Having fallen in love with the fact that data is powerful, very powerful I mean and enjoying the sessions I have with friends, I find myself writing this blog to essentially get anyone started with data, with little or no skills, one can invest into the journey of understanding data and making sense out of it.
In my data cleaning to machine learning post, I talked about how one must understand the data and what makes up the data. This is the very first step of getting things done in terms of analytics or data science. Because very poor data may lead to poor results such as poor insights or model leading to poor decisions or outcomes.
Data is so powerful, it can change decisions and possible outcomes of these decisions. Therefore understanding and using it in the right way for the right insight is deem very important. Incomplete data or data that contains a lot of missing values can be problematic. So in the bid to understanding data, one must seek to make sure that the data is completed, that is to handle missing values, either by completely removing them or imputing them depending on the features in the data.
Before the great build which leads to a good decision, one must identify the audience and ask relevant questions to get the views that make up the build. With this step, in-depth understanding is crucial. For a machine learning task to predict the house prices, one must ask questions to find out which features in the data strongly correlate to these prices, it will then lead to further feature engineering or not. Also, for visualisation, if building a dashboard based on a senior management level audience, questions asked would influence the builds in a view.
Data can be put as being complex or not depending on time spent to understand and cleaning it. I’m a strong advocate for data cleaning because garbage in, results to garbage out, and that’s not what we want. Once the data has been understood, the result becomes a new story to tell. Let’s build now!
Thank you for reading ❤️❤️. Data is the new world.