Big data is one of the biggest buzzwords in business and tech. Many companies continue to grapple with how to take advantage of it best and get the most value out of their data and insights.
Big data has shaped how companies in every sector do business. As a result, understanding how these businesses benefit from big data will give you a better idea of where you can use it effectively in your own work.
This article will discuss how services and industries are affected by big data and how big data can be used to make improvements to businesses across several sectors.
What are big data analytics?
Big data analytics uses predictive modeling, statistical modeling, machine learning and other data-mining techniques to discover patterns in large volumes of data. Predictive modeling provides a forecast for future activity based on established practices.
Statistical modeling examines relationships between different variables and tells how likely it is that one thing causes another. Machine learning uses artificial intelligence to learn from past data how to make predictions or classify new items with little or no human involvement.
You can use these data scientist skills in the healthcare, agriculture, logistics and retail sectors. For example, companies can create algorithms to optimize delivery routes for goods to minimize fuel consumption and costs while maximizing service levels. Universities such as Baylor offer computer science degree programs to prepare you for this type of work with courses on data science.
5 services and industries that use big data
Big data is big business, but it’s not limited to information-heavy industries like IT and analytics. The following list explores multiple industries and services that use big data to stay ahead.
Food delivery services
Food delivery service providers utilize big data to deliver customer orders on time. They collect information on food orders, traffic patterns, weather, local events and more.
These insights help them determine how many drivers they need in a particular area and when they should send out an order. Additionally, these companies can use this data to analyze their marketing efforts.
The findings can help providers identify popular restaurant dishes or promotions that need improvement. The result is that they know exactly how much food to deliver.
For example, delivery services like Uber Eats can predict demand and have enough drivers available when needed.
With this technology, restaurants can know just how much food they will need each hour of the day. This information leads to improved customer satisfaction rates and lower operational costs.
The healthcare industry is one of the largest industries in the world. However, people often criticize the industry for lack of efficiency in certain areas.
One way that hospitals are trying to combat this problem is by implementing big data into their workflow. Hospitals can now make more informed decisions about patient care by looking at a patient’s medical history and determining the most effective treatments.
Healthcare facilities can also use predictive analytics to forecast future needs based on current statistics. For example, they may notice a spike in emergency room visits during flu season.
Knowing this information ahead of time allows them to plan accordingly and mitigate any potential issues before they happen. By making changes to best meet future needs, hospitals are less likely to incur unnecessary costs.
Music and video streaming services
Streaming services are constantly looking for new ways to get listeners to engage with their content. One of the many ways they do this is by mining user data to offer personalized suggestions based on individual listening habits.
For example, if you’re a fan of the Beatles, Spotify will recommend other artists like them or those who influenced their sound. Or, if you listen to music primarily in the morning, Spotify may suggest songs that are more calming in nature for your listening experience.
Other streaming services like YouTube have also incorporated artificial intelligence (AI) into their programming to make recommendations. These recommendations are generally centered around a video’s subject matter, which helps viewers find relevant videos they might not have found otherwise.
Additionally, Kafka technology can be used as an application interface between different systems, which means it can connect data from various applications and formats. What is Kafka? It refers to distributed systems used to collect, store and distribute data. This data can be anything from weather information to financial transactions. One of the most common use cases for Apache Kafka architecture in the navigation industry is that it allows companies to incorporate a wide range of information into their systems without worrying about compatibility issues.
As drivers explore new routes on their way home from work, the system updates and adds data to those maps with every turn the car makes. As a result, newer cars often have built-in systems that collect data from satellites and sensors on the vehicle.
These systems allow for faster calculations based on how fast you’re going, how hard you’re braking and what gear you should be in for a certain part of the road. The better these models predict what you need when driving down a particular stretch of highway, the safer it gets.
Banking and securities
Banking, securities and insurance are all industries that use data analytics to provide better services. In banking, for example, algorithms analyze financial transactions daily so that banks can be more accurate with their predictions of credit card delinquencies or loan defaults.
Banks can also use data such as customer spending habits or the types of products they are interested in buying to offer more personalized services. The same is true for securities and insurance companies who use predictive models to decide how much risk they should take with clients.
These industries also use this information to identify new business opportunities. For example, a company might see an opportunity in flood-prone regions and offer higher premiums to people living there because it knows these customers are at increased risk of flooding.
Big data has the potential to transform industries of all sizes and types. With more data, companies can better understand their customers and make decisions that are in the best interest of their business.
Even if you’re not working with big data yet, it’s essential to stay abreast of new technologies to take advantage of them when they become available. Many qualified professionals can assist you in concept development through implementation, integration, and analytics.