There’s no time like the present to get into this hot field
There’s no shortage of the need for skilled data analysts and data scientists. A quick look at the Bureau of Labor Statistics confirms this:
Employment of computer and information research scientists is projected to grow 15 percent from 2019 to 2029, much faster than the average for all occupations.
“Rapid growth in data collection by businesses will lead to an increased need for data-mining services,” the site shows. “Computer scientists will be needed to write algorithms that help businesses make sense of very large amounts of data. With this information, businesses understand their consumers better, making the work of computer and information research scientists increasingly vital.”
“Some key concepts [learned in the certificate] that I apply are visualizations using R. I build ETL pipelines, do a lot of data wrangling and visualizations using R, as well. I help my company understand who our customers are and why would they come back to CPWM, so my directors can make better decisions toward building better customer loyalty and retention.”
— Graduate Swathi Annamalai, senior data scientist at CostPlus World Market
Interested In a Job in Data Analytics?
If you’re thinking about making a career change to data analyst, you should take an analytical approach to evaluating this field’s fit with your career dreams. Think of this as the pre-assessment stage: Just because data analysis is a popular career doesn’t mean it’s the right career for you.
Yes, I’m Ready to Learn Data Analytics
Check out your options:
Seema Singh Saharan, M.Phil. Mathematics (Operations Research), is an instructor at CSUEB, UC Berkeley Statistics Department and UC Berkeley Extension.
She has taught operations research, quantitative techniques, mathematics for management, computer programming, algebra, statistics and biostatistics, as well as Statway courses by the Carnegie Foundation. Saharan has worked as a software engineer on commercial and scientific projects using programming languages such as MATLAB®, R, C and Java. Her thesis explored simulation and inventory control. In this data-driven world, she is keenly interested in data science, biostatistics and big-data machine learning techniques.
So You’ve Got Skills in Data Analytics. Now What?
Companies are looking at how to best leverage the vast amounts of data at their disposal and — perhaps more importantly — how to correctly analyze those data sets to make informed business decisions.
But it’s still a bit breathtaking to see where you can go in your career, almost any career, by mastering data.
“I use R to perform statistical analysis on experiments that I run in the lab [at Amyris, a renewable-products company]. The data science skills I learned allow me to create useful data visualizations and reports to share with my colleagues and stakeholders.”
— Graduate Joseph Walker, scientist at Riffyn