The Internet of Things (IoT) is often mentioned in the same breath as Big Data. Although they share complementary fields, these modern concepts represent unique features that can help any business succeed.
For instance, IoT systems are known for connecting otherwise decentralized devices to collect information quickly and accurately before processing it in real-time for immediate decisions. On the other hand, Big Data is more concerned with vast and complex volumes of data that can be analyzed later on to generate qualified insights into various operations.
What Is Big Data?
Big Data is the process where large quantities of data, structured and unstructured, are collected and analyzed to dive deep into varying business patterns. As the name suggests, Big Data refers to enormous amounts of data that cannot be processed using traditional methods.
Data scientists have listed four V's to help organizations understand the concept of Big Data:
1. Variety
In the past, there were smaller quantities by which data could be categorized, making it easier to fit information in spreadsheets and charts. Today, there are thousands of different types of data, from scientific information about the latest experimental outcomes to social media posts about famous celebrities and movies.
Due to the sheer variety of available information, powerful analytics software is necessary to harness and combine the data with simpler data streams to gain specialized insights.
2. Velocity
People create over 2.5 quintillion bytes of data daily, with Google searches accounting for more than 3.5 billion processes every 24 hours. Processing this generated data is a massive task that needs the latest analytics and machine learning technologies.
3. Veracity
Veracity is the accuracy of a particular data set, including evaluating the data source's credibility. It is crucial to pursue data veracity by eliminating or reducing duplication and bias, especially since the U.S. loses approximately $3.1 trillion annually due to poor data quality.
4. Volume
The extensive amount of data regularly gathered through various online media cannot be stored, let alone processed through traditional systems. Fortunately, modern data analytics frameworks are being created to help accommodate distributed storage and aggregation.
What Is the Role of Big Data in IoT?
More and more organizations are taking advantage of the data from IoT-connected devices to make well-informed decisions. This trend is leading to the rise of big data analytics as the key to understanding high volumes of information.
In a nutshell, the role of big data in IoT is to process large amounts of data in real time and store them safely using innovative technologies.
Here are the four steps in IoT Big Data processing:
- IoT applications and IoT-powered smart objects generate massive amounts of unstructured data, which are then collected into the Big Data system.
- The Big Data system acts as a shared distributed database, storing the collected volume into Big Data files.
- Data professionals analyze the files using robust analytic tools.
- Management generates reports using analyzed data to make better business decisions.
What Are the Benefits of IoT and Big Data?
Integrating IoT technology into Big Data processes produces several benefits across different industries. Here are a few examples:
Healthcare Sector
The combined features of the IoT and Big Data can revolutionize the next generation of e-healthcare systems. IoT platforms can help better manage and analyze the varying connections between sensor signals and big data so that hospitals can learn more about specific illnesses and improve remote diagnosis.
Manufacturing Sector
Manufacturing companies can install IoT sensors to collect operational data and gain an in-depth look at the business's performance. The valuable insight can help management determine which types of equipment must be repaired or replaced before they affect productivity, saving businesses time and money.
Transportation Sector
IoT sensors are being installed in today's vehicles to track them without compromising mobility. RFID tags can also be used on connected cars to collect data regarding driver routes, fuel efficiency, and time utilization, helping organizations improve productivity and optimize fleets.
Cybersecurity
Every industry is at risk of cyberattacks in this age of internet connectivity. However, organizations can leverage IoT and Big Data tools to strengthen their cybersecurity and safeguard their data infrastructure. Integrating AI and machine learning capabilities into existing security systems can significantly improve threat response times while acquiring adaptive strategies from previous threats.
A Final Word on IoT and Big Data
The convergence of IoT and Big Data provides many opportunities and applications across different sectors. Businesses must start collecting and analyzing data with these technologies to gain valuable real-time insights into their processes, customer base, and behavior.
IoT and Big Data have a significant impact on each other. The more IoT grows, the higher the demand it will generate from businesses needing extensive data capabilities. For instance, as IoT-generated data increases, traditional data storage solutions are pushed to their limits. Advanced storage solutions are necessary to manage these growing workloads while maintaining data quality and integrity.
