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Big Data: what's the big deal?

There was a time not too long ago when data was not such a large part of our lives. Now, we all use data and are impacted by data. We have data plans for our phones and other devices. We talk about 4G and the rate of data transfer. We struggle to stay patient when data does not transfer fast enough or a page online takes too long to load. We use so much data on a daily basis it is hard to imagine what we ever did before data.

Not only big in scale, but also in importance

All this data is the behind the scenes information in the background of our lives. We may forget that it even exists until we are reminded of it due to some error. Businesses, though, have come to live by it. They collect this data, store it, analyze it, visualize it, and make changes based on it. Human behavior is quantified and collected in order for companies to increase their chance at success and to increase their profits.

Big data is not only big in scale (we are talking petabytes and exabytes worth of data), it is also big in importance. In fact, 91% of leaders in marketing believe that brands that are the most successful effectively use customer data to make business decisions.

Multiple factors that impact the flow of data

Big data is a complex side of the business that companies need to learn to manage. It is so complex because it is not always so simple to collect and analyze. There are multiple factors that impact the flow of data: volume, velocity, variety, variability, and complexity.

  • Volume - Machine learning, IoT, and other technologies have increased the amount of things that collect data. This means that the amount of data has increased dramatically. Machines can pull data from computers, mobile devices, business transactions, and basically anything else that can be connected to a network.
  • Velocity - The speed at which data transfers has changed over the years. Now, large amounts of data can be transferred very fast, meaning that businesses need to keep up with the speed and be able to process, organize, and analyze it all at faster rates.
  • Variety - Data is not just a simple spreadsheet. There is a lot of data that is more structured, like numeric data in a spreadsheet or database, but there is also a lot of semi-structured and unstructured data. This type of data includes emails, documents, photos, social media posts, text messages, sensor data, and other sources of data from machines.
  • Variability - Data does not flow at a steady rate. There are some times of the day or certain times of the year when there may be more or less data. For example, during different seasons consumer data may transfer at a higher rate. During a world event, social media data may increase due to a trending topic.
  • Complexity - Most data does not come a from a single source. The data companies have to analyze may come from a variety of sources, using different collection methods, and have different structures. The systems that companies have to analyze data have to sift through it all to find what's relevant and create a coherent message about what the needs to happen to improve profits.

Possibilities with Big Data

Data basically means nothing unless companies analyze it correctly. Businesses that do this see many improvements:

  • They can make better business decisions.
  • They can provide updates about sales and consumer thoughts and behaviors.
  • They can reduce inefficient practices or risks.
  • They can create more thorough consumer profiles.
  • They can improve security by tracking unusual behaviors related to fraud and hacking.

Also read: Tips for using data to streamline processes & increase productivity 

How is Big Data being used? 

Big data is everywhere. But the question becomes, what do companies do with all this data. How do they use it? In almost every industry, companies collect this data and use it to improve their bottom line.

  • Finance - In banking, big data helps companies understand customer behaviors and make them happier. It also helps banks prevent fraud and other criminal activities. American Express has used big data to analyze their customer habits and has identified what factors predict loyalty. They can now identify 24% of all accounts that will close within four months.
  • Education - Big data can help teachers and school systems find out what aspects of the curriculum are helpful, what students are at risk of failing, and how effective teachers and leaders are.
  • Government - Governments at all levels are active users of big data. They collect data about many activities happening at local and federal levels in order to make laws concerning healthcare, crime, traffic, and many other issues. The IRS uses big data to stop fraud, payment issues, and identity theft. Using analytics they have stopped over $3 billion in fraud and recovered over $2 billion in payments.
  • Healthcare - The health system is a complex network of doctors, hospitals, government agencies, drug companies, insurance companies, and consumers. Data helps people at all levels provide quality care and accurate treatment. AETNA uses data from tests to help provide treatment options that will have the most impact, according to statistics. Kaiser used statistics to help lower the risk of blood clots in women who take oral contraceptives. 
  • Manufacturing - Big data helps manufacturers to boost the quality and quantity of their output, while also reducing waste. GE collects data about how their various products operate. They then look at the data and make changes to their manufacturing process in order to create more efficient products. US Express, a provider of transportation solutions for businesses, tracks fuel usage, engine functioning, tire quality, and other driver related data to save millions in operating costs. 

Business decisions based on data

As technology continues to evolve and more things can collect data and transfer it, companies will use more and more data to inform their business decisions. Big data is a big deal and it is not just a trend that will fizzle out soon. We are all a part of the big data system and can learn to use it or risk falling behind.

Tjip-MachineLearningAlso read: The Fundamentals of Machine Learning [whitepaper]

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Maarten de Jonge

Contact Maarten de Jonge

Strategisch Marketing Manager

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