Data Analysis with Omar

Data-related jobs have been gaining popularity in the past few years. Many students are aspiring to become data analysts or data scientists; either by taking courses at their universities that relate to those topics (Data mining, machine learning…) or by taking (free or paid) online (coding or theoretical) courses to acquire certifications as proof of their expertise in the domain. Similarly, many professionals are also following the trend.  A career shift into the field of data has become the new normal. However, many do not know how to approach this field after being certified and how to increase their chances of landing their dream job. Therefore, in the following, I will explain what is the easiest way to get a first hands-on experience in the field of data. This will help you highlight your newly acquired skills, from the online coding platforms or theoretical MOOCS that you have taken. What is a portfolio? The term portfolio is highly popular in the arts and creative industry....

Many fresh graduates dream of starting their careers at a Big 4. Their main reasons to join such companies are the title, the money, and the gained experience from working with executives. In addition, the Big 4 companies provide exposure to diverse fields and sectors. Therefore, the work is highly dynamic and less repetitive when compared to the average company.  In the following, I share my personal experience at a Big 4 and what to expect in general when working there. You should read if You are applying or looking to apply for a job at a big 4. Especially if the position is related to data analytics . Who are the Big 4? The Big four refers to the biggest four accounting firms and they are PwC (PricewaterhouseCoopers), KPMG ( Klynveld Peat Marwick Goerdeler ), and EY (Ernest & Young). They are also famous for their consulting departments which are the dream job for many fresh graduates from diverse fields (Business/Econ, STEM, Law...)...

Data-related jobs (data science, data analyst, data engineering…) are the hottest jobs of this decade. Many companies are upgrading their systems so they can benefit from their data. In addition, many people are aspiring to become part of this data revolution; mainly because the jobs are relatively fun and pay high wages. In the following, I share my two cents on this topic mainly due to the questions I see online on whether to pursue a Master’s degree in data and if it is worth it to secure the job. You should read it if You are looking to get into the data field or if you are already in the data field but looking for an extra challenge. Master of Artificial Intelligence When I first applied to my master of Artificial Intelligence, my ultimate goal was to combine what I have learned as a Civil Engineer (in transportation specifically) with what the MoAI is going to offer me. However, I noticed that the job market combining AI and CE is a niche market, where opportunities are either ...

Motivation... Many data analysts create functions or scripts to automate the cleaning of files that they believe come in the same format. However, human mistakes are pretty common when performing data entry. On my daily work I deal with "supposedly" identical datasets, however, the script would run for 2 to 3 files before throwing an error showing that a file is not in the same shape as the others.  Who should read it Any data practitioner, in general. Or anyone looking to enter the field sooner or later. Data Inconsistency In general The biggest frustration for data analysts and scientists is data inconsistency. It adds an extra layer of suffering to our daily work. Why? Because with inconsistent data, not only we have to transform the data into the shape we actually need, but we also have to clean all the mistakes done by others. In short, a clean data that would usually take 5-10mins to put into good shape for modelling or visualization (pivot, stack unstack...), now requi...

Many persons want to become data analysts and scientists. However, not too many people working in that field are telling exactly what to expect. Most videos on YouTube are very vague and made using datasets from Kaggle, which are in many cases clean (general structure), but require filling missing values. At work, the data is ugly . In the following we will discuss why... Who should Read it... Anyone looking to start their career as a Data Analyst and co. How to Read it Fully. Or watch the video on Youtube. Dataset The dataset used in the following, can be considered as something to be expected from a client. It is a real life template, with all the values changed for privacy purposes. Now the issues with this data is that it is considered wide. So it isn't possible to visualize it on Python unless some transformations are applied to it. The ultimate goal is: To extract the year from "Period_2020", th...

Datacamp is an educational platform that teaches coding. However, unlike other coding platforms, the focus of datacamp is on data-related topics. Its mission is to improve the data literacy of practitioners and professionals who are exposed to data (excel files, databases…) on a daily basis. To improve how people deal with data, DataCamp has created a wide range of courses, ranging from working with basic excel sheets to creating deep learning models. Continuing from  my previous post , I decided to write an honest review on  Datacamp in 2021 . While you are reading, keep in mind that this is not a sponsored post by Datacamp. Disclaimer Prepare yourself for the worse; learn more about that  here . This is for you if You are interested in improving yourself as well as your data literacy skills.   My introduction to DataCamp As a Master ...