Main Challenges with Big Data

Full data privacy and security is required for any IoT-enabled system generating enormous data. As it includes the personal information of users, the data collected and stored should remain confidential and have total protection.

Fremont, CA: Big data is widely used for a broad set of heterogeneous data present in the structured, unstructured, and semi-structured forms. As per Statista, big data revenue generates from service spending, representing 39 percent of the overall market as of 2019. The data volume created by IoT connections reached 13.6 zettabytes in 2019, and it would extend to 79 zettabytes by 2025.

Management and Data Storage

The data generated from connected devices is growing at a high pace, but the storage capacity of most big data systems is confined. Storing and handling a vast volume of knowledge is a huge challenge. Therefore, developing systems or structures that can capture, save, and manage data has become imperative.

Visualizing Data

Heterogeneous data or structured, unstructured, and semi-structured data in various formats is the data generated from connected devices. Visualizing the data instantly isn't easy. Therefore, for better visualisation and comprehension, there is a need to prepare data to obtain reliable decision-making in real time while improving the productivity of the industry.

Privacy and Confidentiality

Full data privacy and security is required for any IoT-enabled system generating enormous data. As it includes the personal information of users, the data collected and stored should remain confidential and have total protection.

See Also: Top Information Security Solution Companies

Captivity with Control

For the continuous and reliable running of IoT operations, Internet-enabled devices need an unending power supply. In terms of memory, computing capacity, and resources, connected devices are missing, so they must have light-weighted mechanisms.

Device Security

As big data is prone to attacks, analytics face device safety challenges. Data processing faces challenges due to short IoT device-end computing, networking, and storage.

Various Big Data instruments provide globally linked systems with useful and real-time data. Via appropriate techniques and processes, big data and IoT evaluate data reliably and efficiently. The analysis of data can differ with the data types obtained from heterogeneous sources.