The Stubborn Little Wolf: Pop-Up Dinner Series

I am definitely not a chef (unless you count pizza rolls and mac and cheese), but I do enjoy eating good food and have an appreciation for the culinary arts. I was excited when my friend, Phil Kovalev, told me about a pop-up dinner series that he would be hosting. Phil, a sophomore at Indiana University, is studying informatics but also has a passion for cooking. Following a growing trend in the gastronomical world, Phil decided that a great way to share his passion would be through a pop-up dinner series. He offered 10 tickets to the event, which was hosted at his house, and chose to call the series The Stubborn Little Wolf, a nickname given to him by his mother based on a children’s book of the same name. When reading the book to Phil as a kid, his mother noticed that he had a lot in common with the wolf in the story, and so the nickname stuck. I had high hopes for the meal, but Phil some how managed to exceed all of my expectations. The dinner was divided into 3 different parts, Provisions, Feather+Beaks, and Sugar+Spice. The Provisions included fresh baguette with homemade pear and cranberry jam. The main course, the Feather+Beaks, combined Pekin duck breast with stuffing and sage. For dessert, the Sugar+Spice portion, we were served poached Fuji apple, salted caramel sorbet, and farina cake. In addition, he created a great atmosphere by hanging lights throughout the dining room and classin’ it up with soft instrumental music.

The food was delicious, the other guests were friendly, and the event was an unattested success. I’m looking forward to see what he cooks up next.

Start Up Weekend Hits Bloomington

This weekend, I had the opportunity to participate in Start Up Weekend in Bloomington. I was planning on visiting some friends in Los Angeles, and later planned on hiking at Red River Gorge in Kentucky, but ultimately ended up stuck in Bloomington, which turned out to be a great decision. Start Up Weekend is a global program sponsored by Google for Entrepreneurs that gives individuals the opportunity to create a start-up in 54 hours. Participants are connected with designers, developers, legal experts, and mentors and spend the weekend working to create a minimum viable product to present at the end of the 54 hours. The weekend-long event began on Friday evening, and I really wasn’t planning on coming back on Saturday or Sunday, but was lucky enough to get connected with a great team (Pictured in the above gallery), so I decided to stay. Our project, adapted from a school project from 5 of my team members, focused on the idea of simplifying the process for receiving tax deductions for food donations by creating a platform that would aggregate this information and generate a report that could easily be passed along to an accountant or filed with the IRS. In essence, $1 trillion worth of food goes to waste each year, while at the same time, millions of individuals go hungry, which sucks. Our goal was to create a platform to incentivize more businesses/individuals to donate left over food by making it much easier to file the donation as charitable giving and by connecting them with charities to collect the food. We would then take a percentage of the newly created tax deductions. After a long 54 hours, all of the teams were given 5 minutes to present their project and an additional 5 minutes for questions from the panel of judges. We were content simply with the final product that we created, but were ecstatic when the judges awarded us first place. My educational and entrepreneurial journey has been filled with a lot of highs and lows, but it always feels great to have a respected and accomplished group of individuals acknowledge your hard work. Along with receiving a first place trophy, which was printed on a 3D printer during the weekend, we were also awarded with a spot in the B-Start Pre-Accelerator Program, a 3 month free partial membership to Cowork Btown, a free consulting session with the IU Intellectual Property Clinic, a free pack of Uel Zing Coffee, and consultation time with The Gayle & Bill Cook Center for Entrepreneurship and the south central Small Business Development Center.

Overall, it was an incredible weekend where I learned a lot of new information and was connected with some really great people. It’s hard to tell if anything will end up coming out of the project that began this weekend…

Students Use West Bristol to Host Art Show for Charity

On my way to class today, I received a text from my business partner, Justin, telling me that apparently there was going to be an art show at our shop in downtown Bloomington in a matter of hours. I have been wanting to host an event in our store for a while and was excited to here that two Kelley students, Cydney Mosby and Kendra Gerst, would be using our space to host an art show to benefit a local charity, the Art Alliance of Bloomington, which promotes the sustainability of the creative arts community. Cydney and Kendra came up with the idea of hosting an art show benefit when they were required to demonstrate leadership for one of their classes in Kelley. Using their connections, they brought together nine different artists and showcased their artwork in our store. The event went smoothly and Cydney and Kendra did a great job coordinating everything. (Hopefully they get an A on the assignment.) I would love to host another event in our shop, so if you have any ideas on what we could do next, drop me a line at

I love it when you call me big data

The Notorious B.I.G. Data: What Is Big Data and Why Does It Matter?

Every day I see a dozen new buzzwords in magazines, online articles, and social media, but I am always disappointed when none of the terms are ever able to live up to the hype. I really wasn’t that impressed or excited when I first learned about the term “Big Data” either, but that began to change when I saw more and more examples of how it touches every single part of my life. Big Data is not another short-lived buzzword, but is going to be a leading factor in shaping the future.

A case study that first caught my attention was the example of CellTell, the Congo-based phone provider, that was able to predict massacres in Congo based on prepaid phone purchases. When families in Congo sensed chaos coming, they wanted to protect their personal assets, so they would buy phone cards because it was one of the only things that was valued in US currency, which was safe from inflation, unlike the local currency. Or there is the now clique example of how Target was able to predict a teen girl’s pregnancy before her father. What is so interesting about the analytics behind Big Data is that completely unrelated things can be linked together to make predictions. For example, according to the predictive modeling company Kaggle, someone is the most likely to make their flight if he or she has preordered a vegetarian meal. And if you buy a used car, you should buy an orange one because its owners take the best care of their cars. Although these might seem like odd coincidences, there are a ton of things going on in the backend to make these connections, such as making connections between the physchology of vegetarians combined with the implications of preordering a personal meal on a flight, or linking the odd color of orange for car with the smaller production number of cars and realizing that someone who drives an orange car will take better car of it because the odd color implies that the car is likely used as a form of self expression.
Although Big Data is mainly used commercially to help businesses target their marketing initiatives, humanitarian initiatives have sprung up as well. Although it was eventually deemed a failure, I loved the idea behind Google Flu Trends. The idea here was that Google would be able to track the spread of the flu based on search queries. Even though there are over 3.5 billion search queries on Google every day, search habits and queries aren’t enough to predict the flu and don’t even begin to scrape the surface of everything that makes up big data.
So if Big Data is really so amazing, what exactly is it, how does it work, and why should individuals who don’t work at Google or the NSA care?
When I first started researching Big Data, data science, and analytical tools, I learned that knowledge about it was very marginalized. There was a huge gap between average citizens and data scientists and analysts. Every thing I read was hidden beneath industry jargon, overly complex models, and of course, more buzzwords and concepts that I didn’t fully understand. It’s almost as if the world of Big Data and data science was a secret society that was careful not to let any outsiders in. My goal with this post is to push aside the hype and buzz, and explain Big Data as simply and concisely as possible.
What is it?
Essentially, Big Data is a combination of structured and unstructured data. So it’s just a lot of information, so much information that traditional software and hardware can’t process it. It’s doesn’t only contain standard data, like your name and phone number, but it also includes things like how many friends you have on Facebook, transactional data from when you swipe a credit card, being captured by video surveillance at a gas station, how often you use your phone, your eye patterns when looking at a website or billboard, and more. It is dynamic and real-time information that comes from an unlimited variety of sources. So you can imagine that a lot of data is being created constantly. In fact, more data was created in the last two years than in all of history combined. We’re talking 1.8 zettabytes (10 to the 12th gigabytes) every two days. The term Big Data has also began to refer to the process of analyzing this data, as well as the companies that do so. Although it can be tricky to define, the name itself, Big Data, actually does a pretty good job describing it: it’s really just a ton of data in all different forms.
How does it work?
The reason that Big Data is a thing now is because it’s getting cheaper and cheaper to store information. But before companies can store data, they have to mine it. Some ways are pretty straightforward: we know that Google stores our search queries, but some ways are a little bit sketchier. For example, any website that has the option to “Share” or “Like” on Facebook is sharing that information with Facebook, even if you don’t hit either button. Many mobile applications also use services like Tea Leaf, which actually records video of your screen when using an application so that analysts can play back the video to improve the user experience. It is not uncommon for companies to leave Floodlights embedded in the code of their website to capture/report the actions of users after visiting their website. Although many methods for extracting data do raise concerns about cyber security, they are mostly used for harmless attempts to advertise products.
After data is mined, it is stored in a enterprise data warehouse, or some other form of database. Think of it like any other warehouse, only the product that is being stored is data. The big boys, like Google, use ridiculously expensive super computers to store and analyze data, while other big companies run NoSQL and Hadoop. In my opinion, this is by far the most boring part of Big Data, but it’s still extremely important because the whole system wouldn’t be able to work without it. Basically, NoSQL uses an agile approach, which means that everything is always a work in progress, with dynamic schema. So it’s a very fluid and constantly changing process. For Hadoop, instead of storing everything on one super computer, it spreads data across many computers. An example that I really like to describe the dynamic, agile approach to Big Data is the example of trying to find a good free throw shooter. Traditional data analysis would tell tell us that to find a good free throw shooter we should have everyone shoot 1000 free throws and then select everyone who makes at least 900 of them. The problem here is that it is not only impractical, but it takes a lot of time. With the dynamic approach for big data, it assumes that everyone is a great free throw shooter and as more data is collected, it will either prove this assumption true or false. With each individual free throw that is shot, it allows us to make a prediction based on that moment in time. As more data is added, the predictions become more and more accurate.
Why should I care?
If you own a business, hopefully you see the advantages that data can have to increasing your profitability. Most people don’t have access to super computers or other high end data tools, but even free tools, like Google Analytics or Excel, can allow you to target your marketing. You can test digital ads to see which are most effective or store data in Excel and do simple computations to find customers that have not been engaged with your company for a long period of time to send them marketing materials to reengage them. You can use heat maps on your site to see where users are engaged on your site and where they ignore content.
If you don’t own a business, you should still care about Big Data, as it will create 1 million jobs directly every year and 5 million jobs indirectly. If you can understand a little bit about Big Data, you instantly become a more valuable employee.
Great Tools to Use
This is a really cool tool that allows you to see how people are engaging with your website and where they are clicking on the site. The best part is that the normally $100 monthly fee for a premium account is waived and it is free for students, teachers, and charities.
Data Camp allows you to learn every thing about programming, data visualization, and data science. The courses are really interactive as well, and the first can be started for free. After you complete a course, you are given a certificate, which can help sweeten up your resume. After doing the first course for free, it is $25 a month, but you should be able to get at least one certificate in the first month.
3. Lynda
If you are a student at Indiana University, you should be using this free service. It is crazy that IU gives us this for free and allows you to receive incredible training for almost anything that has to do with data and IT.

“And if you don’t know, now you know…”
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My October Playlist

Every month, I will share some of the music that has been inspiring me. Check out 12 songs that have been fueling me this past month.


Here is the track list:

  1. Quiet Achiever – Yeo
  2. Waves – Miguel
  3. Adderall (Gazzo & Sweekuh Remix) – The Heydaze
  4. Don’t Wait (Remix) – Mapei, Chance The Rapper & The Social Experiment
  5. My Type – Saint Motel
  6. Hotline Bling – William Singe
  7. Back At The Start (Ft K. Flay) – Viceroy
  8. Down on My Luck – Vic Mensa
  9. Your English is Good – Tokyo Police Club
  10. When I See It – Kanye West
  11. The Message – Grandmaster Flash
  12. So Demanding – Bag Raiders