The term “Big Data” refers to present and future data sets that are much greater in size than the data sets that preceded them. These data sets are also considerably more complex than other data sets from the past. They are also being received at faster rates than ever before.
The term was coined to describe the present phenomenon in which the size of data sets is continuously growing. This uninhibited growth of volume, velocity, and variety of this data makes it difficult for existing databases to capture, manage, and process the data.
Big Data provides organizations with an opportunity to use their massive stores of data to gain more insight, perform better decision making, and compete with other organizations.
The three Vs of Big Data
Big Data can be defined using its specific attributes. These are referred to as the “Vs” of Big Data. The attributes that are observed and studied most frequently by those that work with Big Data are volume, velocity, and variety. Let’s take a look at each one.
When working with Big Data, organizations will have to learn to process increasingly large volumes of low-density, structured data. A lot of this data may not be of much value today, but it could prove to be useful in the future. Sources of this data can include social media feeds, devices with sensors, and clickstreams on web pages.
The velocity with which data is being delivered is always increasing. This could cause problems for existing data management software that have to deal with the ever-increasing rate at which data is being received and has to be processed.
The variety of data being handled when working with Big Data is also far larger than ever before. Traditional data used to be structured and fit into existing databases without problems. Big Data on the other hand, deals with unstructured data types such as text, audio, and video. These data types have to be preprocessed before they can be used for other purposes.
Uses of Big Data
Big Data can be used in a growing number of ways by organizations in different industries.
Creating predictive models
Some companies use Big Data to anticipate customer demand by building predictive models for new products using attributes and the historical success of previous products. The data sets used in these models tend to be very large and are difficult to process using traditional analytical tools. This is has led to the development of newer analytical tools that are comfortable processing and analyzing Big Data sets.
Improving user experiences
Big Data is also used to gather customer experience data from social media, web page visits, and other sources to improve user experience on these platforms. The volume of data being obtained from these sources is continuously growing, which creates challenges for those that are gathering this data. Organizations that can handle the high volume and velocity of this Big Data can develop a better understanding of customer behavior.
Big Data can be used to recognize abnormal patterns and behaviors in data sets. These abnormalities are often detected by analyzing large data sets and are typically indicators of fraudulent activities. Big Data is set to change the way we use data in the future. Organizations could benefit by learning more about the concept and utilizing it in their proceedings.