You have probably heard the popular quote “Data is the new oil”. Organizations need data to help transform their business  as well as individuals and government parastatals to improve the lives of her people. Imagine the good that could be done with all of the data we have.

A lot of people are interested in big data and often wonder how to go about it. One common question is; What area should I specialize in? I asked myself this very question 🙂 . I spent a good chunk of time looking at resources on how to become a data scientist but soon realized with my background the advisable path was that of a data engineer.

Big data has different paths which includes Data Analyst, Business Intelligence Analyst, Data Architect, Data Engineer, Data Scientist, SQL Developer, DBA, Data Warehouse Developer, e.t.c. Often times people tend to confuse roles of a data Scientist and data engineer. They have an overlap but one cannot take the place of the other. Now, the questions; what skills do I need?

Data Scientist:

• R Programming
• Statistics
• Machine Learning
• Deep Learning
• Natural Language Processing

Data Visualization:

• Tableau
• QLik
• Microsoft Power BI
• Data Storytelling

Data Engineer:

• Hadoop
• NoSQL
• Scala

OverLap Skills:

• Python
• Java
• SQL
• Spark
• Linux
• Git
• Agile methodologies: Confluence, Jira…

Note: Some of the skills listed in the overlap section above are needed by Data Analyst and Data Architects. An example will be SQL to data analyst,  Linux and some level of coding skills to the architect. I also think everyone needs to understand agile methodologies as this will go a long way.

Learning Resource: Check out Cognitive Class I encourage this because the teaching is easy to follow and you earn badges that can help you as you try to find a job and it’s FREE!!!. Please feel free to share other amazing learning resource you know.