There has been rapid growth in the Internet of Things (IoT) and big data technologies amongst businesses and consumers. According to Forbes, it’s predicted that the amount of data generated will increase to 175 zettabytes by 2025. This would have tremendous implications in the way data is ingested, indexed and stored.

Considering the amount of data being amassed from IoT sensors every second, it’s vital to have advanced analytics systems in place to collect and harness data effectively. These systems should be capable of finding correlations and revealing trends so that enterprises can gauge actionable insights, which can then be used to improve business strategy and services.

Since IoT devices collect vast amounts of structured and unstructured data, there will be challenges associated with processing and depicting them in real-time. This is where the role of big data becomes pronounced.

The potential of big data to process a tremendous amount of information is one of its main advantages. The relationship between big data and IoT is one of symbiosis, where seamless IoT connectivity and consequent big data capture and analysis can help enterprises in having a higher level of understanding to further their prospects.

Indexing Challenges

We are currently at a stage where capturing, analyzing and reporting of IoT data is mandatory for most businesses. However, there are quite a few challenges faced by these organizations since these technologies are still in their developing stage. Some of them are:

Integration Challenges

Since IoT data is received in different formats over multiple channels, collecting and integrating it is challenging. Analytics systems need to ensure that the data received is in a format that is actionable enough to determine insights and only LogZilla’s Network Event Orchestrator delivers the quickest and most affordable data ingestion method on the market today.

Data Privacy Challenges

IoT systems often have information that is sensitive and needs to be protected from outside interference. The constant influx of data makes it difficult to secure each part of it and to perform analysis. These systems rely on third-party infrastructure due to their limited capacity, which will give rise to increased security risks. Therefore, preventive measures like data anonymity and encryption are employed to enforce data security.

IoT is one of the most innovative developments in the recent decade that successfully blends technology and data to develop more constructive strategies. With the proliferation of sensors and smart devices in the last decade, the relationship between IoT and big data has reached a stage where accurately processing massive amounts of high-frequency data is of paramount importance to organizations.