The Data Dimension

  YOU HAVE NOW ENTERED THE DATA DIMENSION. WE HOPE YOU ENJOY YOUR STAY. My Preferred Information World The information world I want to live in will promote accessibility, equity and inclusion, and will foster an environment where diversity is welcome. We can use information systems to meet goals of a world that is more accessible, equitable, and inclusive. Let’s start with an example of an information system that while benefiting me, was not accessible, nor equitable, nor inclusive.  About a year ago, my very first Microsoft Surface which I had for about 2 years would constantly run out of battery, basically it would go from 100% charged to <10% within 30 minutes. I was able to discover that the battery was starting to fail by running the energy report on the laptop. The report clearly indicated that the battery needed servicing. In this case the information system worked in my favor because it provided me with the necessary information to make a decision whether to get the...

  YOU HAVE NOW ENTERED THE DATA DIMENSION. WE HOPE YOU ENJOY YOUR STAY.  Well, we’re finally back! Sorry for the absence of articles, I was dealing with a medical situation.  So anyway let’s hop right back into the data dimension! So how can we use data science for something that can benefit society at large? Nonprofit organizations can use data to make large strides towards solving social issues. But it isn’t very straightforward for nonprofit organizations to do as they cannot afford to hire data scientists to help them the same way large companies, like Apple or Microsoft for example, can. But if nonprofits can afford to hire data scientists, just imagine the massive strides that could be made! I serve as a data analytics lead for the nonprofit organization ClosingTheDivide and we use data to gauge the demographics of those who donate e-waste so we know what demographic to market towards so we can collect more e-waste and refurbish and distribute these devices to low-i...

    YOU HAVE NOW ENTERED THE DATA DIMENSION. WE HOPE YOU ENJOY YOUR STAY. Data Science and Music The pandemic has without a doubt affected all of us in some way or form. But one question that I’ve had is whether it’s translated to the music we listen to as well. Did the pandemic affect the music that we listened to? During the summer, I’ve been working with an MIT student on a data science project. The project in particular poses the question “Did the pandemic affect the types of music that we listened to?”. This question allows me to bridge together my love for music and data science. For this project, I plan on using a code that looks at certain lyrics of the biggest songs, and based on that analyzes whether a song is more happy or sad. There are already algorithms that do something similar. Spotify is able to take a song’s audio features and analyzes those to recommend similar songs to a user. From a data science article that I’ve read, Spotify looks at a song’s acousticnes...

  YOU HAVE NOW ENTERED THE DATA DIMENSION. WE HOPE YOU ENJOY YOUR STAY. Data Science In Our Everyday Lives Data science is something that is used very often in our everyday lives. It allows us to analyze trends in what consumers may buy. This, in turn, lets companies know which of their products is the most popular, allowing them to profit more. Data science is also used in the music industry and entertainment industry. Upon researching an article discussing this, I’ve found out that streaming services such as Spotify and Apple Music provide data about its users’ listening habits and where they are located. This allows for artists and record labels to know which songs to promote as singles and in what locations. It can also reveal which genres cater to different audiences the best. This is important because promoting songs that audiences resonate with more allow the songs to be more successful. That is an explanation as to why you may find some songs that sound similar when you tur...

YOU HAVE NOW ENTERED THE DATA DIMENSION. WE HOPE YOU ENJOY YOUR STAY. Structured Data vs Big Data Data is essentially any information that can be stored on a computer. Some of the most common types of data are characters, strings, integers, floating-point numbers, and booleans. The number of visitors to a website is considered data. Even something like your name is considered data. There are two more types of data, though: structured data and big data. How do you differentiate these? That isn’t something that comes very easy, since even structured data can fall into big data at points. That said, there are a few key differences. If you’re already familiar with structured data, then this blog post should provide a nice transition into big data. Let’s start off with structured data. There are other types of data like semi-structured and unstructured data, but let’s just focus on structured data for now. It's a type of data where you know the structure of the data well in advance so y...

YOU HAVE NOW ENTERED THE DATA DIMENSION. WE HOPE YOU ENJOY YOUR STAY. Data Science vs Data Analytics So, data science and data analytics are terms that are constantly confused with each other. Who can blame anyone? They both have the word data in them and they both seemingly are about similar things. There are even terms like “big data” and “data mining” - even some experts conflate these terms sometimes! Being someone who is exploring the field of data science, I wanted to get these terms down and get to the bottom of what differentiates them. I mean, I have to know what I’m getting into here, and if you plan on going in this field too then so will you! So let’s start data analytics. It’s about examining large data sets to identify patterns and create visual representations of the data to help companies make better business decisions. In a nutshell, it’s essentially what it says - you are analyzing the data and using it to help people. As a career, data analysts do different things in...