The Impact and Importance of Big Data
In business, buzzwords come and go. The concept of big data, however, is here to stay. Today we produce more data than ever, with the formats ranging from audio to text to image. In 2018 there were 33 zettabytes of data worldwide. The International Data Corporation predicts that by 2025 the global datasphere will total 175 zettabytes—equivalent to 175 trillion gigabytes.
What is big data?
The standard definition of big data is ‘data that contains greater variety arriving in increasing volumes and with ever-higher velocity.’ In short, big data refers to large amounts of data that are received at a fast rate and are varied in format.
Big data can be incredibly helpful and insightful for businesses, but only if it is actually examined and processed. Simply collecting it isn’t enough. Surprisingly, only a small percentage of all data is actually analyzed—a field known as ‘big data analytics.’
Why does big data analytics matter?
More and more companies are realizing the importance of implementing big data analytics—and are already seeing results. According to the Big Data and AI Executive Survey 2019 by NewVantage Partners, 62% of the organizations that took part said that they had already seen ‘measurable results’ from investing in big data and AI.
Big data analytics is opening up new opportunities for businesses in many industries—even those that were not traditionally very digital. Here’s how big data is transforming some of our most important industries.
1. The healthcare and pharmaceutical industry
The impact of big data in this industry is extensive. For example, the ever-increasing popularity of wearable devices, such as smartwatches, as well as health and exercise tracking apps results in a large amount of data that, when compiled and analyzed, may offer useful insights for healthcare organizations. On both an individual level and within groups or populations, this data could allow trends to be spotted and could even lead to earlier diagnosis of illnesses.
Patient care can also be improved and personalized by analyzing digital patient records. In the fight against epidemics and pandemics, patients’ health and medication data can provide crucially important information. Yet despite the potential value of this data, in this industry in particular, a patient’s privacy and rights regarding their personal data must, of course, also be respected.
2. The retail industry
Much of the big data that exists within the retail industry is collected through online purchases and loyalty card schemes. Many retailers analyze this data to try and predict the spending habits of their customers as well as provide shoppers with a more personalized shopping experience. The data can also help retailers to fine tune their marketing campaigns—customer journey analytics offers insights into how and where people research a potential purchase and what eventually compels them to buy the item.
Algorithms can even analyze web searches and social media posts to predict trending products, and then the data can be analyzed to ensure that the supply of these items will meet the demand.
3. The transportation and logistics industry
Big data analytics can help transportation and logistics companies to carry out their deliveries more efficiently. For example, after analyzing its routes and other delivery statistics, UPS realized that, on the right-hand driving roads of the US, it was safer and quicker if drivers tried to avoid turning left. Once this rule was implemented, their fleet of vehicles racked up fewer kilometers and shipped their freight more quickly and economically.
By analyzing traffic data, weather conditions and fuel costs, logistics companies can save time and money and thus increase levels of customer satisfaction. Trucks, ships and airplanes can be tracked via GPS sensors, enabling the recipient of the delivery to be kept abreast of its progress and the expected delivery window. This also helps to avoid bottlenecks within supply chains. Big data combined with increasingly advanced automation technology also facilitates the automation of warehouses.
4. The banking and finance industry
The growth of online banking has led to a significant increase in the amount of banking data created within the banking sector. Analyzing this big data allows banks to track the spending and banking patterns of their customers and personalize the products and services they offer them. This helps banks to build lasting customer relationships.
From the customer’s perspective, perhaps the biggest advantage is that big data helps banks to detect fraudulent activity. If a banking transaction takes place that is not in line with the customer’s profile, for example if a large payment is made in an unusual city or country, the bank can react swiftly and bring this to the customer’s attention.
5. The education industry
Much of the value of big data within education relates to the growing online-learning sector. Analyzing how long students take to complete internet-based tasks or how often they reread certain material can help course designers to optimize the content. Thanks to big data, online courses and content can also be tailored to students’ individual needs and interests, which leads to higher levels of motivation amongst learners and potentially fewer dropouts.
Big data analysis also allows educational institutions to more easily identify and react to trends amongst learners, such as enrollment numbers. Such data analysis can also inform and support the decisions made regarding educational policies.
Big data analytics: Where to begin
As the importance of big data analytics grows industrywide, so too does the demand for data experts—but finding skilled experts isn’t always easy. In case you need a specialist to work closely with Big Data tools, we here at expertlead have rigorously tested Data Engineers and BI Engineers. In addition, our pool also includes Data Analysts and Data Scientists who are ready to support you with your data challenges. We first screen a potential tech freelancer’s CV, and then they are interviewed by the expertlead team as well as by a peer and asked to complete a coding challenge.