Opportunities Ripe for Data

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With today’s technology, we are able to record a large amount of data on our daily lives.  We leave a history of the websites that we visit, our phones can track our location and companies can see what you are buying with your credit card.  Big Data is about taking in this huge amount of data and turning it into useful information. The Wall Street Journal article “Leveraging Data to Drive Innovation” included comments from  Chris Anderson, CEO of 3D Robotics: “We are drowning in data.  But we don’t have enough ability to analyze it.”

If we could come up with efficient ways to crawl through data, we would be better informed and be able to make better decisions that benefit our health.  We could keep track of our vitals constantly, giving us a more complete picture of what we need to do in order to be healthy.  Alternatively, that information can be commercialized. Insurance companies, the food industry, and other commercial interests would use the information to refine their advertising.

By not taking advantage of these pieces of data, we are missing out on potential innovations that can move science and the economy forward.  If homeowners could easily identify what in their home was consuming the most energy, they could take steps towards reducing energy costs.  If automobile manufacturers could reduce emissions from cars by just 1%, that would create a significant decrease in pollution for some cities. It is just a matter of taking the physical world and putting it into measurable data.

Map-Based Visualizations

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The trend in computing today is questioning every aspect of life and compiling data on it.  We can take massive volumes of data and identify deficiencies in the way we run our lives. Directions Magazine’s article, “New map-based visualization provides insight into Seattle commuting data” is an excellent example of this.  IDV Solutions is a data visualization company that took information from the U.S. Census Bureau and other public sources to create an infographic that displays detailed information on the geography of Seattle’s commuting trends.  Infographics help translate the data that we take from the physical world and put it in a data structure that takes the shape of the physical world as well, allowing the reader to quickly spot trends and make decisions based on data that we would not be able to see otherwise.

The implementation of these infographics can bring attention to the efficiency of the public transportation system in Seattle. It can also help determine where improvements can be made.  Even more exciting is the prospect of applying the same techniques to every major population center in the world.  A one percent improvement in efficiency can produce massive reductions in fuel expenditures and gas emissions when applied on a global scale.  The technology exists for the repetition of this process to be a real possibility; it just requires that someone act on it.  The application of this technology is an investment that can save time and resources for commuters. It can also open up other avenues of savings.  The aspects of life that can be improved are endless. We just need to figure out how to put the world in a database.

The Implications of Google Maps

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The Atlantic’s article, “How Google Builds Its Maps – and What It Means for the Future of Everything” isn’t an article about Google Maps as much as it is about Google’s approach to handling data.  As one would expect, there is a lot more to the inner structure of Google Maps than a map from a satellite image.  The directions that you get when you ask how to get from point A to point B stem from a long line of logic problems, logic problems that Google would only know the answers to if Google had committed manpower to investigate the roads themselves.  The physical space that Google Maps allow you to navigate is filled with data that first must be combed for consistency.  Sure, first Google uses other maps with data inputs already, but Google’s commitment to correct data has sent their employees driving all across the world in order to build a massive dataset that is comparable to the physical world that we call reality.

This commitment to accuracy doesn’t just affect Google’s map interfaces, however; this type of thorough and dedicated investment in technologies and applications gives Google a competitive edge in other markets. Google’s strength is the utilization of information, and investments in such areas are helping Google gain an edge over Apple in the growing battle over mobile phones. In particular, The Atlantic’s Alexis Madrigal posits “geo data” in particular “will play an important role in the battle for mobile phones”. While geo data is becoming undeniably important in the mobile phone market, its usages and implementations have larger implications. Google’s large data management techniques as a whole indicate great potential for future developments in the overall field of data analysis.

Connection Revolution

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If you had asked the computer scientists of the late 1960s, it’s unlikely that their theories regarding the effects of connecting the world’s computers via the Internet would bear any resemblance the interconnected world we live in today.  The Internet ushered in a digital age, and today we see the far-reaching effects of connecting computers together in every aspect of our daily lives.  Today, think-tanks at GE are now asking, “Why stop at computers?”

With the Big Data movement changing the way we look at raw information, GE is proposing connecting the vast multitudes of machinery to each other and to sensors.  In particular, GE has plans to attach a jet engine with a variety of different sensors to collect information that could potentially lead to improvements in design.  In fact, GE proposes that we could be doing this with all of our machines.  Though the technology needed to attach such sensors to all of our machines does currently exist, the initial buy-in is huge, and the investment is one that not many companies are likely to make in our current economic situation.  Though the current economic climate does dictate choosing one’s investments wisely, Automation World’s article “Can the Industrial Internet Unleash the Next Industrial Revolution” supports the investment, saying that even if such sensors were able to discover a mere one percent improvement, such a discovery could make a huge difference to a company’s economic situation; for example, a one percent increase in fuel efficiency for airline companies constitutes a $30 billion savings over the course of 15 years.  Optimizing these frequently overlooked aspects of business can create incremental improvements that propel our economy forward.  It’s simply a matter of applying big data concepts to things beyond traditional computing systems, and interpreting the data effectively.

Privacy and Big Data

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Big data, while providing an amazing resource for businesses to optimize their sales and advertising, can also run the risk of invading a person’s privacy if not properly utilized. As FCW’s article “Big data affects hiring, privacy” points out, there is currently very little by way of regulation for the new and developing science of some Big Data collection processes.  To that end, it appears than many are uncomfortable with potential misuses of such information analysis.

As with most new business programs and techniques (in fact, as with most anything that sits on the cutting edge), there is currently very little legislation designed to regulate it and ensure the privacy of all participants. Some find this lack of legislation to be potentially problematic; theoretically, it implies that large, information-collecting companies are free to choose to sell participants’ personal information however and to whomever they please. Legislation regarding the use of such information does seem to be on its way, however.

The article does make an interesting offhanded remark that people of older generations are more bothered by the idea of this perceived invasion of privacy than those of the younger generations. This statement begs more explanation and possibly an article of its own; the effects that generational culture shifts have on the public’s perception of privacy issues are certainly ones that will continue to be the subject of future analysis and examination. Because of this emerging cultural difference, companies may well benefit from a greater understanding of and acting in accordance with this generational divide.

Big Data Analytics for Small Businesses

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Rather than maintaining the trend of simply discussing Big Data principles as they relate to large companies and organizations, Forbes’ “Big Data Analytics: Not Just for Big Business Anymore” explores how smaller business can apply the tools of the information age in order to improve their sales.  The suggestions provided are well laid out, and clear examples are given so that that reader can easily grasp the scope of possibility; the article suggests that in order to effectively utilize Big Data, small businesses must first “become full participants in the digital universe”, “present accurate information about [their] product and services to the customers online”, and utilize analytics to “provide important insights into who the customers are, their interests, and their ‘hangout spots’” online.

I have to say that the article really furthered my excitement about Big Data as a whole. Ultimately, it suggests that not just sales are trackable through technology, but the whims and desires of consumers as well, opening a whole new science of business optimization. Through the above-mentioned information gathering techniques, companies can the utilize Big Data to more accurately tailor their services to customer wants and needs. I would love to see more on the topic discussing the possibility for market prediction based on prior and present information being collected from product searches and Facebook likes.

I think that Big Data also represents a new level of competition between big and small business. Big businesses have massive resources at their disposal in order sift through huge amounts of information, whereas small businesses have to very quickly calibrate against the background noise of information to get to the heart of what they need almost immediately. To this end, I can see companies being formed strictly to help small business get in on Big Data. It’s very exciting being in a time when producers and consumers are communicating and optimizing almost as fast as the market changes.

The Rise and Benefits of Big Data

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In The Wall Street Journal’s “Big Data is on the Rise, Bringing Big Questions”, author Ben Rooney explores the business significance of Big Data through his coverage of the Silicon Valley Comes to Oxford event and examination of the varied benefits of Big Data analysis. In particular, Rooney discusses that while many businesses are aware of the concept of Big Data, “only about 6% of companies have got beyond a pilot stage” of a Big Data initiative, “and 18% are still in one”. Dean of Oxford’s Said Business School Peter Tufano theorizes that while these companies are interested in Big Data analysis for the financial benefits, many are still not sure as to how Big Data can best serve their company’s needs.

Though some individual business have not yet determined exactly how Big Data can benefit them, “those companies that are able to use data effectively are more likely to win in the marketplace”. For example, in the field of personal location data, “some $100 billion of value can be created globally for service providers”. Additionally, the power of Big Data is not proven simply in profits; “John Aristotle Phillips, Chief Executive of Aristotle International” said that while “[the] election was not won because of Big Data…the use of data analytics had a material effect on outcomes” of the most recent presidential election.

In spite of these benefits, however, consumer-driven companies are not embracing Big Data as quickly as some would expect. “Andrew Grant, Chairman of Satalia, a U.K. university spinout that applies algorithms to optimize Big Data, suggests” that for many consumer-driven companies, “cultural obstacles are the biggest impediment” to Big Data implementation. Rooney also discusses that some consumers may find the predictive powers of Big Data to be off-putting; “[the] richest examples of Big Data are to understand consumer behavior and optimize your product for it”, and some customers prefer less targeted marketing tactics.

Chicago as the New Silicon Valley

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In Amy Scott’s article “Creating the Next Silicon Valley in Chicago” for Marketplace, she discusses the possibility of an upcoming technological boom in Chicago. Specifically, she references the presence of the University of Illinois at Urbana Champaign as a potential source of talent for such a boom; the school itself is widely respected, but “its students are often drawn to other shores”.  Talent retention has been a concern for Chicago in the past, as “[founders] of Youtube, Paypal, and Yelp also studied there before heading west”. To help solve this issue, Chicago Mayor Rahm Emanuel “[wants] to draw the talent [to Chicago]”, and believes that “the companies will follow”.

To achieve this goal, Chicago is emphasizing the creation and maintenance spaces in which companies and new technologies can grow. The Merchandise Mart, “a massive building of showrooms and shops”, is becoming such a hub. Motorola Mobility now occupies space within the building, as do 100 startups sharing office space.

An issue that Chicago is facing, however, is the overall culture within the city; according to Margaret O’Mara of the University of Washington, Silicon Valley is unique in its “extraordinary tolerance or risk and failure”, and that such a culture doesn’t yet exist in Chicago. If that cultural impediment can be overcome, however, Chicago holds great potential for new companies. Lightbank, “a venture capital firm run by the co-founders of Groupon” has already begun changing the economic culture of tech startups in the city, having invested in 53 companies after only 18 months. If such trends continue, the potential technological success of Chicago would likely have far-reaching economic implications for the Midwest as a whole.

Voting Online and Computer Security

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In his piece entitled “Why We Still Can’t Vote Online, and Why That May be a Good Thing”, Marketplace’s David Brancaccio responds to an article (“Why Can’t We Vote Online?” from the Verge) concerning the questions regarding and possibility of election voting being conducted online. The Verge’s article presents a thorough overview of the issue, taking into consideration the desires of American voters, political leaders, and the logistical hurdles that would have to be overcome for online voting to be a possibility.

Each article addresses some of the major hurdles in the concept of online voting. First, there seems to be an apparent “lack of enthusiasm when it comes to getting a working online voting system up and running” (Brancaccio). Though Dave Mason, “a former commissioner of the Federal Election Commission, said that ‘it’s just a matter of time until people demand that we vote on the internet’” (Sottek), that time is apparently not today; according to The Verge, there is very little in the way of citizen demand for online voting systems. Secondly, “any system for online voting would need governmental approval from jurisdictions across the country” (Brancaccio), which in itself presents a significant logistical issue.

However, the largest issue facing the implementation of online voting is that of security. Building a hack-proof system that would remain secure even on potentially compromised personal computers is a gargantuan task. Because of the importance of voting and the “stakes of [an]…election”, voting will most likely remain a pen-and-paper affair for now (Brancaccio).

The App Market and Location-Based Services

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In Computer Weekly’s article “Apple iPad App Pushes the Location-Based Cloud”, author Adrian Bridgwater discusses how location-based service technology is currently being used in apps for Apple devices. In particular, he discusses how these technologies relate to the increasing prevalence of cloud computing-based resources and devices. Additionally, he discusses to main types of location-based services: “push” LBS, “pull” (also known as “query”) LBS, and a multi-user LBS service, which is the article’s primary focus.

Specifically, Bridgwater explores the benefits and potential pitfalls of an app called Find My Friends. Find My Friends allows users to view each other’s current locations using their iCloud Apple accounts. Additionally, the app can be used in more specific situations; rather than broadcasting one’s location to one’s friends at all times, Find My Friends allows users to “share [their] location with a group of friends for a limited time”. It can be used to monitor when others leave or arrive at a certain location, and can also distribute that information to one’s own contacts.

While Find My Friends certainly has great potential benefit for users, it also presents a new opportunity for developers to create “a new breed of apps that allows us to interact with each other based on where we are [and] what we’re doing”. However, such possibilities do come with potential privacy concerns. As location-based sharing requires the permission of each user to be fully utilized, individuals’ particular privacy settings could affect the efficacy of LBS-reliant applications. Nevertheless, the increased prevalence of cloud and LBS applications identifies an area of great potential within the apps market.