• Dan Meyer

My Experience Training with Sonic Analytics (Part 1)

Updated: May 27, 2019





We create data everyday.


How?


We, especially in this generation spend many hours in accessing our social media accounts, doing online shopping, playing games, watching movies online. Part of our daily routine includes internet and technology. By doing so, all of our hobbies generate data that are captured in various places and in different ways.


Every time we post pictures on Instagram, rant something on Twitter and post our status and photos on Facebook, we create a lot of data. There is a corresponding data point every time we comment or like something online. Imagine how many data we can generate everyday if every person of this planet accesses online.The data become closer and closer to infinity.


That is why the term “big data” was created.


With that being said, data analytics is key to handle pool of data. Analytics is about searching for clues that will enable us to find answers to our problems. We find, we analyze and we present our data.


Primary people for conducting analytics are called analysts. The problem would be that they are overwhelmed by massive amount of data and have trouble to handle them properly.


In order to be effective, analysts should master effective and current business intelligence (BI) tools that could help them to interpret the data properly and guide the companies and businesses regarding their strategies and decision making processes.


I started having interest in dealing with data when I was 3rd year in college.

Before, I was a Math person. I am the kind of person who likes challenging activities and work on complex subjects. In the pursuit of my Economics degree, I used a lot of data and created graphical representations in order to survive essay crises and  loads of research papers.


Somehow, economics has the same idea as data analytics which is to tell a story out of the representations. The difference lies upon the frequency of the usage of business intelligence tools in data analytics.


Why did I dive into data analytics?

Continue Reading Part 2

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