What is Big Data? Many people, including those in the financial and technology industries, have at least heard the term “Big Data” in reference to advanced statistical analysis and/or exploratory data mining techniques used by marketers, investors, and decision makers in their respective fields. However, few individuals truly understand what exactly is meant by “Big Data” or what its potential uses are. For those people who have been involved in industry-related discussions on this topic, there is usually some confusion regarding what is meant by “Big Data”, particularly as it relates to its potential applications and impacts upon industry sectors and businesses. Thus, this article seeks to address these questions and clarify the potential uses of “Big Data” in today’s ever-changing and demanding business environment.
What is Big Data? In simple terms, Big Data is a discipline that utilizes various techniques to explore, analyze, or otherwise address huge data sets that are simply too large to be handled by traditional statistical analysis or machine-based software programs. In the last 10 years or so, the term “Big Data” has gained increasing prominence, as a result of the significant advances in digital technology, particularly the widespread availability of cloud computing and its ability to leverage a multitude of networked devices for a multitude of computing needs. In short, Big Data is now synonymous with predictive analytics, machine learning, artificial intelligence, and the internet’s ability to provide rich, real-time insights. These advanced analytics systems create personalized experiences for end users, tailored to their individual data preferences and profile preferences.
What is Big Data? In addition to providing marketers, investors, business owners and decision makers with personalized experiences, Big Data helps provide them with insights that are not only applicable but are also helpful in making critical business and financial decisions. In fact, a growing number of businesses and government agencies are leveraging unstructured or structured data sets to support strategic decisions and implement action plans. These applications enable quick and accurate insights with the aid of sophisticated analytical techniques and sophisticated engineering tools. However, even though unstructured or structured data sets are considered ideal sources of data for such activities, some amount of privacy is required for certain activities and certain requirements must be fulfilled for the data to be used in the context of these activities.
According to Christopher Freville, VP of Research at advisory firm ID Analytics, “What is Big Data is not only important today, but will be even more so in the future. The Internet of Things (IoT) will help users interact through their clothing, cars, medical devices and other things which we wear everyday. Likewise, the Cloud will provide resources for our businesses and government agencies, and will become a common language for everyone.” Similarly, Eric Hughes, CTO of Applied Data Analytics, IBM states, “The Cloud will need to provide access to unstructured and structured data to allow us to make faster and smarter business decisions.”
What is Big Data? In order to understand what is Big Data, it’s necessary to understand what is the difference between traditional data gathering methods and what is being done with social media data. Traditional data gathering methods consist of writing queries on a computer to a database. With the social media revolution however, data is being collected in a completely different way: by collecting data in real time, from user activity within social media sites.
With social media, users themselves decide what is important to them and what is of value to their community; this decision can then be analyzed using advanced algorithms to generate and compare different aspects of that activity. The outcome of that analysis may be very different than what a traditional computer would be able to do, because with traditional computer systems, complex data sets are analyzed using mathematical algorithms. However, what is being done with social media is combining the complex data sets with the human curation process and using what is found to be the best (or at least most relevant) information for each individual.
For instance, with Twitter, data analysis is done by finding high frequency tweets, analyzing them and determining if they are valuable data sets to use or if they need to be discarded. With Facebook, data analysis is done by looking at the types of posts that are being made and determining if they are of value or should be discarded because those posts could be repetitive. These are just two examples of how data analysis can be performed using different tools, and Twitter is just one example of how this can be done.
So what is big data? It is basically unstructured data sets (or more accurately, complex unstructured data sets) that are processed differently than traditional data sets. It is being used in many different areas of business and technology today. Although it was once thought of as a tool used by big businesses only, it is now being used by smaller companies as well. The internet, mobile computing, mobile media and the social media are all creating unstructured networks that are much more difficult to manage.