The predictive analytics market is divided into several segments based on components, deployment mode, organization size, industry vertical, and geography. The market is segmented into solutions and services based on component. Solutions are further divided into risk analytics, marketing analytics, sales analytics, customer analytics, and others. Based on deployment mode, the market is divided into cloud and on-premises. The market is segmented into large enterprises and small and medium-sized enterprises (SMEs) based on organization size. The market is segmented into BFSI, manufacturing, retail and e-Commerce, IT and telecom, energy and utilities, government and defense, and others based on industry vertical. The market is segmented into North America, Europe, APAC, MEA, and SAM based on geography.
The adoption of big data has become increasingly important for businesses of all sizes and industries. While the three Vs of big data—volume, velocity, and variety—are commonly used to define it, it’s important to note that big data-enabled technologies can be used for a wide range of purposes beyond these parameters.
Effective use of big data requires a shift in perspective and a focus on finding issues that need special attention. While other technologies may be used to solve specific problems, such as streamlining inventory management or providing real-time tracking of order shipments, big data can help identify issues that require further attention.
The implementation of big data analytics within an organization requires a thoughtful and strategic approach, with a focus on integrating data into strategic planning. Failing to integrate data into big data platforms can lead to missed opportunities and heavy penalties.
Compliance with regulations is a major concern for businesses, and the integration of big data analytics into regulatory compliance reporting can help organizations stay in compliance and avoid penalties. For example, Hexanika is a FinTech company that has developed an end-to-end solution for financial institutions to address regulatory compliance reporting and data sourcing.
The growing adoption of big data technologies, with continuous developments in the field, is driving the growth of the predictive analytics market. As these technologies continue to evolve, we can expect to see even more innovative and effective uses of big data in the years to come.
The COVID-19 pandemic has affected businesses globally, causing a decline in production and operations in various industries such as manufacturing, automotive, semiconductor & electronics, oil & gas, mining, aviation, and others. The imposition of lockdowns resulted in the temporary shutdown of activities, leading to a lesser production of goods and services.
Organizations and governments are using big data technology to store real-time data and information about COVID-19 patients, including details on the spread and control of the SARS-CoV-2 infection. With the ability to capture extensive data, predictive analytics solutions can be utilized to reduce the danger of spreading the infection as the gathered information can be used to develop future strategies for preventing COVID-19 spread.
The rising cases of COVID-19 compelled industries to encourage remote working environments and follow work-from-home policies. Subsequently, the use of third-party networks, digital platforms, and personal computing devices surged in 2020. However, the implementation of such network connectivity solutions puts businesses at risk of cyberattacks and other malware. Furthermore, the surge in digital traffic presents an opportunity for numerous online frauds, phishing attacks, denial of inventory, and ransomware attacks.
Enterprises harnessed the capabilities of predictive analytics-based security solutions to detect and manage abnormal network behavior, thus increasing the need for predictive analytics solutions amid this global health crisis. The implementation of predictive analytics solutions can help in identifying potential security threats and preventing cyberattacks.
