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We are considering to start a regular guest post series focused on reviewing information visualization tools and software. First of all, we would like to know whether there is interest in such a regular review feature, and whether there are more people around the community that want to help us with this initiative. Kim Rees is a partner at Periscopic, an interactive design firm specializing in data visualization and information presentation. It might help to require all people who write reviews to describe in detail how to obtain the data from existing data sets and how to put the data into the program. Reviews are always welcome, but "Data Visualization" is such a vast field you might want to consider subsetting or segmenting it.. Yes, as a Librarian looking to implement visualization techniques to my work and services I would appreciate not only reviews, but a matrix of products with their associated reviews, urls etc.
Absolutely - it would be wonderful to share our user-experiences of data viz tools using concrete examples and cases.
I would really welcome the opportunity to have our software reviewed in this community - getting feedback from people who know a lot about visualization will only make our software better. Your site has introduced me and friends to the 'joys' of data visualizations, and coming from a complete data vis.
The data sets that could be used are (depending on where mostly data visualization is used these days) are simple Monthly Revenue and Analytics charts to slightly more complex Network Monitoring Charts that would require real-time visualization too. Some other things that could be included are: What domain of data visualization is the tool best suited for?
If you do reviews, I'd like to see them in a separate section and the authors should be reputable. For the standard tasks we should actually check how efficient or effective a tool is in order to find certain structures and features in the data - we are all too easily blinded by flashy tools and forget about the analytical part. As a provider of interactive visualization tools, we would of course be delighted to have our applications independently reviewed! I'm a reader who's not professionally involved in visualization, but would like to bring more sophisticated presentation into various projects I'm involved in.
I would be happy just to see a simple matrix, or perhaps the maintenance of a visualization software category on Wikipedia.
A resounding vote "Yes!" with the proviso that reviews are conducted by real-world users with real-world needs -- and not by vendor staff. I started to put the issues raised in your comments in a debategraph (which you'll find once you click on my name).
Sometimes a good case can be made for remaining a technological Luddite; sometimes eschewing the latest-and-greatest technical gizmo may actually work for you.
In a report that aired on April 27, CBS 60 Minutes correspondent Leslie Stahl expressed surprise that part of the computer system responsible for controlling the launch of the Minuteman III intercontinental ballistic missiles relied on data loaded from 8-inch floppy disks. An Air Force officer showed Stahl one of the disks, marked “Top Secret,” which is used with the computer that handles what was once called the Strategic Air Command Digital Network (SACDIN), a communication system that delivers launch commands to US missile forces. It is likely that business will never eliminate gut instinct from the decision-making process.
The caveat, of course, is that data, big data and an even bigger reliance on that data requires subject matter expertise and analysts with critical thinking skills and sound judgement — data cannot be used blindly.
Throughout history, innovations in instrumentation—the microscope, the telescope, and the cyclotron—have repeatedly revolutionized science by improving scientists’ ability to measure the natural world.
So if data is unreliable and so is intuition, what is a responsible decision maker supposed to do? The scientific method is largely responsible for the astonishing increase in our understanding of the natural world over the past few centuries. While data is essential for scientific decision making, theory, intuition, and imagination remain important as well—to generate hypotheses in the first place, to devise creative tests of the hypotheses that we have, and to interpret the data that we collect. Also important is experimentation, which doesn’t mean “trying new things” or “being creative” but quite specifically the use of controlled experiments to tease out causal effects. Replicating the conditions of a controlled experiment is often difficult or impossible in business or policy settings, but increasingly it is being done in “field experiments,” where treatments are randomly assigned to different individuals or communities. Although field experiments are not an invention of the Internet era—randomized trials have been the gold standard of medical research for decades—digital technology has made them far easier to implement. Exacerbating this problem is that many of the most consequential decisions offer only one opportunity to succeed. New reports suggest that the NSA (National Security Agency) is collecting and analyzing over 5 billion records per day from mobile phones worldwide.
The National Security Agency is gathering nearly 5 billion records a day on the whereabouts of cellphones around the world, according to top-secret documents and interviews with U.S. The records feed a vast database that stores information about the locations of at least hundreds of millions of devices, according to the officials and the documents, which were provided by former NSA contractor Edward Snowden. The NSA does not target Americans’ location data by design, but the agency acquires a substantial amount of information on the whereabouts of domestic cellphones “incidentally,” a legal term that connotes a foreseeable but not deliberate result. One senior collection manager, speaking on the condition of anonymity but with permission from the NSA, said “we are getting vast volumes” of location data from around the world by tapping into the cables that connect mobile networks globally and that serve U.S. In scale, scope and potential impact on privacy, the efforts to collect and analyze location data may be unsurpassed among the NSA surveillance programs that have been disclosed since June. The NSA has no reason to suspect that the movements of the overwhelming majority of cellphone users would be relevant to national security. Still, location data, especially when aggregated over time, are widely regarded among privacy advocates as uniquely sensitive.
So, it is no longer a surprise — our digital lives are tracked, correlated, stored and examined. If she truly wanted to disappear herself from Google, Philo could start by changing her superb name to something less diverting.
But still, maybe we should all embrace anonymity, given this week’s revelations that technology giants cooperated in Prism, a top-secret system at the US National Security Agency that collects emails, documents, photos and other material for secret service agents to review. Internet evangelists such as Clay Shirky and Charles Leadbeater hoped for something very different from this pathologised reality. Many companies see big data and related solutions as a panacea to a range of business challenges: customer service, medical diagnostics, product development, shipping and logistics, climate change studies, genomic analysis and so on. As chief scientist for President Obama’s reelection effort, Rayid Ghani helped revolutionize the use of data in politics.
Now, with Obama again ensconced in the Oval Office, some veterans of the campaign’s data squad are applying lessons from the campaign to tackle social issues such as education and environmental stewardship. Ghani, who is 35, has had a longstanding interest in social causes, like tutoring disadvantaged kids. Before joining the Obama campaign in July 2011, Ghani wasn’t even sure his expertise in machine learning and predicting online prices could have an impact on a social cause. One of the most important ideas he developed, dubbed “targeted sharing,” now forms the basis of Edgeflip’s first product.
Edgeflip’s app, like the one Ghani conceived for Obama, will ask people who share a post to provide access to their list of friends.
Say a hurricane strikes the southeastern United States and the Red Cross needs clean-up workers.
Michael Slaby, a senior technology official for Obama who hired Ghani for the 2012 election season, sees great promise in the targeted sharing technique.
For instance, Ghani has been working with Fidel Vargas, CEO of the Hispanic Scholarship Fund, to increase that organization’s analytical savvy. Google continues to extend its technology boundaries and its vast indexed database of information.
So, beware the next time you are sitting in a Starbucks or shopping in a mall or riding the subway, you may be being recorded and your digital essence distributed over the internet. In the online world – for now, at least – it’s the advertisers that make the world go round.
So how do you reconcile the fact that there is a finite amount of data to be gathered online with the need to expand your data collection to keep ahead of your competitors? Google Glass is the first major salvo in an arms race that is going to see increasingly intrusive efforts made to join up our real lives with the digital businesses we have become accustomed to handing over huge amounts of personal data to. The principles that underpin everyday consumer interactions – choice, informed consent, control – are at risk in a way that cannot be healthy.
Imagine if Google or Facebook decided to install their own CCTV cameras everywhere, gathering data about our movements, recording our lives and joining up every camera in the land in one giant control room. More importantly, who gave you permission to collect data on the person sitting opposite you on the Tube? A fascinating article by Tom Simonite excerpted below sheds light on the data collection and data mining initiatives underway or planned at Facebook. If Facebook were a country, a conceit that founder Mark Zuckerberg has entertained in public, its 900 million members would make it the third largest in the world. It would far outstrip any regime past or present in how intimately it records the lives of its citizens. And yet, even as Facebook has embedded itself into modern life, it hasn’t actually done that much with what it knows about us. Heading Facebook’s effort to figure out what can be learned from all our data is Cameron Marlow, a tall 35-year-old who until recently sat a few feet away from ­Zuckerberg. Facebook has all this information because it has found ingenious ways to collect data as people socialize.
Marlow eschews the collegiate programmer style of Zuckerberg and many others at Facebook, wearing a dress shirt with his jeans rather than a hoodie or T-shirt.
Marlow’s team works with managers across Facebook to find patterns that they might make use of. It may seem strange that an eight-year-old company without a proven business model bothers to support a team with such an academic bent, but ­Marlow says it makes sense. Marlow says his team wants to divine the rules of online social life to understand what’s going on inside Facebook, not to develop ways to manipulate it. In April, influenced in part by conversations over dinner with his med-student girlfriend (now his wife), Zuckerberg decided that he should use social influence within Facebook to increase organ donor registrations. Advertisers, too, would be eager to know in greater detail what could make a campaign on Facebook affect people’s actions in the outside world, even though they realize there are limits to how firmly human beings can be steered. These are the central questions raised by a damning FCC report on Google’s Street View program that was released last weekend.
While developing its Street View cars, Google’s engineers realized that the vehicles could also be used for “wardriving.” That’s a sinister-sounding name for the mainly noble effort to map the physical location of the world’s Wi-Fi routers. But Google, unlike other companies, wasn’t just recording the location of people’s Wi-Fi routers. Imagine a postal worker who opens and copies one letter from every mailbox along his route. Pause for a second, and think of all the personal data that companies have amassed about you. Today, people have no choice but to give away their personal information—sometimes in exchange for free networking on Twitter or searching on Google, but other times to third-party data-aggregation firms without realizing it at all. Huberman, who directs HP Labs’ Social Computing Research Group, has come up with an alternative—a marketplace for personal information—that would give individuals control of and compensation for the private tidbits they share, rather than putting it all in the hands of companies.
In a paper posted online last week, Huberman and coauthor Christina Aperjis propose something akin to a New York Stock Exchange for personal data.
On his proposed market, a person who highly values her privacy might chose an option to sell her shopping patterns for $10, but at a big risk of not finding a buyer.


Huberman is not the first to investigate a personal data marketplace, and there would seem to be significant barriers—like how to get companies that already collect data for free to participate.
That ideal, whether invoked in the marketing of business intelligence dashboards or data warehouses, is always a ways off, but data visualization and visual analytics software offer an increasingly broad range of users a way to explore and analyze large swaths of data, run what-if scenarios and otherwise interpret and manipulate complex information. After all, there are plenty of reviews available online, from testing software, electronic gadgets and books, to the literal unpacking of newly acquired goods, but almost none that deal with the development of data visualizations.
Making sense of data is crucial to our everyday lives especially now more than ever with the fast-paced lifestyle we live in. The best I can figure out would be a presentation of some smart flash- and actionscript-based tools.
Meaningful requires that real data be visualized and insights revealed that were not seen in traditional statistical tests or designs.
Tools like Tableau & EnSight are kinda in different realms, comparing them against each other (while are really Visualization tools) isn't really fair. It would be also useful to offer a first review (followed by periodic updates) trying to classify visualization tools by means of several categories. An updated matrix of this information would be extremely useful for me, my faculty and students.
Increasingly, there are outsiders who want to use our tools and have no idea what the strengths and weaknesses of certain tools are.
For example, if a tool offers only gauges, then it is best suited to display KPIs in a dashboard. The format of the review shouldn't be too fixed, just try to find hig standards of the reviews. Vendors are usually good at generating feature matrixes, but I find more value in hearing an actual user's experience in accomplishing results with a product.
But also some tech tips or hints of how each article's featured image was created or could be created. A recent report on CBS 60 Minutes showed us how part of the computer system responsible for launch control of US intercontinental ballistic missiles (ICBM) still uses antiquated 8-inch floppy disks. Beyond the floppies, a majority of the systems in the Wyoming US Air Force launch control center (LCC) Stahl visited dated back to the 1960s and 1970s, offering the Air Force’s missile forces an added level of cyber security, ICBM forces commander Major General Jack Weinstein told 60 Minutes. The analog phone systems, for example, often make it difficult for the missileers to communicate with each other or with their base. However, as data, now big data, increasingly pervades every crevice of every organization, the use of data-driven decisions will become the norm.
Now, with human behavior increasingly reliant on digital platforms like the Web and mobile apps, technology is effectively “instrumenting” the social world as well. While there is no correct answer to this question—the world is too complicated for any one recipe to apply—I believe that leaders across a wide range of contexts could benefit from a scientific mind-set toward decision making.
Yet it has been slow to enter the worlds of politics, business, policy, and marketing, where our prodigious intuition for human behavior can always generate explanations for why people do what they do or how to make them do something different.
Data and theory, in other words, are the yin and yang of the scientific method—theory frames the right questions, while data answers the questions that have been asked. In business, most of what we observe is correlation—we do X and Y happens—but often what we want to know is whether or not X caused Y.
For example, MIT’s Poverty Action Lab has conducted over 400 field experiments to better understand aid delivery, while economists have used such experiments to measure the impact of online advertising. Thus, as companies like Facebook, Google, Microsoft, and Amazon increasingly reap performance benefits from data science and experimentation, scientific decision making will become more pervasive. Unlike scientists, who have the luxury of withholding judgment until sufficient evidence has accumulated, policy makers or business leaders generally have to act in a state of partial ignorance. One cannot go to war with half of Iraq and not the other just to see which policy works out better. Analysts can find cellphones anywhere in the world, retrace their movements and expose hidden relationships among the people using them. Rather, it collects locations in bulk because its most powerful analytic tools — known collectively as CO-TRAVELER — allow it to look for unknown associates of known intelligence targets by tracking people whose movements intersect. Sophisticated mathematical tech­niques enable NSA analysts to map cellphone owners’ relationships by correlating their patterns of movement over time with thousands or millions of other phone users who cross their paths.
Social media have changed the way we interact with other people in line with what the sociologist Zygmunt Bauman wrote in Liquid Love.
Big data: typically a collection of large and complex datasets that are too cumbersome to process and analyze using traditional computational approaches and database applications. During the final 18 months of the campaign, he joined a sprawling team of data and software experts who sifted, collated, and combined dozens of pieces of information on each registered U.S.
Edgeflip, a startup Ghani founded in January with two other campaign members, plans to turn the ad hoc data analysis tools developed for Obama for America into software that can make nonprofits more effective at raising money and recruiting volunteers. In Chicago, Ghani’s hometown and the site of Obama for America headquarters, some campaign members are helping the city make available records of utility usage and crime statistics so developers can build apps that attempt to improve life there.
But the campaign’s success in applying such methods on the fly to sway voters is now recognized as having been potentially decisive in the election’s outcome (see “A More Perfect Union”). These models allowed the campaign to target door knocks, phone calls, TV spots, and online ads to where they were most likely to benefit Obama. It’s a Facebook app that prompts people to share information from a nonprofit, but only with those friends predicted to respond favorably.
This will pull in not only friends’ names but also personal details, like their age, that can feed models of who is most likely to help. The app would ask Facebook users to share the Red Cross message, but only with friends who live in the storm zone, are young and likely to do manual labor, and have previously shown interest in content shared by that user. Vargas thinks social data could predict which scholarship recipients are most likely to contribute to the fund after they graduate. He imagines online petitions that act like open-source software, getting passed around and improved.
Surely, giving all people access to the combined knowledge of the human race can do nothing but good, intellectually, politically and culturally. After all, you are information: from the sequence of bases in your DNA, to the food you eat and the products you purchase, to your location and your planned vacations, your circle of friends and colleagues at work, to what you say and write and hear and see. Now with the introduction of Google Glass the company extends its domain to a much more intimate level. If you’re Google, they represent more than 90% of your revenue and without them you would cease to exist.
Firstly, try as hard as is legally possible to monopolise the data streams you already have, and hope regulators fine you less than the profit it generated.
Our ability to walk away from a service depends on having a choice in the first place and knowing what data is collected and how it is used before we sign up. In abandoning critical thought and decision making, allowing ourselves to be guided by a melee of search results, social media and advertisements we do risk losing a part of what it is to be human. With its 900 million member-citizens Facebook is the third largest country on the planet, ranked by population. In fact, its data privacy policies and personal data mining might well put it in the same league as the Stalinist Soviet Union or cold war East Germany. Private conversations, family photos, and records of road trips, births, marriages, and deaths all stream into the company’s servers and lodge there. The group Marlow runs has escaped the public attention that dogs Facebook’s founders and the more headline-grabbing features of its business. Users fill out profiles with their age, gender, and e-mail address; some people also give additional details, such as their relationship status and mobile-phone number. For one thing, Marlow is confident that exploring this resource will revolutionize the scientific understanding of why people behave as they do. Although it was just a research project, it soon became so popular that Marlow’s servers crashed.
For instance, they study how a new feature spreads among the social network’s users. Users were given an opportunity to click a box on their Timeline pages to signal that they were registered donors, which triggered a notification to their friends. For those who like to believe that Google has good intentions recent events strain these assumptions. The Street View scandal began with a revolutionary idea—Larry Page wanted to snap photos of every public building in the world. Creating a location database of Wi-Fi hotspots would make Google Maps more useful on mobile devices—phones without GPS chips could use the database to approximate their physical location, while GPS-enabled devices could use the system to speed up their location-monitoring systems. When a Street View car encountered an open Wi-Fi network—that is, a router that was not protected by a password—it recorded all the digital traffic traveling across that router. Google’s sniffing was pretty much the same thing, except instead of one guy on one route it was a whole company operating around the world. In its response to the FCC and its public blog posts, the company says it is sorry for what happened, and insists that it has established a much stricter set of internal policies to prevent something like this from happening again. Then think about the billions that these companies make in trading this data to advertisers, information researchers and data miners. This may not be as far fetched as it seems, especially as the backlash grows against the increasing consolidation of personal data in the hands of an ever smaller cadre of increasingly powerful players. A trusted market operator could take a small cut of each transaction and help arrive at a realistic price for a sale. But with Internet companies making billions of dollars selling our information, fresh ideas and business models that promise users control over their privacy are gaining momentum. But, he says, since the pricing options he outlines gauge how a person values privacy and risk, they address at least two big obstacles to making such a market function.
Until recently, this was the purview of experts.Related StoriesUsing the science of perception to visualize network security data. Tools that could efficiently deliver results that people could act on would be most useful.
Very usefull when it comes to present information model not though diagrams but adapted to the business view.
Thorough reviews are time consuming, and it's for yourself to judge whether it's what your energy should go into.
This part of the national defense is so old and arcane it’s actually more secure than most contemporary computing systems and communications infrastructure. The Air Force commissioned studies on updating the ground-based missile force last year, and it’s preparing to spend $19 million this year on updates to the launch control centers. As this happens, more and more businesses find themselves employing data scientists to help filter, categorize, mine and analyze these mountains of data in meaningful ways.
The resulting deluge of data has revolutionary implications not only for social science but also for business decision making.
It can lead decision makers to ignore information that is harder to obtain, or make them feel more certain than they should. For every Robert McNamara, there is a Ron Johnson, the CEO whose disastrous tenure as the head of JC Penney was characterized by his dismissing data and evidence in favor of instincts. Because these explanations are so plausible, our natural tendency is to want to act on them without further ado. How many additional units of your new product did your advertising campaign cause consumers to buy? Likewise, one cannot reorganize the company in several different ways and then choose the best.


And if you’re not unGoogleable then, if Philo is right, you can never be truly chic, even if you were born in Paris. Only a cynic would suggest that this blog post might help the Waikiki Acrobating Troupe veteran’s career at this – serious face – difficult time.
Both men revelled in the fact that new web-based social tools helped single mothers looking online for social networks and pro-democracy campaigners in Belarus.
Usually the big data moniker will be accompanied by an IT vendor’s pitch for shiny new software (and possible hardware) solution able to crunch through petabytes (one petabyte is a million gigabytes) of data and produce a visualizable result that mere mortals can decipher. It’s all part of a bigger idea to engineer social systems by scanning the numerical exhaust from mundane activities for patterns that might bear on everything from traffic snarls to human trafficking. That’s a big change from the usual scattershot approach of posting pleas for money or help and hoping they’ll reach the right people.
But if the same person shared an appeal for donations instead, he or she would be prompted to pass it along to friends who are older, live farther away, and have donated money in the past.
You are a collection of datapoints, and if you don’t market and monetize them, someone else will. While the Orwellian dystopia of government surveillance and control may still be a nightmarish fiction, corporate snooping and monetization is no less troubling. You don’t own the data, you don’t control the data and you definitely don’t know what happens to the data.
There is a gaping hole in the middle of the Google Glass world and it is one where privacy is not only seen as an annoying restriction on Google’s profit, but as something that simply does not even come into the equation. They’ve already produced stickers to put up informing people that they should take off their Glass.
Facebook has collected the most extensive data set ever assembled on human social behavior.
Known internally as the Data Science Team, it is a kind of Bell Labs for the social-networking age. A redesign last fall introduced profile pages in the form of time lines that invite people to add historical information such as places they have lived and worked. His team can also help Facebook influence our social behavior for its own benefit and that of its advertisers.
He might have become one had he not realized early in his career that Web companies would yield the juiciest data about human interactions.
The new feature started a cascade of social pressure, and organ donor enrollment increased by a factor of 23 across 44 states.
If the American Heart Association wanted to encourage healthy eating, for example, it might be able to refer to a playbook of Facebook social engineering.
The company was found to have been snooping on and collecting data from personal Wi-Fi routers. Beginning in 2007, the search company’s vehicles began driving on streets in the United States (and later Europe, Canada, Mexico, and everywhere else), collecting a stream of images to feed into Google Maps. As long as the car was within the vicinity, it sucked up a flood of personal data: login names, passwords, the full text of emails, Web histories, details of people’s medical conditions, online dating searches, and streaming music and movies.
The FCC report says that when French investigators looked at the data Google collected, they found “an exchange of emails between a married woman and man, both seeking an extra-marital relationship” and “Web addresses that revealed the sexual preferences of consumers at specific residences.” In the United States, Google’s cars collected 200 gigabytes of such data between 2008 and 2010, and they stopped only when regulators discovered the practice. The company characterizes the collection of Wi-Fi payload data as the idea of one guy, an engineer who contributed code to the Street View program. The FCC report points out that Milner’s “design document” mentions his intention to collect and analyze payload data, and it also highlights privacy as a potential concern.
He’s tested this the academic way, through experiments that involved asking men and women to share how much they weigh for a payment. An app should be clearly categorized based on, let's say technology or available visualization methods in addition to a short review and maybe some examples.
If a tool has the basic charts which are very customizable and flexible, then it can be used for the most of the generic data visualization (polls, analytics, surveys etc) though I am not very sure what exactly to call that. We have already worked with developers of social network visualisation software at universities in Europe so happy to make this info available on a wider basis and try out new ones. So, next time your internet-connected, cloud-based tablet or laptop gets hacked consider reverting to a pre-1980s device.
The risk is that in managing what we have measured, we miss what really matters—as Vietnam-era Secretary of Defense Robert McNamara did in relying too much on his infamous body count, and as bankers did prior to the 2007–2009 financial crisis in relying too much on flawed quantitative models. For every flawed statistical model, there is a flawed ideology whose inflexibility leads to disastrous results. But if we have learned one thing from science, it is that the most plausible explanation is not necessarily correct. No matter how rigorously one tries to base one’s decisions on evidence, some guesswork will be required. With this in mind, some are taking ownership of the issue and seeking to erase themselves from the vast digital Orwellian eye.
But then Homes has thought a lot about privacy, having written a play about the most famously private person in recent history, JD Salinger, and had him threaten to sue her as a result. Among those pursuing such humanitarian goals are startups like DataKind as well as large companies like IBM, which is redrawing bus routes in Ivory Coast (see “African Bus Routes Redrawn Using Cell-Phone Data”), and Google, with its flu-tracking software (see “Sick Searchers Help Track Flu”). Not surprisingly, this raises numerous concerns over privacy and security, and not only for the wearer of Google Glass. Remember, to some, you are merely a datapoint (care of Google), a publication (via Facebook), and a product (courtesy of Twitter). For added impact, if you’re not content with Google analysing the data, the person can share it to social media as they see fit too. Put another way – what would you say if instead of it being Google Glass, it was Government Glass?
We trust what we see, it’s convenient and we don’t question the motives of a search engine in providing us with information. Everyone has a feeling that this unprecedented resource will yield something big, but nobody knows quite what.
Unlike academic social scientists, Facebook’s employees have a short path from an idea to an experiment on hundreds of millions of people. And which of these scenarios should we wish for—which would assuage your fears about the company that manages so much of our personal data? By the time Google began building its system, several startups had already created their own Wi-Fi mapping databases. Was it the inevitable result of Google’s maximalist philosophy about public data—its aim to collect and organize all of the world’s information?
Though Google’s privacy team never reviewed the program, many of Milner’s colleagues closely reviewed his source code.
Adopting a scientific approach to decision making requires us to test our hypotheses with data. Simply observing the outcome of a particular choice does not answer causal questions like these: we need to observe the difference between choices. However, to some being untraceable online is a fashion statement, rather than a victory for privacy. They apply math, programming skills, and social science to mine our data for insights that they hope will advance Facebook’s business and social science at large.
Several members of the team have training in sociology or social psychology, while others began in computer science and started using it to study human behavior. On Monday, the New York Times identified him as Marius Milner, a network programmer who created Network Stumbler, a popular Wi-Fi network detection tool. Whereas other analysts at the company focus on information related to specific online activities, Marlow’s team can swim in practically the entire ocean of personal data that Facebook maintains. The company argues that Milner—for reasons that aren’t really clear—slipped the snooping code into the Street View program without anyone else figuring out what he was up to. Of all the people at Facebook, perhaps even including the company’s leaders, these researchers have the best chance of discovering what can really be learned when so much personal information is compiled in one place.
Nobody else on the Street View team wanted to collect Wi-Fi data, Google says—they didn’t think it would be useful in any way, and, in fact, the data was never used for any Google product. They allow users to view large datasets at a glance, to discern details, relationships and trends that might not be apparent in tables or unstructured text. Data visualization, if done right, taps human vision and cognition to present data in ways that quickly convey scope, connections, anomalies and trends. Tableau this month is adding a low-cost ($500) software as a service (SaaS), or hosted version of its Tableau server. Wealth Management subsidiary replaced a proprietary, in-house data analytics application with Tableau. The bank was one of the Seattle-based company’s early customers, beginning in 2009 when it used the visual analytics software to generate several dozen regular reports for the sales support group for investment advisors serving high-net-worth clients, says Shawn Spott, vice president and manager of marketing research. After deliberately starting small, Spott says the investment group has increased to 3,500 users and 50 developers spanning business, sales and marketing departments, providing data dashboards, reporting and direct data access. While the dashboards mostly present predefined queries in a narrow range of visualizations, more technical and statistics-savvy users have a freer hand in using Tableau.
For example, analysts and consultants in finance and product management can run animations of scatter plots representing five years of client segmentation data, according to Spott.This year the research department began using Tableau to analyze, condense and present the results of lengthy surveys.
Wea€™ve got that window shortened to anywhere from a day to ten days for a report that has links to current data. The taxonomies vary, but broadly put, visual analytics and data visualization applications help users discover and explore their data, analyze it and present it. They are commonly grouped with business intelligence and analytics or data visualization software. Microsoft Excel is the most widely used tool in part because of its ubiquity and ease of use.
Others offer front end integration with a wide range of data sources.Gartner Group, in its February, 2013 Business Intelligence and Analytics Platforms review highlights some key visual analytics and data visualization capabilities. These include interactive visualizations, graphs and reports, predictive modeling, tracking business metrics via scorecards, real-time data updates, ad hoc querying (eliminating the need for IT assistance), and collaboration. Forrester singles out a number of defining characteristics, including a wide array of display and visualization options, dynamic data content, visual querying, linking of related graphs, charts and other elements such that changes in one are reflected in the others, animation, event alerts, geospatial representations (like maps and architectural drawings), and personalization.While most tools handle both structured and unstructured data, some are better for structured dataa€”the rows and columns of network security statistics or financial data, and others are better for unstructured dataa€”like social media feeds or genetic information. Some data, such as Twitter feeds, can be treated as unstructured text or organized in spreadsheets, although there are trade-offs. Forrester Research notes in its third quarter 2012 Advanced Data Visualization Platforms review that visual analytics applications also need to handle semi-structured data like XML and state of process information from business process management applications.The tools in this category support popular query languages, primarily SQL and MDX, but also XQuery and DMX. Support for multiple data platforms is a baseline requirement, according to Shawn Spott, vice president and manager of marketing research at RBC Wealth Management. The tool requires little programming to set up and connect to data sources and automates the process of selecting the right visualization for a given data set. Most products pair data with appropriate graphics, or present users with suitable choices, including tables of text, bar charts, heat maps, scatter plots, tree maps, or Gantt charts.



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    The tasks of automation, inbound marketing, e-mail, social networks help a user in reaching the preferred outcome.
  3. 14.12.2015 at 20:27:24

    Leonardo_dicaprio writes:
    Details of everyone, video editing software is what behind clips, movie.
  4. 14.12.2015 at 10:19:43

    RESUL_SAHVAR writes:
    The software is a plus if it comes date with the view count and coverage as the this and.