Tech Talk with Toni

Barnes & Noble's beginnings can be traced to 1873 Today's post is inspired by an article I read about the recent resurgence of Barnes & Noble, the iconic American bookstore chain. As a bookworm, I found the story especially appealing. Back in secondary school, I used to imagine working in a bookstore or a library during summer vacation, surrounded by shelves of book. It seemed like a dream job. Barnes & Noble originally set itself apart with vast, well-stocked stores and an enormous selection of titles. This approach attracted a steady stream of customers and fueled the company’s rapid expansion. But then Amazon arrived, making it possible to order a book with a few clicks and have it delivered to your doorstep. The shift to online shopping left many of Barnes & Noble's stores eerily empty. Enter James Daunt, the managing director of Waterstones, the largest bookseller in the United Kingdom. Tasked with turning Barnes & Noble around, he brought a fresh p...

  How much value are you willing to extract? This week, I once again experienced writer's block. If you had asked me in February, "What would your 40th blog post be about?" I would probably have laughed and shrugged. However, in the midst of not knowing what to do next, I asked myself, "What is Analytics?" and discovered five sub-categories. While constructing a mind map in Coggle, I realized that each type of analytics posed one question and required a specific skillset to obtain the answer. Each answer was assigned a different value, akin to the by-products of a sugar cane distillery. Alcohol is perceived as a high-value product of cane juice when compared to sugar crystals.  Therefore, the value comes from the level of processing rather than the starting materials. With that being said, here are the five questions answered by the five types of analytics: Descriptive: What Happened?  Value: $1.00 Think of a news reporter telling you about past events or curren...

  A simple pie chart that looks like Pac-Man Many people frequently approach me with questions like, 'Toni, how did you get a job in Data Analytics?' or 'Do you have any advice for someone trying to break into the field?'  As someone who was in their shoes just a year ago, I understand the confusion and frustration that comes with trying to find your way in.  While I don't consider myself a data guru, I've gained a reputation as an expert in the field. However, I want to make it clear that I don't have some grand story about how I solved a complex data problem. In fact, I still classify myself as a beginner, constantly learning and using my blog as a way to reflect on the problems I encounter.  Despite this, I firmly believe that anyone can get a job in this field with the right mindset, network, portfolio, and a bit of luck. So, to help those trying to get into the data field, here are six essential points to keep in mind: Excel is now your best friend This...