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レポート概要
| 本調査レポートでは、世界のビッグデータエンジニアリングサービス市場について調査し、イントロダクション、調査手法、エグゼクティブサマリー、市場動向、新興技術動向、種類別（データモデリング、データ統合、データ品質、分析）分析、ビジネス機能別（マーケティング・販売、財務、操作、人的資源）分析、組織規模別（中小企業、大企業）分析、展開方式別（クラウド、オンプレミス）分析、エンドユーザー別（金融、政府、メディア・通信、小売り、製造）分析、地域別分析、競争状況、投資分析、市場機会・将来動向など、以下の構成でお届けいたします。 ・イントロダクション ・調査手法 ・エグゼクティブサマリー ・市場動向 ・新興技術動向 ・世界のビッグデータエンジニアリングサービス市場規模：種類別（データモデリング、データ統合、データ品質、分析） ・世界のビッグデータエンジニアリングサービス市場規模：ビジネス機能別（マーケティング・販売、財務、操作、人的資源） ・世界のビッグデータエンジニアリングサービス市場規模：組織規模別（中小企業、大企業） ・世界のビッグデータエンジニアリングサービス市場規模：展開方式別（クラウド、オンプレミス） ・世界のビッグデータエンジニアリングサービス市場規模：エンドユーザー別（金融、政府、メディア・通信、小売り、製造） ・世界のビッグデータエンジニアリングサービス市場規模：地域別 ・競争状況 ・投資分析 ・市場機会・将来動向 |
The big data engineering services market is expected to witness a growth at a CAGR of 16.3% over the forecast period (2021-2026). The evolution of technological tools has enabled solutions to be delivered as a service. Owing to this, Software as a Service (SaaS), Platform as a Service (PaaS), and Data as a Service (DaaS) have emerged as potential growth opportunities for Big Data vendors.
– Moreover, most of the businesses are primarily driven by increased consumerization, competition, and data explosion. Complexity and scalability of disparate data pose a challenge for the traditional analytics and database technologies. Real-time processing of big data, using the cloud as an enabler, has become the norm. Disruptive technologies that underpin SMAC (social, mobile, analytics, and cloud) are driving new business scenarios, which make the best use of data.
– BDaaS has taken things to a whole new level, by combining these tools and applying them to massively large data sets, in order to help large and small organizations meet today’s Big Data demands in a cost-effective manner.
– Also, with the emergence of fully automated trading systems such as high-frequency trading platforms (HFT) that analyze market and execute trades in a matter of milliseconds without any human intervention is enabling the rise of streaming analytics. For instance, platforms such as Amazon Kinesis, Kafka, Flink enable high-throughput and fault-tolerant processing of real-time data.
– Software companies are currently increasing their focus on in-demand technologies and re exploring innovative ways to service their clients as the covid-19 crisis is creating challenges across multiple industries and is leading to a reduction in technology spending.
– With COVID-19 crisis having a major impact in the manufacturing industry, it is likely that most of the existing company suppliers are having challenges to fulfil the urgent requirements. From government health departments to private medical device providers, both are struggling to fulfil the sudden surge in demand for key safety gears to counter COVID-19.
Key Market Trends
Big Data Analytics in Banking is Expected to Grow Significantly
– As technology is advancing, the number of devices that consumers use to initiate transactions is also increasing (such as smartphones), making the number of transactions increase. This rapid growth in data requires better acquisition, organization, integration, and analysis.
– Considering the regional analysis of government regulations, the government’s approach in every region varies in intensity. The European banks are taking stronger regulatory approaches than their Asian counterparts. For instance, in Europe, regulations have been significant catalysts for the rise of open banking. These include Europe’s implementation of its Second Payment Services Directive (PSD2) and the UK Competition and Markets Authority’s (CMA) Open Banking regulation.
– According to Open Banking Implementation Entity (OBIE), API calls increased from one million a month in May 2018, to more than 66.7 million in June 2019. (PSD2 mandates that banks create APIs (vehicles for bundling and sharing discrete data sets between organizations) for digital banking transactions.
– Danske Bank is the largest bank in Denmark, with a customer base of more than 5 million. It utilizes its in-house advanced analytics to identify fraud while reducing false positives. Thus, after implementing a modern enterprise analytics solution, the bank realized a 60% reduction in false positives, which increased true positives by 50%.
Asia Pacific to Hold Major Market Share
– The Asia Pacific region is expected to hold a significant market owing due to the increasing rate of internet, smartphone generation, and ever-growing urbanization development in machine learning, algorithm development, and the need for customer and behavioral analytics.For instance, as per Xinhuanet, China has 854 million internet users currently. The volume of data and users offers significant advantages, such as more data powers, more accurate predictive models, and more productive analysis. It also supports more advanced machine learning and more profound learning techniques.
– The potential for Big Data to revolutionize the country is massive. China has one of the world’s largest and most valuable consumer market. It is already the world’s workshop, producing many goods for export. Big Data engineering services is expected to provide opportunities for the enormous Chinese consumer market, and it is likely to assist Chinese firms looking to engage in high-value economic activities. For instance, As per the Ministry of Industry and Information Technology, China’s Big Data sector aims to increase its annual sales to CNY 1 trillion by 2020, from an estimated CNY 280 billion in 2015.
– Also, within the emerging economies such as India, global technology vendors are leveraging partnerships and collaboration with local vendors as a competitive strategy to counter the growing demand for digital analytics and enterprise-scale AI solutions and services across the region. For instance, In May 2020, Accenture plc announced the acquisition of Byte Prophecy, a big data analytics company. The company aims to deliver emerging client needs with speed and scale and enhance its portfolio of technologies to help its client across its AI markets.
– Additionally, companies in the region embrace cloud adoption by shifting their IT operations out of their data center and into the cloud. It is expected to further leverage the adoption of big data engineering services as companies in the region demand reduced costs and greater flexibility.
Competitive Landscape
The Big Data Engineering Services Market is moderately fragmented and holds the potential to shift rivalry by opening up new avenues for differentiation and value-added services. Thereby, few prominent vendors including Accenture Plc, Capgemini SE in the market are leveraging acquisitions and investments into new startups and technologies to capture the intelligence market and leverage their service offerings
– April 2020: Capgemini SE announced the acquisition of Advectas AB, a business intelligence and data science company based in Sweden. Advectas is integrated into the company’s insights and data business unit, as the company aims to leverage the growing client demand for data analytics services. Further, going forward the company expects ongoing growth of 4% for 2020 and aims its focus in expanding into the intelligence industry market.
– March 2020: Infosys Limited reported an investment of USD 4.5 million into US-based startup Waterline Data Science through its innovation funds. The startup offers data governance and data discovery software and also provides business analysts and data scientists a self-service data catalog to help understand the data.
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1 INTRODUCTION
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Market Drivers
4.2.1 Increasing Volume of Unstructured Data, Due to the Phenomenal Growth of Interconnected Devices and Social Media
4.2.2 Cost-Effective Services and Cutting-Edge Expertise Rendered By Data Servicing Companies
4.3 Market Restraints
4.3.1 Inability of Service Providers to Provide Real-Time Insights
4.4 Porters FIve Force Analysis
4.4.1 Threat of New Entrants
4.4.2 Bargaining Power of Buyers/Consumers
4.4.3 Bargaining Power of Suppliers
4.4.4 Threat of Substitute Products
4.4.5 Intensity of Competitive Rivalry
4.5 Assessment on the Impact of COVID-19 on the market
5 EMERGING TECHNOLOGY TRENDS
6 MARKET SEGMENTATION
6.1 By Type**
6.1.1 Data Modelling
6.1.2 Data Integration
6.1.3 Data Quality
6.1.4 Analytics
6.2 By Business Function
6.2.1 Marketing and Sales
6.2.2 Finance
6.2.3 Operations
6.2.4 Human Resource
6.3 By Organization Size
6.3.1 Small and Medium Enterprizes
6.3.2 Large Enterprises
6.4 By Deployement Type
6.4.1 Cloud
6.4.2 On-Premise
6.5 By End-user Industry
6.5.1 BFSI
6.5.2 Government
6.5.3 Media and Telecommunication
6.5.4 Retail
6.5.5 Manufacturing
6.5.6 Healthcare
6.5.7 Other End-user Verticals
6.6 Geography
6.6.1 North America
6.6.2 Europe
6.6.3 Asia-Pacific
6.6.4 Latin America
6.6.5 Middle East & Africa
7 COMPETITIVE LANDSCAPE
7.1 Company Profiles*
7.1.1 Accenture PLC
7.1.2 Genpact Inc.
7.1.3 Cognizant Technology Solutions Corporation
7.1.4 Infosys Limited
7.1.5 Capgemini SE
7.1.6 NTT Data Inc.
7.1.7 Mphasis Limited
7.1.8 L&T Technology Services
7.1.9 Hexaware Technologies Inc.
7.1.10 KPMG LLP
7.1.11 Ernst & Young LLP
7.1.12 Latentview Analytics Corporation
8 INVESTMENT ANALYSIS
9 MARKET OPPORTUNITIES AND FUTURE TRENDS