Keywords

1 Introduction

“Big Data” as the buzzword has attracted the attention of industry insiders, coupled with data warehouse, data security, data analysis, data mining and other commercial applications of big data. The U.S. Internet Data Center noted that the data on the Internet grows by 50 % annually and doubles every two years, and more than 90 % of the data worldwide came into being in recent years, especially after the year of 2009 [2].

Although the business data is valuable, the strategic significance of big data technology is reflected in specialized processing of these meaningful data, instead of the grasp of huge data information as for most enterprises, especially those engaging in technological innovation. If the big data is compared to the technological resource, the key to giving full play to such a technological resource is to improve “processing capacity” of the dada and realize “added value” of the data through “processing”.

Therefore, this article from the actual needs of the enterprise in technological innovation management is expected to figure out the practical problems in how to effectively fit in the new environment of “big data” era, how to deal with the ideological and technological revolution brought by “big data” to the traditional technological innovation management, and how to help the enterprise to achieve breakthroughs in technological innovation management. In order to fulfill this goal, the article with the latest research progress at home and abroad explores the impact of big data technology on enterprise in the way of technological innovation management and seeks new concepts on the basis of big data technology to address the problems in technological innovation management of the enterprise, expecting to give support to practical work of the enterprise in terms of technological innovation management.

2 Literature Review

  1. 1.

    Big Data

According to McKinsey Global Institute, big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The big data is featured by 5 Vs. The first one is volume, i.e. the increasing amount of data. The data of Baidu showed that its home page is required to provide the data of more than 1.5 PB (1 PB = 1,024 TB) everyday and the printouts of these data will exceed 500 billion pieces of A4 paper. It is confirmed that the total amount of data from printed materials is only \(200\) PB so far. The second is variety, i.e. diversified data types. In addition to the text, the data types include picture, video, audio and geographical information with overwhelming amount of the individualized data. The third feature is velocity, i.e. fast processing speed. The data processing follows the rule of “one-second response time”, allowing the users to quickly obtain high value information from various types of data. The fourth one is known as value, i.e. low value density. In the one-hour video, for example, the continuous monitoring may only capture one to two seconds of useful data. The last one is veracity, i.e. accurate analysis results. By massively parallel processing (MPP) database, data mining grid, distributed file system, distributed database, cloud computing platform, the Internet, scalable storage system and other technologies of big data, the users can access to valuable information from a variety of data types [5].

Since 2008, the research on big data has witnessed a rapid development in China and reached a peak in the last three years. According to Zhu et al. [8], the research focusing on “Big Data” and “Cloud Computing” with the keywords of “Computer” and “Software Technology” accounts for more than half of the studies. However, as the big data is increasingly influential in enterprise management, the keywords of “Data Management”, “Data Grid” and “Ontology” appeared in a large number of studies centering on “big data” management. Nevertheless, the research of “big data” at home and abroad still pays much attention to the big data technology and software application in storage, processing, analysis and management, while there is scarcely any study combining “big data” with applied management, especially with technical management.

  1. 2.

    Big Data and Enterprise Technological Innovation

Since Schumpeper proposed technological innovation in well-known “Theory of Economic Development”, more and more enterprises have attached importance to restructuring of production factors, conditions and organizations to establish an efficient production system to earn high profits [7]. The emergence of big data technology is expected to greatly improve the efficiency of enterprise technological innovation. On the one hand, big data technology has brought new means of technological innovation management, allowing enterprises to analyze the behavioral data through real-time monitoring and follow-up study of technological innovation activities, uncover the underlying regularities, find the problems and put forward solutions. On the other hand, Krishnan et al. [3] and other scholars noted that the big data is able to hasten the organizational reform under the condition of rigorous data management, insightful data analysis, and motivated management innovation environment. Thirdly, the application of big data is crucial for enterprises to enhance the core competitiveness, for the decision making of technological innovation has been driven by data instead of business currently. The analysis on big data not only enables the enterprises to grasp and respond to market dynamics quickly, but also helps them to timely provide personalized products and services through technological innovation.

3 Big Data Technology Under Enterprise Technological Innovation Management

From the technological innovation practice of the enterprises, some of them introduced advanced technology or technological equipment to improve their technological level; some companies integrated the technological advantages of cooperators to realize cooperative technological innovation; and there are also enterprises that invested in technological innovation for technology creation and product research and development to achieve cooperative technological innovation with intellectual property right. Accordingly, enterprise technological innovation can be divided into technology introduction, technology integration and technology creation.

  1. 1.

    MPP Technology at the Level of Technology Introduction

Technology introduction, at a lower level in cooperative technological innovation, refers to the enterprise introduces advanced and applicable technology from other companies through a certain way. Generally, there are five ways in technology introduction. Firstly, introduce technology and manufacturing technique, technical knowledge and data (including product design, material formulation, manufacturing drawing, technological process, technological testing methods and maintenance), as well as technical service by hiring experts and entrusting training staff. Secondly, introduce complete equipment, key device and detection means in addition to technology. Thirdly, introduce modern management method and give full play to the introduced technology, attaching importance to the knowledge in both technology and management. Fourthly, introduce advanced innovative ideas and scientific and technological knowledge through technical exchange and cooperation, academic exchange and technology exhibition, etc. Fifthly, introduce technical personnel. The technology introduction is expected to eliminate the technology gap and improve technological level of the enterprise fundamentally in a long term; and the short-term goal is to fill in the technology gap of the enterprise from the production requirements.

It is noteworthy that the technology introduction should give top priority to technology identification. The enterprise has to identify those advanced, applicable and feasible technologies before introduction, so that it can absorb the introduced technology and carry out technological innovation under the existing technological level. As for the enterprises, insufficient technicians and weak technological base usually indicate the insufficient technical information and weak technological identification ability. In this sense, the enterprises can resort to more advanced big data technology, which will be greatly helpful in decentralized processing of massive technical information.

Massively Parallel Processing (MPP) database system is able to divide the collected alternative technologies into independent data blocks managed by isolated storage and CPU, breaking the constraint that the massive technical data can only be managed by centralized research and development center. The data in technological innovation system will be distributed to different servers and stored in various departments involving different links of technological improvement.

Although MPP system will cause data redundancy to a certain extent, it is helpful in data recovery once the system failure happens by storing the same data in different departments involving technological improvement. At the same time, resource management tools in MPP will assist departments involving different links of technological improvement in managing the massive technical data, of which technical query optimizer will optimize various technical query tasks to improve computational efficiency.

The identification ability tends to determine whether the technological innovation of the enterprise is able to go smoothly, achieve success and create commercial value, etc. MPP technology will directly affect the accumulation of technological knowledge of the enterprise, have an impact on knowledge architecture of technological innovation and concern the performance of technological innovation eventually (Fig. 38.1).

Fig. 38.1
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MPP technology and enterprise technology introduction

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  1. 2.

    Cloud Computing Technology at the Level of Technology Integration

Generally, technology integration as a new means of technological innovation indicates that the enterprise evaluates and chooses the suitable technologies systematically to integrate with the existing technologies during the process of technology or product research and development, so as to create new products or new technologies.

As the subject of technological innovation, it is not easy for the enterprises to own technical capacities of different disciplines and industries, while technological innovation that is able to integrate advanced technologies of all industries is the best solution. The technical expertise, management knowledge, production technology, materials technology, process program, equipment system, standardized technology, information technology and management control technology owned by enterprises in all sectors are the source of technological innovation. The enterprise can select the required technologies as the supplement from various disciplines, categories and professional fields and integrate them with existing technologies, so as to fulfill the objectives of technological innovation.

With the rapid development of science and technology, the resources of enterprise technological innovation become increasingly decentralized and thus more and more companies began to attach great importance to the external integration of a variety of technological resources. The companies tend to strengthen the contacts from the perspective of technology with external organizations including their competitors, expecting to realize technological innovation through integration of resources and complementation of technologies.

Since the emergence of cloud computing technology, enterprise technological innovation is facing a growing number of cloud environments. As the underlying hardware of the cloud computing can be anywhere geographically, the enterprises can enjoy the cloud computing services by only paying operating costs according to usage amount, dispensing with infrastructure construction or fixed capital. There are various hardware rental models of cloud computing, allowing different enterprises to share the services and accordingly the rental costs. What’s more, the system capacity of cloud computing is scalable in a very short time, while the traditional hosting services are restricted by scalability of the system. Therefore, cloud computing has shown a remarkable strength (Fig. 38.2).

Fig. 38.2
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Comparison between traditional query and MPP query

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From the application practice of cloud computing, it consists of two types, i.e. public cloud and private cloud. For users of public cloud, they can upload the technical data to an external cloud computing system and access to the resources allocated by the system for technical data processing, with the charging standard of usage amount. This mode not only helps the enterprises to save the cost in construction of technical resource system, but also allows them to obtain new technical resources quickly. As the technical data is stored in the system outside the enterprise firewall, technical data sharing between different enterprises becomes simple and each enterprise can be authorized to login and access to the technical data. However, the public cloud will not make a commitment in performance, handling time and more importantly the data security.

Private cloud is almost the same as the public cloud, except that the private cloud is owned by an enterprise and runs inside the corporate firewall. With exactly the same services as the public cloud, the private cloud only gives service to the enterprise’s internal staff and team. As for the obvious advantage of this type of cloud computing, the enterprise is able to fully control the private cloud, including the security of technical data and system. Of course, the enterprise has to pay for a set of cloud computing device and bear the risk of idle resources of the system in most of the time.

Fig. 38.3
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Comparison between public cloud and private cloud

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The technology integration through enterprise technological innovation has to be based upon strong technological cooperative capability. Cloud computing technology allows the enterprise to closely cooperate with its partners to take the advantage of external technology, reduce transaction costs in technology, improve the specialization of technology, strengthen collaborative innovation, spread the risk of technological innovation and avoid vicious competition in the cooperative organization of technological innovation connected by the interests. Besides, with the help of cloud computing technology, the information can spread quickly and efficiently to achieve resource sharing in both knowledge and technology, so that the enterprise can not only obtain new knowledge and new technology at a low cost, but also transform the technological superiority by integrating the new technology with the existing technology to technological competitiveness, hereby maximizing the efficiency and the benefits of enterprise technological innovation (Fig. 38.3).

  1. 3.

    MapReduce Technology at the Level of Technology Creation

The highest level of enterprise technological innovation is the technology creation which is featured by the technologically leading position of the enterprise.

In order to achieve a breakthrough in technology, the enterprises are likely to establish R&D team, project group, joint venture and other professional organizations involving in technological innovation. On that basis, the enterprises tend to invest heavily in technological innovation to enhance technical competence and expect to obtain unique technologies and products with competitive edges.

In order to achieve a qualitative leap technologically through technological innovation, the enterprises are required to establish a model with new elements of innovation and go through the process of “creative destruction” to achieve the goal of technology creation. In this process, the enterprises have to develop predictive ability, so as to create new technologies that bring competitive advantages for enterprises or develop resource-based products that meet the needs of market and obtain higher economic benefits.

As a new type of strategic management capacity, technology-related predictive ability is the important means for enterprises to realize technological, economic and social integration, as well as the ability to effectively carry out the resource combination and optimal configuration. It is helpful for enterprises to develop scientific strategic plan of technological innovation and on that basis the enterprises are allowed to utilize the results of technological prediction, analyze the changes of market demand and thus find the information technology and technological opportunity in favor of technological creation. Based on technological prediction, the enterprises are also able to accurately identify the market need to prepare for the next competition, develop or adjust the direction of technological innovation, and create new technology in line with market demand and development tendency.

MapReduce technology in the era of big data is a parallel programming framework and is helpful for R&D personnel of the enterprises with the processing of massive technical data, especially in two key links: “map” and “reduce”, which will be executed concurrently in a series of nodes of technological innovation. Unlike MPP system, information exchange will not happen between these nodes, reducing information interference for R&D staff.

Currently, more and more enterprises have found that it is crucial to analyze constantly generated massive technical data to support technological innovation and decision making and MapReduce technology is able to help technical personnel to manage massive semi-structured or unstructured technical data.

In the process of technological innovation, MapReduce technology will provide the useful information for technical management personnel through two steps. The first is “map” step. Since the technical data of enterprise is continuously written in the system, analysts can analyze every key data recorded in the text by establishing the mapping program that is able to search the data from the text, parse the data from the paragraph, and then do a word count. The next step is “reduce”. Through reduction operation, the results output by mapping program in different nodes will be collected for secondary allocation. By outputting the results of technical data processing, technical management personnel is able to identify and focus on the key information in the process of technological innovation, so as to seek breakthroughs in key links of industry technology (Fig. 38.4).

Fig. 38.4
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Execution of MapReduce

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MapReduce technology is able to help the companies to improve technology-related predictive ability, effectively invest in technical resources, predict the development trend of technology and product, and hereby guide the technological innovation.

4 Big Data-Related Approaches in Improvement of Enterprise Technological Innovation Management

As for the enterprises in the era of big data, they can achieve technological innovation by improvement of big data technology. Objectively, some of the companies restricted by their own conditions can’t improve the big data technology. Therefore, the approaches in improvement of big data technology may not exactly the same and the enterprises on the basis of their conditions should upgrade big data technology and enhance the management of technological innovation in a planned and orderly way [4].

  1. 1.

    Breakthrough Approach in Improvement of Big Data Technology

Breakthrough approach in improvement of enterprise technological innovation refers to the enterprises can take MPP, cloud computing, grid computing, MapReduce and other technologies that are easy to make progress as a breakthrough and improve the performance of the enterprise technological innovation by upgrading the data analysis technique.

Requiring the enterprise to have the advantages in a certain aspect, this approach is able to maximize the strengths of the enterprise and transform them to favorable terms required by the big data technology. Besides, it highlights the key points of management and it is easy to control. However, the development environment is changeable and thus the advantages of enterprises will not last for a long time, especially some of the companies lack the core competitiveness with only relative and limited competitive edge. Therefore, it is risky and unsustainable to develop big data technology merely by the superiority in one aspect.

  1. 2.

    Parallel Approach in Improvement of Big Data Technology

Parallel approach in improvement of enterprise technological innovation from the perspective of management allows the companies to coordinate technical resources from different sources, improve big data technology concertedly and thus enhance the performance of enterprise technological innovation significantly. This approach promotes the interaction of big data technology in different enterprises and effectively carries out technological innovation with the means of parallel development, so as to accelerate synergies between enterprises and launch technological innovation activities more efficiently.

Parallel improvement of performance requires the enterprises involving in technological innovation to enhance capabilities of internal data analysis and focus on improvement of external data environment, knowledge sharing and technology exchange between cooperators.

The advantage of parallel approach in improvement of performance lies in synergies, to be exact, the enterprises can mobilize all resources in favor of improvement of big data technology to achieve the effects of \(1 +1 > 2\). In the process of technological innovation, data analysis techniques of different enterprises are not the same, which is conductive to reinforcing complementary advantages and thus promoting cooperation between enterprises.

  1. 3.

    Vertical Approach in Improvement of Big Data Technology

Vertical approach is the most advanced way to promote big data technology of enterprise, which enables the companies to fully integrate the advantages in various fields and comprehensively improve each factor that may affect data analysis technique, so as to substantially upgrade the technological innovation.

According to the vertical approach, the enterprises are required to aggregate technological data and innovative resources to the maximum extent, analyze and process the data in a highly coordinated way, as well as maximize synergies in selection of technical direction, cooperation of technology research and development and allocation of technological achievements, so as to enhance the performance of technological innovation roundly.

With respect to the difficulties of technological innovation management, the vertical approach in improvement of big data puts forward higher requirements for enterprise technology innovation obviously. In order to promote the big data technology with this vertical approach, the enterprises need to abide by the following principles in the process of technological innovation:

Principle of Multi-objective Development: data analysis should pursue economic, technological and social benefits. Economic benefit indicates that big data technology of the enterprise has to maximize the value of technological innovation; technical benefit implies that the big data technology helps to improve the technological capabilities of the enterprise and create the advanced and transformative technological achievements with technological content; and social benefit requires the big data technology to avail social harmony, as well as economic and scientific development.

Principle of Coordinated Development: the enterprises are required to focus on the coordination of business interests in the process of organizing and participating in the improvement of big data technology. Enterprises embrace benefit maximization and thus the management activities are also driven by interests. However, the vertical approach in improvement of big data technology asks for maximum coordination between speed and quality with respect to the development of big data technology.

Principle of Sustainable Development: big data technology of the enterprises should go after sustainable development in technology, economy and natural ecology. The development of big data technology is expected to promote cleaner and more advanced production technology with high-tech products, as well as the sustainable development of technological innovation eventually.