What to Expect From Big Data in 2015

Big data had quite a big year last year, as Hadoop gained more widespread acceptance and hit Wall Street with a bang. How hard will it be for big data to hold the headlines this year?

Until now, the heaviest users of big data were in the IT department, and much of it has gone toward driving the company’s marketing efforts. In 2015, this trend will change. Big data will be used by human resources, research and development, production, accounting, and other departments to help drive their efforts. Big data won’t remain the sole property of “data scientists,” but will become mainstream.

Sensor Data Becomes More Prominent

Consumers have become accustomed to sensor data being collected on them, and offer little to no resistance to being tracked, monitored, and reported upon. Thank some of the fitness innovations for this—people are used to having their exercise and diet tracked and logged to monitors in the gym or fitness apps like MyFitnessPal. People are used to traffic sensors, people counters in retail outlets and amusement parks, and GPS systems in their cars and on their cell phones. This trend will pick up in 2015, as organizations learn to use more sensors and more sensor data to improve operations and marketing efforts.

Python Surpasses R

R will likely grow during 2015, but the biggest gains will be the bragging rights of Python. This little language has proven to be highly versatile and easy to learn. Useful for web programming, systems administration, software development, GUI development, and scientific applications, Python should overtake R this year and become the go-to language of many big data users.

NoSQL Gains Momentum

The time for the in-memory database has arrived. It offers smarter, quicker search capabilities. In order to prepare, it’s a good idea to begin learning MongoDB or perhaps NEO4j.

Data Viz Skills Become Essential Among Big Data Scientists

As big data gains users and popularity, the need to format the results and predictions of all that analysis will drive the need for workers skilled in data viz. In fact, all big data scientists will need to be able to present this information in easily digested, easily understood form. Fortunately, there are some tools that help with data viz, particularly QlickView (also QlickSense) and Tableau. These software packages have data viz features that make it easier for non-graphic artists to present information in a visual way.

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