The birth of the data programmer

bridgwatera | No Comments
| More

The term "data programmer" now appears more readily on job posting boards serving the software application development community.

More accurately, the job tends to be referred to as data programmer / data analyst.

A random job listing taken today reads:

"The Data Programmer / Data Analyst must be a flexible team player able to use skills in programming and software development, data mining, as well as database management. Work directly with client managers and technical staff to understand business problem, develop predictive models and deploy/implement models into client database/data warehouse system..."

So will this role require new agility and/or skillsets of the individual?

ReadSoft UK's Adam Chapman says that we need to have some way of joining up all the data sources we face today and be able to get a single view of the information within the business -- and that this is the task ahead for the data programmer.

"This means extracting data in a meaningful way from any format of document, tagging it and processing it so that business analytics can then be applied in a meaningful and valid manner," said Chapman.

But while data control (tagging and processing) skills are important, so are modeling and management competencies.

Modeling and management

Anthony Saxby data platform product marketing manager Microsoft UK argues that analytics is increasingly being used to assist organisations in making decisions through the application of modelling to determine response to trends, identify underserved segments and pursue opportunities for product innovation.

"Whilst a level of analytics has always existed in the computer industry -- in fact the very first application developed for computers was for rudimentary weather forecasting -- the wide availability of huge amounts of processing power and storage has opened opportunities for even the smallest organisation with the required foresight to use data to build a deeper understanding of where to direct their attention."

Deeper circumstantial challenges

SMB owners take note, that was "even the smallest organisation" there, but there are deeper circumstantial challenges ahead.

F5 EMEA product manager Nathan Pearce argues that the key to using data analytics effectively is context.

"There's a huge amount that can be understood about the user and usage -- such as time of day, geographic location, access policy, device, operating system etc. -- to better understand a business and its customers."

"This information can be used to optimise the experience every single time, by routing traffic internally to serve up the app to an end user in the right way. At its most basic level, for example, mobile devices can be directed to a separate web server for a mobile interface while sending desktop connections to full-function applications that are expecting users with full screens and high-speed access," said F5's Pearce.

So the new data programmer cum analyst has a big role ahead. The need to understand what "type" of data the data in hand is will be key.

Access, security, control, contextual meaning and interpretation, wider system management and database connection point skills will all come to the fore now.

This is going to be a tough (although interesting job) -- the annual salary indicator below shows that pay is going up in this sector, but perhaps not enough if we take on some of the vendors' comments above.

a data.jpg

Leave a comment

About this Entry

This page contains a single entry by Adrian Bridgwater published on June 18, 2013 7:48 AM.

SAP: analytics builds "almost neural" future computer systems was the previous entry in this blog.

IBM and Microsoft build cloud application lie detector is the next entry in this blog.

Find recent content on the main index or look in the archives to find all content.