The Origins of The Data Analysis Process

Origins of the data analysis process

As a Data Analyst, have you ever wondered the origin of the Data Analysis Process? Well, I've got you covered. So I am currently enrolled in the Google Data Analytics Certification program and today, in one of the modules the topic is the: ORIGINS OF THE DATA ANALYSIS PROCESS - It was fascinating for me to find out the origins of  Data Analysis and that its dates back to the Ancient Egyptians.

Well here is the brief history of the origins of the data analysis process:

Data analysis is rooted in statistics, which has a pretty long history itself. Archaeologists mark the start of statistics in ancient Egypt with the building of the pyramids. The ancient Egyptians were masters of organizing data. They documented their calculations and theories on papyri (paper-like materials), which are now viewed as the earliest examples of spreadsheets and checklists. Today’s data analysts owe a lot to those brilliant scribes, who helped create a more technical and efficient process.

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So far in this program, you’ve learned about analytical skills, analytical thinking, and data-driven decision-making. Based on this knowledge, respond to the following questions:

• Which of your skills and ways of thinking will help you become a successful data analyst?

• Why will these skills help you become a successful data analyst?

Please write a response of 5-7 sentences (100-140 words). When you’re done submitting your response, visit the discussion forum to read what other learners have written, and respond to at least two of them with your own thoughts.

I learnt about 5 Analytical skills which are: curiosity, understanding context, having a technical mindset, data design and data strategy. First I learnt that most data analyst are naturally curious and with curiosity, as a data analyst you can ask the right questions which will lead you to understanding the context of the problem or the business and then having a technical mindset involves breaking down the problem into actionable steps and with data design, I will be able to design a flow or how to organize the data and of course data strategy is the management of the people, processes and tools used in data analysis.

Analytical thinking involves identifying a problem and then solving it by using data in an organized step-by-step manner. The five aspects of analytical thinking are: Visualization, Strategy, problem orientation, correlation and big picture and detail-oriented thinking. Visualization is the graphical representation of of information. Visuals helps a data analyst to understand her data and explain the result visually. Strategy improves the quality of the data that we collected, and then a data analyst uses problem orientation approach in order to identify, describe and solve problems. Correlation is identifying the relationship in the data and finally having a big picture of the problem and how to solve it.

Data-driven decision making simply means using data to make the right decision