Market Trends of APAC Operational Intelligence Industry
Growing Need for Real Time Data Analytics is Expected to Drive the Market
- Real-time big data analytics is a big data innovation. While big data analysis converts the database after the raw files are created, real-time big data analysis converts the raw files as they are created. In other words, the hazy raw data is turned into useful data milliseconds after creation. The responses come in a timely manner.
- Businesses lose money due to delays in decision-making and operations. Real-time analytics overcomes this problem by allowing company leaders to make decisions based on rapid and actionable data insights. This means businesses can avoid costly delays, seize opportunities, and anticipate issues.
- Real-time data analytics can be used for various purposes in almost any business (and even on an individual basis). Real-time data analytics is a prerequisite when it comes to running a firm and keeping a finance team going at full capacity. Finance teams can use real-time data analytics for a variety of purposes, including determining how everyday operations are working (identify bottlenecks), implementing process improvements (analyze KPIs), and monitoring a company's financial position (reporting), to mention a few.
- SAP HANA is a single database that combines powerful data processing, application services, and flexible data integration capabilities into a single database. HANA uses in-memory database software, which allows users to query data kept in the system's memory (RAM) rather than on physical drives. Customers may now process data in various ways much faster and create a series of what-if scenarios to help them capitalize on opportunities or prevent pitfalls. Established technology suppliers, such as IBM and Oracle, have also used new technology to enable real-time operations in their platforms.
- Despite being attentive in dealing with massive amounts of data, real-time data analytics has some drawbacks. Real-time data analytics must be accessible to manage enormous amounts of data and respond quickly to requests. This implies that real-time big data analytics should be capable of dealing with market and business elements to make effective and efficient real-time judgments.
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Increasing Adoption of Big Data Analytics and the Internet-of-Things (IoT) is Expected to Drive the Market
- The market is driven by end-user adoption of big data analytics and the Internet of Things (IoT). Operational intelligence (OI) and analytics solutions have earned a significant market share in the last decade thanks to the rise of Big Data and the growing need to make key business decisions quickly. According to IBM, 62% of merchants believe using data (Big Data and analytics) gives their businesses a competitive advantage. This number compares to 63% of responses from all industries.
- Furthermore, the Internet of Things (IoT) is a digital connectivity extension to gadgets and sensors in homes, workplaces, automobiles, and practically any place. As a result of this breakthrough, nearly any device may now collect and communicate data on its activities, which can then be analyzed to aid monitoring and various automatic functions. IoT requires operational intelligence to complete these duties (OI). PTC Inc, for example, uses IIoT-delivered operational efficiency insights to evaluate real-time production performance and anticipate problems before they occur.
- During the pandemic, digital transformation in healthcare, manufacturing, retail, and other industries increased data creation. Automation in the manufacturing business is driven by industrial IoT and artificial intelligence (AI). Inventory management, asset management and predictive maintenance, real-time alerts, network manufacturing, and other technologies are being introduced to help the manufacturing industry prosper in uncertain business situations.
- According to GSMA, the global number of Internet of Things (IoT) connections is expected to increase through the period from 2020 to 2030, with an forecast total of 24 billion enterprise IoT connections in 2030. The Asia Pacific region leads the list is expected to 18.2 billion connections by 2030.
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