Are Programmers Headed Toward Another Bursting Bubble?
Staying relevant in the ever changing technology landscape can be a challenge. By looking at the technologies that are replacing programmers in the status quo we should be able to predict what jobs might disappear from the market. Additionally, to predict how salaries and demand for specific skills might change we should consider the growing body of people learning to program. ...
“[P]ublic ignorance” about computers is keeping wages high for those who can program and the public is becoming more computer savvy each year.
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“Business Intelligence” tools such as SalesForce, Tableau and SpotFire are also beginning to occupy spaces historically held by software engineers. These systems have reduced the demand for in-house Database Administrators, but they have also increased the demand for SQL as a general-purpose skill. They have decreased demand for in-house reporting technology, but increased demand for “integration engineers” who automate the flow of data from the business to the third-party software platform(s).
A field that was previously dominated by Excel and Spreadsheets is increasingly being pushed towards scripting languages like Python or R, and towards SQL for data management. Some jobs have disappeared, but demand for people who can write software has seen an increase overall.
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In many ways data science looks like web development did 5–8 years ago — a booming field where a little bit of knowledge can get you in the door due to a “skills gap”.
As web development bootcamps are closing and consolidating, data science bootcamps are popping up in their place. Kaplan, who bought the original web development bootcamp (Dev Bootcamp) and started a data science bootcamp (Metis) has decided to close DevBootcamp and keep Metis running.
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Another big group of newcomers to programming are MBAs and data analysts. Job listings which were once dominated by Excel are starting to list SQL as a “nice to have” and even “requirement”. Tools such as Tableau, SpotFire, SalesForce, and other web-based metrics systems continue to replace the spreadsheet as the primary tool for report generation. If this continues more data analysts will learn to use SQL directly simply because it is easier than exporting the data into a spreadsheet.
People looking to climb the ranks and out-perform their peers in these roles are taking online courses to learn about databases and statistical programming languages. With these new skills they can begin to position themselves as data scientists by learning a combination of machine learning and statistical libraries. Look at
Metis’ curriculum as a prime example of this path.