The quantity of data produced from various sources, such as social media, mobile devices, and the internet of things, has increased dramatically in recent years. (IoT). Big data analytics, which entails analysing and interpreting huge and complex data sets to unearth insights, patterns, and trends that can help companies make informed choices, has emerged as a result of the quick increase in data.
Organizations from a variety of industries have made significant investments in big data and analytics in the Asia/Pacific area, which has been at the forefront of this transformation. The Asia/Pacific area is expected to spend $42.2 billion on big data and analytics by 2023, up from $23.8 billion in 2018, according to a recent report by IDC, a worldwide market intelligence company. By 2026, expenditure is expected to increase at a compound annual growth rate (CAGR) of 24.8% and hit $70.7 billion, according to the study.
This piece will explore the major factors influencing the development of big data and analytics in the Asia/Pacific area, the sectors that are setting the pace, and the difficulties that businesses encounter when implementing these technologies. We’ll also look at some of the creative ways businesses are using big data and analytics to boost development and obtain a competitive advantage.
Big Data and Analytics Spending in Asia/Pacific* to Reach $42.2 Billion in 2023, $70.7 Billion by 2026
IDC’s Worldwide Business Data and Analytics (BDA) Spending Guide predicts that Asia/Pacific* will spend $42.2 billion on BDA goods in 2023, an increase of 19.6% from 2022. Over the preceding year, there has been a significant rise in investment in business intelligence products. Due to organisations’ growing desire to take part in data-driven decision-making, improve client experiences, speed up business innovation activities, and take advantage of cost-saving possibilities, it is predicted that it will stay constant.
The phrase “data-driven everything” is increasingly guiding Asia/Pacific companies’ DX efforts, especially for those at higher DX development levels. According to Jessie Cai Danqing, Associate Research Director, Big Data & Analytics, IDC Asia Pacific, “More of them must modernise their organisation’s data platform to address trust, adaptability, and agility issues associated with highly disparate and diverse data sources and sinks.”
The uptake of BDA solutions is being driven by improved corporate data access, according to Abhik Sarkar, market analyst for IDC’s Asia/Pacific IT Spending Guides. External hindrances like the pandemic, cyberthreats, economic unpredictability, supply-chain irregularities, and the need to minimise these risks, coupled with the quick rise of digital companies and shifting workforce demographics, he continues.
The Asia/Pacific BDA industry is growing as one of the key factors influencing its growth, according to research. This can be ascribed to the increasing need for companies to enhance privacy policies and practices, work closely with ICT suppliers to reduce third-party risk, and enhance the risk management procedure. In addition, business disruptions brought on by international pandemics and sociopolitical conflicts have shown how crucial it is to adopt data sovereignty practises in order to ensure operational and commercial resilience.
More than 35% of the BDA market’s revenue in 2023 will come from banking, telecoms, and professional services. They will continue to dominate the market over the projected time span. Improved risk management and the ability to produce real-time information from customer data are two use cases driving expenditure in the financial industry. In 2023, expenditures on telecommunications will total $4.6 billion. The rising adoption of “cloud first” with organisations’ “wireless first” multi-access network strategy and the growing emphasis on connectivity resilience are both anticipated to greatly disrupt the industry.
Services’ income portion will be 41.1% in 2023, rising to $28.4 billion at a CAGR of 17.9% from 2021 to 2026. 79% of the overall cost of BDA services in the area is spent on IT services. Software will spend $13.8 billion in 2023 and grow by more than 23% in 2024, trailing only services in terms of expenditure. The greater use of database data stores, end-user query, reporting, and analytics tools, as well as artificial intelligence software systems, is to blame for this. Software is the fastest-growing business sector, with a CAGR of 22.8%. Spending on the goods industry will total $11.1 billion in 2023. Computers will make up roughly 75% of technology spending in 2023.
The purpose of the Worldwide Big Data and Analytics Spending Guide is to satisfy the needs of companies assessing the possibilities of big data and business analytics by region, industry, and company size. Subscribers can access the Spending Guide’s revenue forecasts for 20 technology and service fields across 19 industries, five business size categories, and 53 countries. The full Spending Guide was developed to aid IT decision-makers in clearly grasping the scope and direction of industry-specific big data and business analytics options today and over the next five years, unlike any other resource in the sector.
Challenges that organizations face in adopting these technologies
Organizations in the Asia/Pacific area face a number of difficulties when adopting big data and analytics tools. Here are a few of the main difficulties:
Big data algorithms are dependent on the precision and quality of the data being analysed. However, organisations frequently battle with problems related to data silos, inconsistent data forms, and missing data sets. To ensure that data is reliable, accurate, and easily available, it is crucial to have effective data administration procedures.
Ability shortfall: The Asia/Pacific area is severely lacking in data mining ability. Finding qualified data scientists and researchers who can work with large data and derive insightful conclusions is a challenge for many organisations. Due to the intense rivalry for talent, businesses frequently pay a price to entice and keep experienced pros.
Infrastructure: To keep, handle, and analyse big data, a reliable infrastructure is needed due to its volume and complexity. To satisfy their big data analytics requirements, organisations may need to make investments in high-performance computing resources, like cloud computing. For some firms, especially tiny and medium-sized ones, this may require a sizable investment.
Data Privacy and Security: Organizations must exercise caution when it comes to data privacy and security given the growing quantity of data being produced. They must make sure that confidential information is shielded from abuse or unauthorised access. This is crucial for sectors like banking, healthcare, and government where stringent data privacy laws apply.
Return on investment (ROI): Companies must make sure they are receiving a decent return on their investment when implementing big data and analytics technologies because this can be a costly process. Big data analytics ROI measurement can be difficult because it frequently takes time for these technologies to pay off.
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Innovative ways in which companies are leveraging Big Data and Analytics to gain a competitive edge and drive business growth.
Companies in the Asia/Pacific region are leveraging big data and analytics in innovative ways to gain a competitive edge and drive business growth. Here are some examples:
Personalized customer experiences: Businesses are gaining insights into consumer behaviour and tastes using big data and analytics. The client experience is then personalised using this data, with each customer receiving a unique set of goods and services. For instance, e-commerce businesses use machine learning algorithms to suggest goods based on past purchases and viewing habits of customers.
Big data and analytics are being used to optimise supply chain processes, bringing down costs and raising productivity. For instance, to optimise distribution plans and reduce delays, logistics firms use real-time data on traffic, weather, and shipment routes.
Fraud identification and prevention: To identify and stop fraud, financial organisations use big data analytics. Large amounts of data can be analysed in real-time by machine learning algorithms to spot suspicious activities and mark them for follow-up inquiry.
Big data and analytics are being used by businesses in the production and industrial sectors to adopt predictive maintenance strategies. Companies can forecast when machinery is likely to malfunction and plan maintenance before an issue arises by analysing data from sensors and other sources.
Smart city initiatives: To enhance municipal planning and infrastructure, governments in the Asia/Pacific area are using big data and analytics. Cities use data from devices and other sources, for instance, to optimise traffic movement, lower energy use, and boost public safety.
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At last, the Asia/Pacific region is witnessing significant growth in big data and analytics spending, driven by the need for businesses to make informed decisions and gain a competitive edge. With spending set to reach $42.2 billion by 2023 and $70.7 billion by 2026, companies across various industries are investing in big data and analytics to gain insights into customer behavior, optimize supply chain operations, prevent fraud, and implement predictive maintenance programs.
However, companies in the Asia/Pacific region also face several challenges in adopting these technologies, including data quality and management, talent shortage, infrastructure, data privacy and security, and measuring ROI. Addressing these challenges will be critical to realizing the full potential of big data and analytics in the region.
Despite the challenges, the innovative use of big data and analytics is helping companies in the Asia/Pacific region drive business growth and deliver better products and services to their customers. As the volume and complexity of data continue to grow, big data and analytics will remain a critical tool for businesses in the region to stay competitive and succeed in the digital age.
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