what is big data

Big data refers to large datasets that are too large or complex for traditional data processing tools to handle. These datasets are often characterized by the "3Vs" of big data: volume, variety, and velocity. Big data is generated by a wide range of sources, such as social media platforms, sensor networks, and online transaction records, and it can be analyzed to extract insights and improve decision-making. In order to process and analyze big data, businesses and organizations often use specialized tools and technologies such as Hadoop, Spark, and NoSQL databases.

Operational big data

Big data refers to extremely large datasets that are too large and complex to be processed and analyzed using traditional data processing and analysis tools. Operational big data refers to data that is generated in real-time or near real-time through the operation of an organization's systems and processes, and that is used to support operational decision-making and enable operational processes.

Operational big data can come from a variety of sources, including transaction data, machine data, sensor data, and social media data. It can be used in a wide range of applications, including fraud detection, customer analytics, supply chain optimization, and real-time decision making.

To effectively manage and analyze operational big data, organizations often use specialized big data technologies, such as Apache Hadoop, Apache Spark, and NoSQL databases, which are designed to handle large volumes of data at high speed and scale.

Operational big data

Big data refers to extremely large datasets that are too large and complex to be processed and analyzed using traditional data processing and analysis tools. Operational big data refers to data that is generated in real-time or near real-time through the operation of an organization's systems and processes, and that is used to support operational decision-making and enable operational processes.

Operational big data can come from a variety of sources, including transaction data, machine data, sensor data, and social media data. It can be used in a wide range of applications, including fraud detection, customer analytics, supply chain optimization, and real-time decision making.

To effectively manage and analyze operational big data, organizations often use specialized big data technologies, such as Apache Hadoop, Apache Spark, and NoSQL databases, which are designed to handle large volumes of data at high speed and scale.