Understanding Big Data

Friday, July 31, 2020

Since the beginning of the digital age, there has been an eruption in the amount of data generated and collected in the past years. This is due in part to the creation of computers, the rise of the Internet and the growth of technology that takes real-world information and converts it into digital data.   Big Data is a term used to describe the large amounts of both structured and unstructured data that businesses interact with on a daily basis.   Examples of Big Data include:

  1. Unstructured Data: email and messenger communications, word documents, videos, photos, audio files, presentations, data from social media
  2. Structured data: information with a high degree of organization; examples: spreadsheets, catalogs, machine-generated, weblog data, programmatic, other

  Though the term big data is still comparatively new, people have been gathering and managing large amounts of data and information for a long time. Today’s mainstream definition of big data is defined by the three Vs:

  • Volume: Organizations gather data from many various sources, from business transactions and social media to sensor and machine-to-machine data. New technologies have allowed organizations to better store this data in large quantities.
  • Velocity: Data streams come in at high speeds and in large amounts. It must be organized quickly and efficiently to stay on top of it all. RFID tags, sensors, and smart metering are some of the technologies used today to help organize waves of data in near-real-time.
  • Variety: Data comes in many and all types of forms. It can come in as structured, numerical data in traditional databases or as unstructured text documents, video, email, audio, etc.

  Why Big Data? Today, the quantity of data and information that is created, gathered and stored around the world is unbelievable. And yet, it’s still growing. This massive growth in big data allows organizations more potential to leverage key insights from the business information to benefit their organizations. Big data shifts the way that organizations today analyze information. It allows us to quickly and efficiently analyze and gather information from any type of data, structured or unstructured. It also allows us to examine any information from any source, from words to locations, and turn it into usable data that helps organizations make better decisions. For example, using and analyzing the data allows you to find solutions that could enable reductions in time and cost, help new product development and optimized offerings and help the organization make better decisions.   However, big data is not only about the volume of data. What matters is how organizations use the data. It’s about effectively managing the business events while they are still occurring and using big data to obtain insights that help the organization make better decisions and smart business moves. Currently, big data is used across every and all industries, from banking, education and the government, to healthcare, manufacturing, and retail. Bankers can use data to help them minimize risk and fraud and stay compliant with regulatory requirements. Teachers and educational institutions can use big data to monitor student progress and identify at-risk students. The government uses it to gain insights on managing utilities, running agencies and preventing crime while retail use it to find new ways to market to customers and handle transactions effectively.   Big Data is extremely beneficial to organizations because it gives them access to a wide variety of information they may not have access to otherwise. With the help of big data, you can know more about anything or any situation, what your clients are interested in or what current sales trends are like. This collection of data allows you to analyze and compare so that you can make predictions for the future, make more informed decisions and identify emerging trends and relationships that may have otherwise been hidden. One slight issue though is that big data only allows us to identify a correlation between two or more items; it may tell us WHAT is happening but doesn’t always indicate WHY it is happening.  

Last year (2017) surveys by GM, IBM and Accenture found that on average, of the companies that are using big data, 92% of executives are satisfied with the results and 89% rate big data as “very” or “extremely” important. Similarly, 89% of respondents who have implemented at least one big data project see it as a way to revolutionize business operations, and 85% believed big data would dramatically change the way business is done. 84% of companies believe big data analytics will “shift the competitive landscape for my industry” within a year and 87% believe that will happen within three years. In addition, 89% believe a lack of big data adoption will create a risk of losing market share, and 75% see growth as the key value of analytics.

  Overall, big data has revolutionized the way we collect, look at, and use information. The insights that come from big data then allow us to make better, more informed business decisions. Today, big data is used across all industries, from banking to education. However, while big data shows the correlation between data points, it doesn’t necessarily tell us why something is happening. With the rise of big data, we are left wondering whether it is really more useful than conventional analytics like data warehouses and whether we have the right tools and technologies to truly leverage big data. While there is no real answer to these questions yet, big data is an important trend for organizations to consider, especially moving into the future.

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