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Big Data COMP683

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By Karla Rangel Garcia January 27, 2019 - 8:35pm

In recent years, new technologies / methodologies have emerged that people tend to think that they’ll fix many things. As mentioned in Linden and Fenn at the beginning of the curve many customers have been confused thinking that technologies such as IoT, Blockchain, Big Data Analytics among others will do wonders for their business, for which a lot of money is invested but could be wasting. These technologies are the ones I hear most often, however, people often confuse these concepts with miraculous solutions that will fix every company problem.


Being very specific, I'll talk about the supply chain at IBM. Like any process, this also has areas of opportunity, the raw material is expensive, customers have many channels to solve different problems, there is a lot of bureaucracy, etc. When the IoT technology started, we were all looking for applications in our processes. To our disappointment, we saw that it was a very expensive solution and the cost benefit would not be justified. Since then, the following technologies, for example, Data Analytics was taken with more reserve. Nowadays this technology is in high demand, which is why we are first seeing how it will really benefit the clients (internal and external), what processes could be applied and, above all, how can we offer a high-value integral solution?


IBM is a very large company, it has all kinds of internal processes and works with companies from different areas. To answer the question of what would you do? I will focus on a specific area: supply chain. The first step is to be very clear about the process of the chain and choose only a part of the chain and then scale it along the other areas. In my case, I would focus the efforts on a single product that is shipped to a specific client. This will lead me to have three main users connected: 1) client, 2) IBM, 3) carrier.

Algorithms will be very helpful, since we don’t need to understand how it works, only make sure it does. However, this is not enough for many fields that are trying to understand how the amazing amount of information could be processed in a way it’ll not only prevent undesired things to happen, but it’ll help make sure the right things happen. An interesting example comes to my mind, setting companies’ perspective aside, which is the analysis of students’ behaviors. If data is analyzed correctly professors may take action early enough to help the student have a successful learning process.


A. Linden y J. Fenn. (2003). Understanding Gartner's Hype Cycles . Mayo 2018, de Gartner Sitio web:

B. Marr. (2018). How Blockchain Will Transform The Supply Chain And Logistics Industry. Mayo 2018, de Forbes Sitio web:



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