Big Data: A New Mission for CIOs
Convergence of New Computing Models
The pace of change for developing ICT technologies brings pressing challenges to Chief Information Officers (CIOs).
New computing models represented by social networking, Location-Based Services (LBSs), mobile Internet, and commercial services are converging. The rapidly growing mobile Internet and Internet of Things (IoT) clear the path for collecting data as a core component in enabling people to communicate, collaborate, and share more conveniently via social networking. As a consequence, we see a surge in Big Data analytics that uses cloud computing resources to process massive amounts of data. These four technology trends — Mobile, social, Big Data, and cloud computing are the four major areas that are at the core of interest in ICT development.
The development of ICT technologies is a key driving force in for innovation in enterprise as well as in government. For example, local governments in China are using ICT technologies to transform service delivery and modernize governance, and federal-level departments are using Big Data to assess financial risks in local jurisdictions.
In all cases, CIOs must ensure risks are mitigated and challenges effectively addressed.
McKinsey & Company has predicted that there will be in-the-order of twelve economically disruptive technologies that will emerge over the next decade, the majority of which will be in the ICT domain. Impacts can be expected in mobile Internet, IoT, cloud computing, and Big Data processing. The report states that the contribution of these 12 disruptive technologies to the global economy will exceed US$ 15 trillion by 2025.
The increasing rate by which knowledge workers are having their work automated is adding to the disruption. By 2025, knowledge work automation systems will take on tasks typically performed by the current full-time workforce of 110 to 140 million people. The incremental economic impact is possibly as much as 5.2 to 6.7 trillion U.S. dollars, due largely to the contributions of Big Data in intelligent learning, disease diagnosis, drug discovery, legal contracts, patents, financial investment, accounting, and modern governance.
In the recent fight against the Ebola virus, the US adopted disruptive methods to quickly develop vaccines and other countermeasures. This is a prime example of how cloud computing, Big Data, and IoT applications are powering transformational outcomes at institutional scales — such as altering the policies and practices of the U.S. healthcare system.
Developing ICT Technology Tracks and Integration
ICT technologies have evolved independently in the past, in contrast to today’s convergent models that require deeper integrations to achieve the best results. ICT technologies are continuing to develop in multiple directions simultaneously, with each and all on paths to greater integration.
For example, the mobile Internet provides important technical support for Big Data applications. IoT facilitates the collection of Big Data, functioning as a network for convenient data collection, monitoring, and decision-making. By using state-of-the-art and cost-effective sensors, wireless networks, and Near-Field Communications (NFC) equipment, IoT not only optimizes the collection of Big Data, but also creates a substrate for processing remote services.
Without cloud computing, Big Data processing does not exist. As Big Data and cloud computing have developed, the technologies have combined to add new functionality to the key components of information processing — including semantic computing, updated file systems, new databases and data warehouse techniques, metadata and data modeling extensions, in-memory processing, and distributed storage.
Multi-Dimensional Data Structures (MDDSs), Machine Vision (MV) algorithms, and video rendering technologies are all contributing to an increasing demand for high-performance cloud computing. Big Data requires computational support from the cloud for user views, data retrieval, data mining, and online analytics. Big Data platforms add intelligence to information services by allowing users to efficiently extract the desired information from massive amounts of data. Cloud computing offers users’ software applications and storage resources in an on-demand, easy-to-manage, elastic, cost-effective, energy efficient, secure, and convenient platform.
As a result of these interdependencies, operating systems, databases, middleware, and application software will continue to interoperate to form a more perfect unified platform. This integration of software with hardware, hardware with networks, products with businesses, and software across industries will accelerate and deepen. The result will give rise to new technologies, business models, and service patterns long into the future.
Big Data as a Strategy
Big Data is a valuable resource that is the natural result of ICT development. Analogous to drilling for oil, the first step for extracting value from Big Data is “exploration.” The second step is to “mine” or collect the information that meets specific requirements. The third step is to “refine,” or structurally process the collected information based on the demands of each application. The final deliverables are Big Data-driven application systems and Big Data management systems.
Arguably the greatest leverage for Big Data systems is their use in the creation of new business models. For example, several banks in China use Big Data to obtain credit rating and transaction volume information to customize loan products to support the growth of small and micro enterprises who operate on top of larger online shopping platforms and express companies.
Data collection is influenced by a variety of factors such as relevant laws and regulations, system standards, operating mechanisms, and business models. Thus, t h e structure of the information is critical to each successful Big Data deployment.
Developing application software is another top priority for Big Data, as software is essential to the mission of Big Data management. More intelligent information-processing technologies must be researched and developed.
To help meet the needs for, improving the interior logic and delivering new application requirements organizations specializing in research on Big Data management will spread across multiple fields, and professional Big Data management services will emerge.
It is crucial to recognize the strategic importance of effective Big Data policies and best-practices for competitive and governance capabilities in both the public and private sectors.
With an abundance of data resources and huge markets, China is a global leader in Big Data applications. To promote Big Data applications, China intends to enhance top-layer designs for the development of information resources, specify Big Data application goals, and forge cooperation with the world’s leading enterprises. Through constant innovation, China is expected to make meaningful contributions to the development of Big Data technologies throughout the world.