_management  customer_feedback  variance_analysis  leisure  branding  Gary_Loveman  marketing  observations 
july 2012 by jerryking
Consumer banking: Counter revolution
May 19th 2012 | | The Economist | Anonymous

the growth of internet usage on smartphones, the rise of “big data” computer processing and the increasing willingness of customers to do complicated things online. These developments have long promised to transform the way banks do business and organise themselves....If this was just a more convenient way of paying, the banks would probably shrug. But it also promises to overturn your existing financial relationships. Instead of reaching for the first card that happens to be in your wallet to pay for a $2 cup of coffee (and risk being charged a $35 penalty by your bank for exceeding your overdraft limit), your phone will choose the best method of payment.
banking  disruption  massive_data_sets  Google  judgment  Paypal  Square  smartphones  data_mining  immigrants  migrants  remittances  mobile_phones 
may 2012 by jerryking
Will This Customer Sink Your Stock? Here's the newest way to grab competitive advantage: Figure out how profitable your customers really are. - September 30, 2002
By Larry Selden and Geoffrey Colvin
September 30, 2002

Get ready for a big idea that's about to sweep through most companies: managing the enterprise not as a collection of products and services, not as a group of territories, but as a portfolio of customers. Of course, managers have always known that some customers are more profitable than others. But it's amazing how many executives, like those of that big retailer, haven't the least idea just how profitable (or unprofitable) individual customers or customer segments are.
customer_profitability  Geoff_Colvin  Dell  RBC  Fidelity_Investments  HBC  customer_lifetime_value  customers  retailers  banks  data_mining  data_driven  competingonanalytics  competitive_advantage 
april 2012 by jerryking
Bizarre Insights From Big Data - NYTimes.com
March 28, 2012 | NYT | By QUENTIN HARDY.

Sometimes unexpected data sources offer big insights....The idea is to have a lot of data of all kinds on hand, because sometimes unexpected combinations of information can lead to valuable insights.
...We will probably see more strange corollaries start to pop up, as more behavior is stored in online databases.
massive_data_sets  data_mining  flu_outbreaks  mobile_phones  unexpected  corollaries  insights 
march 2012 by jerryking
Big Data is watching you
Jan. 06, 2012 | The Globe and Mail | Simon Houpt.

Companies have amassed trillions of digital bread crumbs: from credit card transactions, from people’s online wanderings on social media and search sites, from GPS devices embedded within smart phones...

Live Nation acquired Big Champagne, a consumer data analytics firm that had gained notice for developing the Ultimate Chart, a ranking of the most popular songs and artists according to chatter on social networks and other online sites.

Big Champagne will help Live Nation crunch the information it has on the 200 million ticket buyers in its database, and also help design the company’s dynamic pricing model...An ever more connected world offers richer opportunities for marketers to collect specific consumer data.

The Christmas season may still be a recent memory, but many marketers are already casting a hopeful eye upon 2012 as the year they finally turn into mercantile versions of Santa Claus: omniscient beings who know everything about their customers, and not just whether they’ve been bad or good. (And yes, the marketers believe they’re doing it for goodness’ sake.)

In the past few years, companies have amassed trillions of digital bread crumbs: from credit card transactions, from people’s online wanderings on social media and search sites, from GPS devices embedded within smart phones. Last June, the market intelligence firm IDC said the amount of data produced by our ever-digitizing mass of humanity is more than doubling every two years. Companies are drowning in data. But they’re also recognizing an extraordinary opportunity, and after a series of studies of so-called big data published by research firms over the past year, many are predicting it will become a major focus of marketing executives in 2012.

Already this year, Big Data has received a big endorsement. On Wednesday, after being appointed president of Yahoo, the ex-PayPal executive Scott Thompson was pledging that data would be the key to his new company’s future just as it powered his last company.

“I am certain that the battle of the next generation of Internet businesses will be made up of who has more data and who knows how to use it better than anyone else,” he told a reporter for the trade publication AdAge.com. “I’m not talking about your classic segmentation stuff,” he said, referring to the demographic categorization that companies use to group individuals into broad target markets. Companies such as Yahoo will increasingly focus on individuals. “It’s the segmentation of one and what the data of one tells you,” he said.

In the middle of December, the live entertainment colossus Live Nation acquired Big Champagne, a consumer data analytics firm that had gained notice for developing the Ultimate Chart, a ranking of the most popular songs and artists according to chatter on social networks and other online sites.

Big Champagne will help Live Nation crunch the information it has on the 200 million ticket buyers in its database, and also help design the company’s dynamic pricing model: the practice of altering ticket prices depending on real-time supply and demand. Old industries are also getting into that act. Over the past year, Broadway producers have capitalized on dynamic pricing to charge much higher ticket prices for especially hot shows, and nimbly offer discounts when demand fell away.

Even very young industries are being remodelled by the use of more specific data. Last year, after trying to slug it out with Groupon and Living Social, the two-year-old San Francisco-based local offers provider Bloomspot took a different tack. The company realized it could confront the main reason for merchants’ disenchantment with the sites – a belief that too many people merely take advantage of discounts and never patronize the merchants again – by sifting data in order to find the most valuable customers.

With the permission of both the participating merchants and the customers, “we are able to effectively get access to the stream of consumer credit card purchases belonging to a particular merchant by going through the credit card processors,” said Jasper Malcolmson, the Canadian-born president of Bloomspot, which received $40-million (U.S.) in funding last summer.

Mr. Malcolmson said that analysis of that data enables Bloomspot, which operates in 10 U.S. cities, to determine which customers who have bought, say, a 60-minute massage at New York’s Broadway Chiropractic for $39 (a “$270 value”) end up “acting like penny-pinchers and don’t spend well and don’t return,” and which ones instead treat the discount as an incentive and end up spending more money at the merchant: the goal of making the discount offer in the first place.

“The customers who are good receive follow-up offers, effectively in recognition of their spending behaviours,” he explained.

But Big Data isn’t just being used for newfangled loyalty marketing; many companies are using it to provide better service to customers in new ways. Kenna, a data analytics firm based in Mississauga, designed a mobile app to be used by customers of its client BASF Canada, the farming chemical company. BASF cross-references its customer purchase data with information on weather patterns to generate real-time information for farmers on when to apply the chemicals for greatest crop yield.
Simon_Houpt  massive_data_sets  data_mining  real-time  data  data_driven  personalization  agriculture  Kenna  Live_Nation  loyalty_management  dynamic_pricing  Broadway  Bloomspot  purchase_data 
january 2012 by jerryking
For Start-Ups, Sorting the Data Cloud Is the Next Big Thing - NYTimes.com
By MALIA WOLLAN
Published: December 25, 2011

Splunk, a San Francisco-based start-up whose software indexes vast quantities of machine-generated data into searchable links. Companies search those links, as one searches Google, to analyze customer behavior in real time....Splunk is among a crop of enterprise software start-up companies that analyze big data and are establishing themselves in territory long controlled by giant business-technology vendors like Oracle and I.B.M....“Big software is sold on the golf course, not sold to the people who actually use it,”
massive_data_sets  cloud_computing  start_ups  unstructured_data  sorting  Industrial_Internet  Splunk  data_driven  data_mining  cheap_revolution 
december 2011 by jerryking
Mining of Raw Data May Bring New Productivity, a Study Says - NYTimes.com
May 13, 2011 | NYT | By STEVE LOHR.
(fresh produce) Data is a vital raw material of the information economy, much as coal
and iron ore were in the Industrial Revolution. But the business world
is just beginning to learn how to process it all. The current data surge
is coming from sophisticated computer tracking of shipments, sales,
suppliers and customers, as well as e-mail, Web traffic and social
network comments. ..Mining and analyzing these big new data sets can
open the door to a new wave of innovation, accelerating productivity and
economic growth. ..The next stage, they say, will exploit
Internet-scale data sets to discover new businesses and predict consumer
behavior and market shifts.
....The McKinsey Global Institute is publishing “Big Data: The Next
Frontier for Innovation, Competition and Productivity.” It makes
estimates of the potential benefits from deploying data-harvesting
technologies and skills.
massive_data_sets  Steve_Lohr  McKinsey  data  consumer_behavior  data_driven  data_mining  analytics  Freshbooks  digital_economy  fresh_produce  OPMA  Industrial_Revolution  datasets  new_businesses  productivity 
may 2011 by jerryking
Scraping, cleaning, and selling big data
11 May 2011 | O'Reilly Radar | by Audrey Watters.
What are some of the challenges of acquiring data through scraping?
Flip Kromer: There are several problems with the scale and the metadata,
as well as historical complications.

Scale — It's obvious that terabytes of data will cause problems, but
so (on most filesystems) will having tens of millions of files in the
same directory tree.
Metadata — It's a chicken-and-egg problem. Since few programs can
draw on rich metadata, it's not much use annotating it. But since so few
datasets are annotated, it's not worth writing support into your
applications. We have an internal data-description language that we plan
to open source as it matures.
Historical complications — Statisticians like SPSS files. Semantic
web advocates like RDF/XML. Wall Street quants like Mathematica exports.
There is no One True Format. Lifting each out of its source domain is
time consuming.
massive_data_sets  data  analytics  data_mining  databases  digital_economy  chicken-and-egg  data_quality  metadata 
may 2011 by jerryking
The value of information
Philip Delves Broughton
Financial Times; London
03-08-2011

Jump to best part of document
The value of information
data  data_driven  analytics  Philip_Delves_Broughton  Thomas_Davenport  data_mining 
april 2011 by jerryking
For Data Crunchers, a Glittering Prize - WSJ.com
MARCH 16, 2011| WSJ | By JENNIFER VALENTINO-DEVRIES. With $3
Million Prize, Health Insurer Raises Stakes on the Data-Crunching
Circuit
algorithms  hospitals  predictive_modeling  data_mining  contests  massive_data_sets  data_driven 
march 2011 by jerryking
Google’s 8-Point Plan to Help Managers Improve - NYTimes.com
March 12, 2011 |NYT| By ADAM BRYANT. IN early 2009,
statisticians at Google began a plan code-named Project Oxygen. Their
mission was to devise a way to build better bosses. So, as only a
data-mining giant like Google can do, it began analyzing performance
reviews, feedback surveys and nominations for top-manager awards. They
correlated phrases, words, praise and complaints. Later that year, the
“people analytics” teams at the company produced what might be called
the Eight Habits of Highly Effective Google Managers. ...H.R. has long
run on gut instincts more than hard data. But a growing number of
companies are trying to apply a data-driven approach to the
unpredictable world of human interactions.
“Google is really at the leading edge of that,” says Todd Safferstone,
managing director of the Corporate Leadership Council of the Corporate
Executive Board, who has a good perch to see what H.R. executives at
more than 1,000 big companies are up to.
Google  Octothorpe_Software  human_resources  data_driven  data_mining  analytics  gut_feelings  correlations  praise  complaints 
march 2011 by jerryking
Are Charity Fundraisers Spying on You?
May 18, 2010 | SmartMoney Magazine | by Anne Kadet. Donor
research isn’t new, of course. In a bygone era, fund-raising sleuths
spent days at the library and county clerk’s office, scribbling facts on
index cards. More recently, major charities have spent large sums on
donor data to prepare for capital campaigns. But now, for as little as
$3,000 a year, even smaller nonprofits—like the Cape Cod Commercial Hook
Fishermen’s Association—can use databases that estimate everything from
a donor’s net worth to the size of her mortgage. According to nonprofit
marketing-research firm Campbell Rinker, nearly half of all charities
now use these tools to research donors.
privacy  charities  target_marketing  scuttlebutt  hospitals  nonprofit  fundraising  data_mining  high_net_worth  personal_finance  estate_planning 
may 2010 by jerryking
The data deluge
Feb 27, 2010 | The Economist. Vol. 394, Iss. 8671; pg. 11 |
Anonymous. Everywhere you look, the quantity of information in the
world is soaring. According to one estimate, mankind created 150
exabytes (billion gigabytes) of data in 2005. This year, it will create
1,200 exabytes. Merely keeping up with this flood, and storing the bits
that might be useful, is difficult enough. Analysing it, to spot
patterns and extract useful information, is harder still. Even so, the
data deluge is already starting to transform business, government,
science and everyday life (see our special report in this issue). It has
great potential for good--as long as consumers, companies and
governments make the right choices about when to restrict the flow of
data, and when to encourage it. Plucking the diamond from the waste
ProQuest  data_driven  data_mining  competingonanalytics  transparency  massive_data_sets 
march 2010 by jerryking
Reaping Results: Data-Mining Goes Mainstream
May 20, 2007 | New York Times | By STEVE LOHR. "And Cemex, the
big cement company, uses global positioning satellite locators and
traffic and weather data to improve delivery-time performance in
Mexico."
data_mining  competingonanalytics  data_driven  Steve_Lohr  weather  Cemex 
november 2009 by jerryking
At a Software Powerhouse, the Good Life Is Under Siege
November 21, 2009 | New York Times |By STEVE LOHR. SAS’s
specialty, a lucrative niche called business intelligence software, is
becoming mainstream. Free, open-source alternatives to some of the
company’s products are increasingly popular. On the other end of the
spectrum, the heavyweights of the software industry — Oracle, SAP,
Microsoft and, especially, I.B.M. — are plunging in and investing
billions of dollars. As the stream of companies’ collected data turns
into a torrent, SAS and other software companies are trying to find new
ways to harness it.
Freshbooks  Steve_Lohr  competingonanalytics  data_driven  data_mining  SAS  haystacks 
november 2009 by jerryking
Innovate, Yes--But Where?
03.13.06 | Forbes | by Rich Karlgaard. "Today’s bestseller
list on management bursts with innovation-themed titles. Two I’ve read
and recommend are Geoffrey Moore’s Dealing With Darwin: How Great
Companies Innovate at Every Phase of Their Evolution and Vijay
Govindarajan and Chris Trimble’s 10 Rules for Strategic Innovators: From
Idea to Execution." Startups, I think, hold the best cards when it
comes to two types of innovation: technology and price. But incumbents
also have ample areas in which they can innovate. Consider these
examples: Cost Innovation, Logistics Innovation, Design Innovation,
Line-Extension Innovation, Data-Analysis Innovation,
innovation  howto  Rich_Karlgaard  Geoffrey_Moore  data_mining  design  branding  logistics  Vijay_Govindarajan  books  start_ups  costs  taxonomy 
october 2009 by jerryking
Stuck in traffic? Phone may soon help you escape - The Globe and Mail
Monday, Jan. 15, 2007 | Globe & Mail pg. A12 | by JEFF
GRAY. "In the surprisingly near future, your cellphone may be able to
warn you about a traffic jam ahead, predict precisely how long your
commute home will take, or even recommend an alternative route."
computers essentially take a look at the torrent of data this "pinging"
pours in, using a "triangulation" process based on the time-delay
between pings. Its system figures out which cellphones are moving, where
they are, and how fast they are going. The data are then streamed into a
traffic map and produce precise information on speeds and estimated
travel times not just on major expressways, but on every single road in
cellphone range.
Jeff_Gray  mobile_phones  triangulation  privacy  congestion  competingonanalytics  data_mining  massive_data_sets  location_based_services  metadata  traffic_congestion 
october 2009 by jerryking
Drill Down to Ask Why, Part 1
Jul 2008 | DM Review. New York: Vol. 18, Iss. 7; pg. 6 | by Ralph Kimball.
data_warehouse  business_intelligence  data_mining  BIAs 
june 2009 by jerryking
Put Ad on Web. Count Clicks. Revise. - NYTimes.com
May 30, 2009 | New York Times | By STEPHANIE CLIFFORD. This
approach turns marketing “upside down,” says Ron Proleika, the vice
president of marketing communications at Windstream Communications, an
Internet service provider and a client of Mr. Herman’s. “It forces
marketers to stay on their toes and think of thousands of small great
ideas instead of one great big one."
online_advertising  analytics  data_mining  competingonanalytics  advertising 
june 2009 by jerryking
FT.com / Companies / Technology - Make sense of the in-house data mountain
November 22, 2006 | Financial Times | By Tom Braithwaite. With
swaths of unstructured data lying in corporate servers, whether in the
form of e-mails, PowerPoint presentations or TV images, companies are
increasingly seeking the means to sift through the in-house information
mountain.
search  in-house  databases  information_overload  haystacks  massive_data_sets  data_mining  unstructured_data  sense-making 
june 2009 by jerryking
Data Mining for Shopping Centres - customer knowledge management framework
2001 | Journal of Knowledge Management | Charles Dennis; David Marsland; Tony Cockett
data_mining  retailers  BIAs  shopping  shopping_malls 
may 2009 by jerryking
I.B.M. Unveils Software to Find Trends in Vast Data Sets - NYTimes.com
May 20, 2009 | New York Times | By ASHLEE VANCE. New software
from I.B.M. can suck up huge volumes of data from many sources and
quickly identify correlations within it. The company says it expects the
software to be useful in analyzing finance, health care and even space
weather.
data_mining  IBM  pattern_recognition  massive_data_sets  Ashlee_Vance  haystacks 
may 2009 by jerryking
The Data Mining Renaissance
Friday, April 10, 2009 | Gigaom | Gary Orenstein.

the web changed the way we radiate and consume information and in doing so, created a new opportunity to measure and monetize it. Faced with more user data, logging information, and web content than anyone thought one system could handle, the major web companies developed highly scaled data warehousing solutions themselves. Armed with these tools, they improved customer resonance by building better recommendation engines, more targeted advertising networks and more intricate campaigns.
data  analytics  analysis  data_mining  renaissance  digital_storage  massive_data_sets  tools  value_creation 
may 2009 by jerryking
Political Device Goes Corporate - WSJ.com
MAY 21, 2007 | Wall street Journal | by JOHN D. MCKINNON.

Journal of Political Marketing.

Political operatives who perfected political "microtargeting," a system
for squeezing votes from neglected segments of the electorate, based
largely on reams of data about such things as voter demographics and
personal-spending habits--are taking their mastery of sophisticated new
campaign techniques into the corporate world. Particularly useful in
helping corporations focus on potential customers' core feelings about
buying a product or service.
microtrends  microtargeting  demographics  competingonanalytics  data_mining  political_campaigns  customer_insights  customer_experience  behavioural_targeting  data 
april 2009 by jerryking
IBM's Big Push into Business Consulting - BusinessWeek
April 16, 2009 | Business Week | by Steve Hamm

IBM sees rich opportunity to profit if it can help improve productivity
in sectors such as transportation, electric utilities, and health care.
"We're at the beginning of a new wave," says Kern. "We've begun to
instrument the world [with sensors and other devices that collect
information], but now we have to take that data and analyze it."
competingonanalytics  IBM  data_mining  analytics  sensors  Industrial_Internet  productivity  management_consulting 
april 2009 by jerryking
Math Will Rock Your World
JANUARY 23, 2006 | Business Week | Stephen Baker

The world is moving into a new age of numbers. Partnerships between mathematicians and computer scientists are bulling into whole new domains of business and imposing the efficiencies of math. Look at where the mathematicians are now. They're helping to map out advertising campaigns, they're changing the nature of research in newsrooms and in biology labs, and they're enabling marketers to forge new one-on-one
relationships with customers.
advertising  Stephen_Baker  competingonanalytics  data  data_mining  mathematics  analytics  algorithms  data_scientists  marketing 
april 2009 by jerryking
L. Gordon Crovitz Says Technological Creativity Could Help Wall Street Make Sense of Data - WSJ.com
FEBRUARY 9, 2009 | WSJ | By L. GORDON CROVITZ reports on
the annual Technology, Entertainment and Design conference. TED as an
antidote to recessionary pessimism. Reminder that other industries,
especially Wall Street, need to embrace the technologist ethos of
constant creativity and innovation. "Raw data, now!" Find new
relationships among data and new answers to problems in ways we haven't
been able to imagine
analytics  L._Gordon_Crovtiz  Web  data  Wall_Street  TED  unimaginable  sense-making  pattern_recognition  patterns  data_mining  problems 
february 2009 by jerryking
Mining for Gold - WSJ.com
Interview with Deutsche Bank Asset Management CIO, Sean Kelly.
Details how the firm sorts through the clutter of information to gain an
edge.

THE WALL STREET JOURNAL: How is information technology strategically important for Deutsche Asset Management?

MR. KELLEY: In finance there is a concept called "alpha," which means that you make returns beyond the market as a whole. It's really what asset managers get paid for. For us technology is a sizable factor for creating alpha.

"There's a lot of information but also a lot of noise. You have to figure out algorithms to crawl through [all] this automatically, taking out 95% of the noise and finding signals that indicate the emotions of the market. That's the thing: The information doesn't have to be correct -- it just has to be dominant. A person doesn't have to be right. It just has to be that everyone thinks that way. So if you can figure out ways to get to that information and act on it before the market has a chance to correct itself, it gives you an added edge."
alpha  Deutsche_Bank  data_mining  slight_edge  information_overload  competingonanalytics  CIOs  sorting  noise  signals  informational_advantages 
january 2009 by jerryking

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