Malaak Blog

 Chapter 8 demonstrated the power of visualizing your data. Numbers by themselves are data, but when you start to organize those numbers into graphs, dashboards, and trends you begin to turn that data into information. I love how Tableau allows you to easily identify patterns, comparisons, and time series. It drove home to me the importance of presentation when it comes to making business decisions. Analyzing your data is great, but only if it can be done in an easy to read and understand format. My favorite part of this chapter was learning about how Tableau is extremely easy to use, yet still has robust features. With just a few clicks you can drag and drop fields to create powerful visualizations. I also love all of the features that Tableau has such as blending data, creating calculated fields, inserting trend lines, and creating interactive dashboards. I love how the stock market example and UFO example from this chapter took a simple set of data and turned it into something y...

  In chapter seven we learned about Looker Studio (previously Google Data Studio).  Honestly I did not think a free tool could be this powerful.  Prior to reading this chapter I assumed you needed to have a paid software program or know how to code at an advanced level in order to visualize your data.  I think my favorite part about Looker Studio is how user friendly it is with the ability to just drag and drop things on the page.  Learning that you can take raw data from Google Sheets or Google Analytics and turn it into something as impactful as an interactive dashboard really made data less scary for me.  It allowed me to realize that visualization is about telling a story with your data in a way that’s easy to understand. I also enjoyed how the chapter broke down Looker Studio vs Tableau.  I liked that it was very clear about Looker Studio being free and allowing you to connect to other Google products you might use.  While Tableau is great it...

 For this week’s blog post, I actually sat down to try one of the tools we learned about rather than simply reading about it. I decided to use DALL-E and thought it would be fun to see how my grandparents would react to this tool. I had my grandpa sit down with me, and I explained that this tool creates pictures based off of words you type. He didn’t quite believe that it would work and thought a computer wouldn’t be able to create something from a description alone. I asked him to describe his farm from when he was younger and specific, and we both typed it into the tool. As soon as the picture popped up he was genuinely shocked that the tool was able to create something so similar to his description. He kept commenting on how it reminded him of home growing up, particularly the red barn and open fields. What really stood out to me was after he got over the initial surprise he began to ask if we could change the color of the sky or add certain animals. Having to teach him made me ...

What really stuck with me from Chapter 6 was the overarching idea that food policy shapes the health of our nation. I always thought of health from an individual perspective; you are only as healthy as the decisions you make. Do you read nutrition labels? How often do you eat fast food? How often do you exercise? What you may not realize is that policies are being made at the federal, state, and local level that determine what food is available to your community, how much it costs, and how it is being marketed. When you think about policies such as SNAP or school meal regulations, it is a direct reflection of how our society wants to address health disparities. Until reading this chapter, I never fully thought about health past the individual level. The first topic that I found interesting was how farm subsidies impact our food system. I had no idea that subsidies were given to certain crops and not others. When specific crops like corn and soy are subsidized, it lowers the cost of ing...

What really intrigued me about chapter 5 was seeing how data analytics leads to insights that can be used in business decisions. Specifically, I found data driven marketing very interesting. Using customer data to allow for more personalized targeting of customers was something I hadn’t thought about. Companies can utilize past buying behavior, preferences, and actions to better personalize ads and campaigns. I think BeautifyMe gave me a great example of how even small improvements can have visible effects on conversion rates. Predictive analytics and its use in supply chain management was another section I found particularly interesting. Using historical data to more effectively predict future outcomes can prevent problems such as overproduction or wasted resources. I thought EcoFood was a great example of how predictive analytics can decrease waste and improve sustainability. The wide range of applications for customer segmentation and risk management also caught my attention. Seeing...