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What is big Data?
Big data is a massive collection of both unstructured and structured data and that keeps growing exponentially. Another characteristic of this big data is that it is complex and the traditional data management tools and processes cannot process it efficiently.
Some examples of big data sources
- Social media: The social media platform is one of the most popular online platforms that billions of users across the globe use on a daily basis. These media platforms generate massive amounts of data. The type of data collected by the social media servers takes the form of photos and videos, including text messages.
- The New York Stock Exchange: This trading platform in the United States is one of the busiest trading exchange centres globally. On a single day, the trading centre is known to generate more than one terabyte of data.
From these two examples alone, it is clear that these are huge amounts of data that these two sources collect and process every single day.
List the Three types of Big Data
Generally, there are three types of big data. These include:
- Structured data
- Unstructured data
- Semi-structured data
The history of big data
The processes of accessing, processing and storing huge amounts of data have been around for quite a while. However, the concept of big data has been used in mainstream, discussions since the early 2000s after Doug Laney popularized the concept and defined big data based on three factors. These three factors include:
- Volume: data collection takes place from multiple sources such as mobile devices, social media, videos, pictures, etc.
- Variety: The data comes in all forms of formats such as numeric, photos, videos, text, structures, etc.
- Velocity: The speed of data accumulation is huge and demands timely handling as well.
These three factors are basically dimensions of data that help define big data. When data meets all these three factors, it can comfortably be defined as big data.
Why big data is important
Big data is increasingly proving important to organizations around the globe. After careful processing and analysis of the data, organizations can benefit in the following ways:
- Determining the causes of failures, defects and issues as soon as possible.
- Helps an organization in the recalculation of risk portfolios within a short time.
- Helps in improving learning models and ensuring better data classification and accurate reactions to changing variables.
- Helps in early detection of fraudulent behaviour in an organization and addressing it on time before it grows or causes more problems.
- Helps in spotting any anomalies in the systems faster than a human eye can.
The future of Big Data
Big data is increasingly playing critical roles in today’s business operations globally. All industries now rely on data to make accurate decision-making and in this regard, big data has become a key player in determining the direction of business operations. The increasing usage of Internet of Things devices is seeing more information collected and stored. The obvious advantages from the use of this information are seeing more appreciation of big data. The use of machine learning and Artificial Intelligence in analysis of big data is set to revolutionize big data in the future.
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