Monday, November 28, 2016

Big Data in Baseball

The Chicago Cubs won the 2016 MLB World Series and had the best team ERA average during the regular season. A portion of their pitching success can be attributed to the Cubs’ unparalleled use of big data analysis. The Cubs work with a motion capture technology company called KinaTrax to help them analyze numerous pitchers’ movements and angles throughout the process of every pitch. 
Big data has slowly been making its way into the sports world for a while, and for a sport regarded by some as stuck in the past, baseball has been among the quickest to embrace it. This was portrayed most famously in the 2011 film “Moneyball”, which followed the story of Oakland A’s general manager Billy Beane as he formed a team with decisions made largely on the basis of data analysis. Beane and Oakland were extremely successful in the regular season following this method, but the knock on them was that the lack of big-money players did them in in the postseason.
There are many differences and similarities between the 2016 Cubs and the 2002 Athletics. First of all, the Cubs did not need to play “Moneyball”.  Their team salary was a middle of the road $116,654,522, the 14th highest mark in the league, compared to Beane’s Athletics, who had the league’s lowest total salary in 2002. Beane was forced into efficiency, while the Cubs chose it. The Cubs’ money combined with their attention to data analytics is what made them more successful than the A’s in both the regular season and postseason.
Another difference between the two teams could be found in the types of data they were looking at. Much of what the A’s were looking for were predictive statistics. What the Cubs are doing, however, is looking at specific moments in a pitcher’s delivery in order to predict how effective, efficient, durable, etc. a pitcher can be throughout an inning, game, season and career. This attention to detail allows the organization to understand what allows a player to put up good numbers in the relevant statistics the 2002 Athletics examined. Those Athletics were simply capturing the numbers, while the modern day Cubs are analyzing pictures and videos to understand the story behind these numbers.

The 2002 Athletics started a big data movement throughout baseball, and no team has adopted the notion more heavily than these Cubs. It is no wonder they were the best team in baseball in 2016. Big data for the win.


Saturday, November 26, 2016

Tech solutions to tackle overfishing

Overfishing has become an increasing concern over the past few decades. However through the use of technology there are increased solutions for combatting this problem. Technology platforms such as App for Workers, Bar Codes, Eyes on the Sea, Global Fishing Watch, and Tech for Tuna are the future to help save the oceans from over fishing.

In an industry like commercial fishing, regulations must be monitored in order to prevent overfishing and maintain a healthy population. Despite everyone’s efforts in combatting this problem, 25% of the world’s fish stocks are either overexploited or depleted, and another 52% is fully exploited. But with the use of technology this problem could potentially be reduced and eventually resolved.

But can technology really make a substantial impact on the overfishing forefront? Personally I believe it will be a challenge for fishing companies to carry out these technological advances. Although tech companies are making it easier for fishing vessels to prevent overfishing there is still not a simplest solution. The App For Workers is an application that allows Burmese and Cambodian migrant workers around the world to inform and report their working conditions. But the problem I see with this solution is the availability of smartphones for these workers. The workers on these ships are hired for cheap labor and a lot of them can’t afford luxury items such as a smartphone, something that we take for granted. Obviously not every vessel is going to be run up to code, so the use of this app could be important. But with a short of cellphones this genius idea could be an utter failure.

The use of Bar Codes could be an answer to the prayers that overfishing activists have been looking for, but I see downsides to this solution as well. With few monitoring restrictions on the open water the room for potential problems are endless. The barcode can provide a permanent record of where the fish was caught, the species, the weight and the boat that it was caught on. But what happens if fish aren’t scanned? The potential for black market fish sales are even greater, and undersized fish could be kept and not counted on hand. Also another step in the fishing process could decrease production, and pure laziness could get in the way of saving the drastically decreasing marine life.

But with platforms such as Eyes on the Seas and Global Fishing Watch I see huge potential in identifying illegal fishing. This could help prevent fishing in protected areas and help maintain a new standard for commercial fishing. Although I don’t see this problem being fixed in the near future, I believe that this can be a start. Through the use of technology I see fishing becoming much more stringent in the future, and I hope that this can be resolved before we are completely depleted of our greatest food source.

Tuesday, November 22, 2016

Amazon: The Road to Leading the Tech Market

This article from Fortune talks about the new technology that Amazon plans to introduce during its annual tech conference. Amazon Web Services plans to introduce its newer version of PostgreSQL, which is a database used for its cloud customers. This is similar to what Amazon has done in the past with MySQL, but promises this new service will be much easier to manage for the everyday customer. This new product, PostgreSQL would be a great tool for small businesses with little SQL knowledge. One of the things that this article mentions is how this new product compares to its competitors such as Oracle and Microsoft. Amazon’s new product, PostgreSQL offers a less pricey alternative compared to its competition. The pricing of the product in comparison to its competitors lends itself to become the obvious alternative to customers who are browsing for these types of services. By offering a lower price and an easy to use interface for the average customer, Amazon will be well on its way to lead the market of databases for cloud computing. This article also highlights that Amazon has recently been cutting the prices of their products such as QuickSight, which is an analytics product as well as their storage prices. In this regard, Amazon is truly appealing to smaller businesses to take charge of their own business and to utilize their analytical tools in order to do so. One of the new changes that Amazon has done to an existing product of theirs, the Elastic Compute Cloud (EC2) is to allow customers to delete or add memory or processor cores depending on how much they need. This allows customers more flexibility when choosing their options without being limited to a set, static list of choices that other companies are more prone to doing. What do you think competitors such as Oracle or Microsoft could to slow Amazon down from becoming the market leader? In my opinion, Oracle and Microsoft should both focus on creating a new product that is intuitive and easy to use for small business owners with limited to no SQL background. A lot of the times, people will shy away from these types of services/ products because they feel they will not be able to utilize it in a way that could be truly helpful. But if Oracle and/or Microsoft can create this product and market it in a way that makes the average customer feel they are capable of using it, then they might be able to catch up to Amazon.
            Another thing that Amazon plans to bring up during their annual tech conference this year is the possibility of making the machine learning technology that is behind their product Alexa, more accessible and available to more developers. This is one market space that Amazon fails to lead its competitors such as Microsoft and Google. By doing this, Amazon is allowing other developers the opportunity to create and build off of the technology they have already discovered. Why do you think it is so important for companies such as Amazon to allows developers access to their leading technology?

How Predictive Analytics is Shaping the Future of Hockey

            Over the past decade, big data and predictive analytics has taken over the landscape of the sports, most prominently baseball, basketball, and football. One thing that all three of these sports have in common is the vast amount of raw data that each game produces. This makes it relatively easy for analytic specialists and mathematicians to create algorithms that produce actionable data. A sport that does not fall under that category is hockey, a sport contingent upon toughness and teamwork. Those two variables are extremely hard to tally as the article states that “The business of sports, however, can’t quantify the toughness of its players”. Nonetheless, hockey teams are attempting to implement big data analytics in their front office operations, just in a different form than most other sports. Teams have started hiring people from all backgrounds to head their analytics departments, while also hiring outside consultants. How teams are collecting data and what data they are seeking was the most intriguing aspects of this article in my opinion.
Unlike most sports, who collect and interpret data in similar ways, hockey teams take varying approaches, depending on how they value certain immeasurable intangibles. Kyle Dubas the assistant general manager of the Toronto Maple Leafs, who assembled one of the first “research and development” staffs in the NHL. His staff consists of people from an array of backgrounds including a chemical engineer. Their team (and many others) values blocked shots, which they incorporate with other stats including hits to compile ‘grit’ stats or shots to derive ‘real shots on net’ stats. Along with in house statistician teams, teams will hire outside consultants, some with no hockey background to assist them strive for analytical success. Teams have hired industry juggernauts such as SAP analytics to assist them with compiling relevant data and analyzing it to produce actionable results. Also, hockey is adopting analytics in a more broader sense than just at the team level.
As the NHL has always been the little brother to the NFL, MLB, and NBA, the league has taken measures to attempt to have competitive ratings with the big 3 sports leagues in America. The league is valuing fans input more than ever as fans are being presented with surveys and other forms of questionnaires to express their opinion on how the league to become more popular. Also, the league compiles data based on viewership to see which teams, match up and time slots are most likely to produce high ratings. This, along with the data from the fans can be analyzed by the league office to produce predictive results that can increase popularity and hopefully make hockey more popular throughout the world. I believe predictive analytics will become more prevalent throughout the hockey world as it attempts to cement itself as one of the most popular (and profitable) sports worldwide.

Trump’s Win Has Ad Agencies Rethink How They Collect Data, Recruit staff

With Donald Trump’s recent and surprising win in the 2016 presidential election many ad agencies are beginning to question their tactics. The focus of this article is the idea that as big data has begun to revolutionize the world, many people have become infatuated with it to the point that they miss out on other very important data. Ad agencies are looking at this recent election as a primary example of unexpected value. After seeing Trump and his campaign team come out with the win, ad agencies understand that the truly valuable data lies in the very heart of the local consumers. The best example I can use here is the demeanors of both candidates. Hilary Clinton is very political and loves to preach what her audience apparently wants to hear (the Big Data), on the other hand, Donald Trump is an open-minded (and open-mouthed) businessman that connects with the people and tells them what he truly believes is right and the best way to “Make America Great Again”. Furthermore, ad agencies are taking this win as proof that there is opportunity for improvement. The improvement lies in generating more hand on data collection through local staffing. They believe that hiring people from the very town they are marketing gives them an advantage to gain the most valuable and accurate data rather than what data on a large scale claims.

            I believe that this sudden realization is very beneficial and important. An example that instantly came to mind for me is wholesale clubs like Costco. Costco uses big data to follow trends and ultimately offer products that the general public claims as necessities and must haves. However, what gives Costco there competitive advantage over other retail companies is offering products that are special and relevant to the location. For example, Texas loves their BBQ and has many local crafters as well as many locals who hold a place in their heart for that tasty local BBQ sauce. Costco can collect that local data through local staff and therefore can be one step ahead of their competition. 

I completely agree with the idea of strict focus on Big data blinding the opportunity to collect other very important data. I especially liked this quote, “If you want to understand how a lion hunts you don’t go to the zoo, you go to the jungle". If you want to get a fine grasp on trends in say alabama you dont look to big data which is collected mostly in major cities such as New York. People are different, trends are different, the only way to truly understand that and find value in it is to look beyond what the majority claims.

Twitter Terms of Service Violations

In this article I will go into detail about Twitter and their renewed push to punish companies that violate their terms of service. Companies have been using twitter’s data for surveillance and other activities are in violation of their terms of service and this could negatively affect many businesses. In the financial technology world there are a number of firms that use twitters data for surveillance for law enforcement and anti-terrorism. Twitter continues to cut ties with social media monitoring companies and in October they cut off ties with Snaptrends and Geofeedia. Snaptrends has been able to provide police groups with access to its software and has helped boost the number of arrests the department was able to carry out while executing warrants. Geofedia has since laid off half their staff due to the loss in Twitter and Facebook data.
I think that twitter has been hurting recently and their recent struggles have initiated this movement. Twitter has been losing its relevance and with acquisition talks over the past year they need to make themselves more attractive as an organization. Twitter claims that recent stories about surveillance have caused the company “great concern” and that social justice is a long standing and core part of Twitters social mission. However Twitter is not acknowledging the use of the tweets to help law enforcement make arrests. If people are dumb enough to post these ideas and actions online they should be punished and caught for these actions. The FBI has a 5% stake to monitor tweets and Twitter has been a successful resource to help stop terrorism. Terrorist groups use social media to recruit followers and to show their agenda. Twitter should focus on ensuring that groups like ISIS do not use their platform to create a world with hate and violence rather than creating an effort to stop organizations that use this data to catch these criminals. It is mind boggling to me that they would make this massive effort to infringe on businesses when their site is being used as a tool for terrorism.
Twitter has become much less relevant in the market in recent years and this push against people using their data to help law enforcement groups is an example of how much they are struggling. I think they may try to charge organizations for this service in the future so they may have more market appeal and help influence their bottom line. Twitter however needs to find a way to pivot to become relevant again and they should not limit public organizations from using data that is easily accessible on the web, I think that anyone who is dumb enough to have their page set to public and to post their beliefs for anyone to see should not be upset when people use this data. Twitter is a social site but it is not a private group chat with friends and people should smarten up if they truly want this privacy.

Roberts, Jeff John. "Twitter Warns Developers About Misusing Data." Fortune. Fortune, 21 Nov. 2016. Web. 22 Nov. 2016.

“How Nike and Under Armour Became Big Data Businesses”

This article, “How Nike and Under Armour Became Big Data Businesses” by Bernard Marr discusses how Nike and Under Armour are evolving the sports apparel industry, using innovative technology and big data methods. Both companies, are heavily pursuing unique apps, cutting-edge technology and data tracking methods in attempt to make a ground-breaking line of “wearable tech” sports apparel, that will decisively separate their brand as the superior product in the industry.
Nike looks to accomplish this through integration with Apple, recently announcing the Apple Watch Nike +. This integration with Apple coupled with their “Category Offense” marketing plan, which groups their consumers by specific athletic activity rather than demographics, will allow Nike to stay extremely competitive in the sports apparel industry, as they attract not only their consistent consumers but also the massive Apple fan base.
            On the other hand, Under Armor, who have been pursuing Nike as the superior sports apparel company for years, seek to overtake them by innovating unique sports apparel that tracks big data with extreme precision and exactness. Under Armour is heavily investing in “wearable tech that goes way beyond a watch.” They want to create a product that doesn’t just track your steps or your heart beat. They want to create a product that can change your life, using big data to precisely track fitness, health, location, and general lifestyle way beyond any previous device.
            After evaluating both Nike and Under Armour’s methods of innovating the next ground-breaking product in the sports apparel industry, I find myself more attracted to the Nike product. With the Apple Watch Nike +, Nike looks to penetrate a new market which will most likely attract countless new customers. The pairing with Apple also permits Nike to access massive amounts of big data stored by Apple, which allows Nike to create a more unique and customized product experience for its consumers. Nike also has the advantage of enabling this product to operate on all Apple technology, which will make it more attractive to the Apple consumer market and ultimately a more convenient product for Nike consumers in general.  
            I believe Under Armour is also looking to create an innovative product that will take the sports apparel industry by storm, however, their product plans seem to be too similar to existing products, such as the Fitbit. I do not believe UA’s product will be able to compete with Nike simply because of the massive market Nike is going to appeal to and the massive amount of data they will have access to, paired with Apple.
            In conclusion, Big Data and technology are the future of the sports apparel industry. I believe whichever company learns how to successfully incorporate big data with their apparel and provide accurate life changing statistics to their users, will ultimately thrive in the industry in years to come.

Marr, Bernarn. "How Nike And Under Armour Became Big Data Businesses." Forbes. Forbes Magazine, 15 Nov. 2106. Web. 17 Nov. 2016.