What is Big Data?

Big Data technology makes totally new business models possible as well as the introduction of new products or services.

Big Data has always been an important resource in all industries. Since the beginning of the information age, business intelligence and descriptive statistics have been used as standard tools to pull out information and to make all types of important decisions.

But now, however, the costs of collecting, storing and processing data have decreased and the amount and differentiation of data has reached a point where it’s no longer possible to handle this is in a traditional way.

New techniques and tools

The term Big Data is therefore often used to describe the fact that new techniques and tools are needed to process and analyze data.

A more formal definition of Big Data was introduced by Gartner in 2012 based on the 3V’s – Volume, Velocity and Variety. Since that time the 3V-model has been expanded to include a fourth V for Veracity and, more recently, a fifth V for Value.

Without explaining the V’s in depth, we can also view Big Data from the new set of technologies which contribute to solving challenges in collecting, handling and analyzing large amounts of data. These technologies include cloud computing and cluster computing (with Hadoop MapReduce as the best-known example) for data storage and manipulation, and machine learning for data analysis.

Creating value

The value of Big Data is determined in two main ways: as a source to analyze, and as a tool for new products and services. In the first, Big Data analyses are used to improve existing business models by giving insight into data which was previously too expensive to store or process.

“Big Data competence yields huge competitive advantages”

Amazon’s recommendation system, USPS’s preventive maintenance system, and Walmart’s prediction system are all really good examples. These companies track, collect and store all available data from customer transactions to social data from GPS-road maps and geographic and meteorological data. They then combine the data and use Big Data analysis to glean meaningful insights. This would not be possible without the new Big Data technologies as e.g. cluster computing and machine learning.

In other cases, Big Data technology makes totally new business models possible as well as the introduction of new products or services. Lots of new so-called “unicorn start-ups” like Airbnb, Über or Snapdeal have been enabled using Big Data Analysis. Their products have unique features thanks to the new technologies they use. Without using this approach, their products would not be able to compete with traditional business models.

Big Data at eSmart Systems

Big Data has been eSmart Systems’ core value and competence from the beginning. Big Data analysis and machine learning are embedded into most of the product range to predict electricity demand on a transformer level, segment customers based on power consumption patterns and to implement response strategies.

eSmart Systems has also started using machine learning to automatically analyze power grid surveys carried out by drones, to help detect errors and perform preventive maintenance.