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Leaving your fears behind, photo on Isha Foundation I am glad to have you for the second part of my career journal. #1: 7 Deadly Fears I Have Faced - Part 1 #2: 7 Deadly Fears I Have Faced - Part 2 <– You are here #3: 7 Deadly Fears I Have Faced - Part 3 They Don’t Know Sh*t About My Great Artwork - The Pride The Fear Of Becoming Arrogant Rather than being tormented by the Fear of Not Being Valued in my early career, I gradually learned the art of tempering the discomfort upon receiving criticism and grew indifferent to others’ opinions. Instead, I shifted my focus towards bridging the gap in knowledge and skills, and extracting lessons from each completed task. I bet that some colleagues might perceive my attitude as an expression of arrogance; however, the truth is quite the opposite. ...

I am glad to have you for the fourth part of my complete guide on data cleaning. #1: Tidying Messy Data #2: Dealing with Missing Data #3.1: A discussion on the Nature of Outliers #3.2: The Origin of Outliers & Detection Techniques #4.1: Where does Data Duplication come from? #4.2: A Practical Tutorial for Data Deduplication <– You are here Can you spot the impostor? - Picture by the author ...

Photo by Patty Vanitas on flickr There are six things the Lord hates, seven that are detestable to him: haughty eyes, a lying tongue, hands that shed innocent blood, a heart that devises wicked schemes, feet that are quick to rush into evil, a false witness who pours out lies and a person who stirs up conflict in the community. — Proverbs 6:16-19 I am glad to have you for the first part of my career journal. ...

I am glad to have you for the first part of my complete guide on data cleaning. #1: Tidying Messy Data <– You are here #2: Dealing with Missing Data #3.1: A discussion on the Nature of Outliers #3.2: The Origin of Outliers & Detection Techniques #4.1: Where does Data Duplication come from? #4.2: A Practical Tutorial for Data Deduplication Photo by Vadim Sherbakov on Unsplash Data cleaning has always been a nightmare that every single analyst has to walk through (like through fire and flames). Although it is a hard pill to swallow, we cannot simply skip this step since the avoidance of data cleaning only brings more miseries to the analyst. ...

I am glad to have you for the second part of my complete guide on data cleaning. #1: Tidying Messy Data #2: Dealing with Missing Data <– You are here #3.1: A discussion on the Nature of Outliers #3.2: The Origin of Outliers & Detection Techniques #4.1: Where does Data Duplication come from? #4.2: A Practical Tutorial for Data Deduplication When you are missing someone, time seems to move slower, and when I’m falling in love with someone, time seems to be moving faster. — Taylor Swift ...

These days, the need of understanding paying users among companies, especially those who operate online solutions, has been arising noticeably. As a result, the business intelligence unit should provide a accurate and insightful segmentation analysis to business units as a required course of action. In this article, I would try to run you through a step-by-step instruction on how conduct a segmentation analysis by using K-means clustering. Figure 1: Photo by John Lockwood on Unsplash ...