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市场调查报告书
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巨量资料工程服务：市场占有率分析、产业趋势与统计、成长预测（2024-2029）

Big Data Engineering Services - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3个工作天内

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简介目录

巨量资料工程服务市场规模预计到 2024 年为 793.4 亿美元，预计到 2029 年将达到 1622.2 亿美元，在预测期内（2024-2029 年）复合年增长率为 15.38%。

大数据工程服务-市场

资料整合和工程需要应用程式介面。资料工程师使用专用的工具、程序和设备来准备和分析资料以供以后分析。

主要亮点

  • 巨量资料工程服务市场的成长受到几个关键因素的推动。首先，在数位技术激增的推动下，各行业资料生成呈指数级增长，对先进资料管理和处理解决方案的需求正在迅速增长。随着公司寻求利用资料的潜力，他们越来越多地转向巨量资料工程服务来优化储存、处理和分析能力。
  • 金融业正在迅速变化并提供新的消费产品和服务。银行业预计将对资料工程市场产生重大影响。例如，澳洲国民银行和亚马逊网路服务之间的合作关係正在不断发展。该银行表示，其 70% 的程式现已转移到云端，并且刚刚成为第一家转换其线上商业银行平台的澳洲大型银行。
  • 医疗保健中使用的资料量正在迅速增加。电子健康记录是医疗保健产业最普遍且最重要的资料来源。以前，这些资讯储存在手写檔案中。借助电子病历创建的大量资料和机器学习等强大的分析技术，医学研究人员现在能够创建预测模型。
  • 此外，机器学习和人工智慧的进步为从大型资料集提取有价值的见解开闢了新的可能性，促使组织投资资料工程服务以支援其人工智慧倡议。此外，资料隐私和安全的监管要求迫使公司采用更强大的资料管理实践，增加了对巨量资料工程专业知识的需求。
  • 对于资料工程计划来说，不了解特定使用者群体的需求是很困难的。处理无穷无尽的资料涌入和价值失调很快就会变得不堪重负。透过资料管治计划建立全面的资料管理策略是应对此资料工程挑战的潜在应对措施。

巨量资料工程服务市场趋势

银行业巨量资料分析预计将大幅成长

  • 银行业正在见证巨量资料分析和工程的采用迅速增加。其主要原因是巨量资料分析在提高业务效率、客户体验和风险管理方面提供的巨大价值。摩根大通和富国银行等公司正在大力投资巨量资料计划，以利用业务中产生的大量资料。
  • 此外，巨量资料工程有助于处理、储存和分析大量资料集，使银行能够有效地处理资料的速度、种类和数量。 Hadoop 和 Spark 等技术使银行能够大规模储存和处理资料，从而加快决策速度并改善客户服务。
  • 此外，数位银行的成长和线上交易的盛行进一步增加了银行业对巨量资料解决方案的需求。透过利用先进的分析和机器学习演算法，银行可以提出个人化提案、简化业务并有效降低风险。
  • 2023 年 12 月，印度联合银行与Accenture合作建构可扩展且安全的企业资料湖平台。该措施旨在提高业务效率，提供以客户为中心的银行服务并改善风险管理。该平台利用预测分析、机器学习和人工智慧从结构化和资料中产生有价值的见解。此外，它还为员工提供跨各种职能的强大资料视觉化和报告功能。

亚太地区占主要市场占有率

  • 近年来，由于数位技术的采用不断增加，对资料主导决策的需求不断增长，包括中国、新加坡、印度和马来西亚在内的亚太地区的巨量资料工程市场出现了显着增长 以及互联网连接设备的激增 以及互联网连接设备的激增。这些地区的企业正在认识到利用大量资料来获取洞察并在全球市场上保持竞争力的价值。
  • 阿里巴巴、腾讯等主要企业处于巨量资料创新的前沿，利用其广泛的用户基础和先进的分析能力，提供个人化服务并提高业务效率。例如，阿里巴巴的云端运算部门阿里云提供各种巨量资料解决方案，包括资料仓储、分析和人工智慧服务，为各行业的公司提供服务。
  • 此外，东南亚领先的超级应用程式 Grab 等公司严重依赖巨量资料工程来优化其叫车、食品配送和金融服务平台。 Grab 利用资料分析来改善使用者体验、优化司机分配并开发适合客户偏好的新产品和服务，从而为公司的快速扩张和市场主导地位做出贡献。
  • 同时，在马来西亚，亚航等公司正在利用巨量资料工程来改变航空业，提供个人化的旅行体验，并透过预测分析和机器学习演算法优化营运。亚航的资料主导方法使我们能够简化流程、降低成本并在高度动态的航空市场中保持竞争力。
  • 总体而言，亚太地区巨量资料工程市场的成长反映了数位转型和创新的更广泛趋势，随着竞争的加剧，各行业的公司都利用资料的力量来推动业务成功并释放新的成长和差异化机会。

巨量资料工程服务业概况

凭藉差异化和附加价值服务的新机会，适度分散的巨量资料工程服务市场有可能改变竞争格局。此外，许多行业都在人工智慧方面进行了大量投资，对巨量资料工程技能和能力的需求很高。为了获得市场占有率并扩大其在情报领域的服务范围，埃森哲 (Accenture PLC) 和凯捷 (Capgemini SE) 等知名供应商正在收购和投资新公司和新技术。

  • 2023 年 10 月 Google Cloud 合作伙伴 Onyx 收购资料 ，这是一家以 IP主导的顾问公司，专门从事资料迁移、现代化和 BI/分析。 Datametica 独特的产品套件可自动将资料仓储、资料库、ETL 流程和分析工作负载迁移到 Google Cloud 并实现现代化，为客户提供快速结果并保证结果。这项策略性倡议增强了 Onix 的资料和人工智慧能力，并将其定位为 IP主导的云端转型和资料管理解决方案的领导者。
  • 2023 年 2 月，Alteryx 宣布在 Alteryx 分析云端平台中增强自助服务和企业级功能。重新设计的 Alteryx Designer Cloud 介面使现代资料工作者能够以互动方式和协作方式分析、准备和管道资料。 Alteryx Auto Insights 让分析师和资料工程师能够轻鬆建立互动式报告，利用机器学习来显示描述性值和关键驱动因素，以做出更好的决策。该平台的可扩展性和安全性使组织能够做出更快、更明智的决策，同时维护资料管治标准。

其他好处：

  • Excel 格式的市场预测 (ME) 表
  • 3 个月的分析师支持

目录

第一章简介

  • 研究假设和市场定义
  • 调查范围

第二章调查方法

第三章执行摘要

第四章市场动态

  • 市场概况
  • 市场驱动因素
    • 由于互连设备和社群媒体的显着成长，非结构化资料量不断增加
    • 来自资讯服务公司的具有成本效益的服务和尖端专业知识
  • 市场限制因素
    • 服务提供者无法提供即时见解
  • 波特五力分析
    • 新进入者的威胁
    • 买家/消费者的议价能力
    • 供应商的议价能力
    • 替代品的威胁
    • 竞争公司之间敌对关係的强度
  • 评估宏观经济因素对市场的影响

第五章 新科技趋势

第六章 市场细分

  • 按类型
    • 资料建模
    • 资料整合
    • 资料品质
    • 分析
  • 按业务
    • 行销和销售
    • 金融
    • 手术
    • 人力资源
  • 按组织规模
    • 小型企业
    • 大公司
  • 依部署类型
    • 云
    • 本地
  • 按最终用户产业
    • BFSI
    • 政府机构
    • 媒体/通讯
    • 零售业
    • 製造业
    • 卫生保健
    • 其他最终用户产业
  • 地区
    • 北美洲
    • 欧洲
    • 亚太地区
    • 拉丁美洲
    • 中东/非洲

第七章 竞争格局

  • 公司简介
    • Accenture PLC
    • Genpact Inc.
    • Cognizant Technology Solutions Corporation
    • Infosys Limited
    • Capgemini SE
    • NTT Data Inc.
    • Mphasis Limited
    • L&T Technology Services
    • Hexaware Technologies Inc.
    • KPMG LLP
    • Ernst & Young LLP
    • Latentview Analytics Corporation

第八章投资分析

第九章 市场机会及未来趋势

简介目录
Product Code: 71352

The Big Data Engineering Services Market size is estimated at USD 79.34 billion in 2024, and is expected to reach USD 162.22 billion by 2029, growing at a CAGR of 15.38% during the forecast period (2024-2029).

Big Data Engineering Services - Market

Application programming interfaces are necessary for data integration and engineering. Data engineers use specialized tools, procedures, and equipment to prepare and analyze data for later analysis.

Key Highlights

  • The growth of the big data engineering services market has been driven by several key factors. Firstly, the exponential increase in data generation across various industries, fueled by the proliferation of digital technologies, has created a pressing need for advanced data management and processing solutions. As organizations seek to harness the potential of their data, they increasingly turn to big data engineering services to optimize storage, processing, and analysis capabilities.
  • The financial industry is quickly changing and providing new consumer products and services. The banking industry is expected to significantly impact the data engineering market. For instance, the partnership between the National Australia Bank and Amazon Web Services has grown. According to the bank, 70% of its programs have now been migrated to the cloud, and it just became the first significant Australian bank to convert its online business banking platform.
  • The amount of data used in healthcare is growing quickly. Electronic health records are the most prevalent significant data source in the healthcare industry. Earlier, this information was stored in handwritten files. Medical researchers can now create prediction models thanks to the enormous data created by EHRs and powerful analytics techniques like machine learning.
  • Furthermore, advancements in machine learning and artificial intelligence have opened up new possibilities for extracting valuable insights from large datasets, prompting organizations to invest in data engineering services to support their AI initiatives. Additionally, regulatory requirements around data privacy and security have compelled companies to adopt more robust data management practices, leading to increased demand for specialized big data engineering expertise.
  • Not comprehending the needs of a specific user group is difficult for a data engineering project. The endless influx of data and dealing with value inconsistencies can quickly become overwhelming. Establishing a thorough data management strategy with a data governance plan is one potential response to this data engineering challenge.

Big Data Engineering Services Market Trends

Big Data Analytics in Banking is Expected to Grow Significantly

  • The banking industry has witnessed a significant surge in the adoption of big data analytics and engineering, primarily due to the immense value they offer in enhancing operational efficiency, customer experience, and risk management. Companies like JPMorgan Chase and Wells Fargo have invested heavily in big data initiatives to harness the vast amounts of data generated within their operations.
  • Furthermore, big data engineering facilitates the processing, storage, and analysis of massive datasets, enabling banks to handle the velocity, variety, and volume of data efficiently. With technologies like Hadoop and Spark, banks can store and process data at scale, enabling faster decision-making and improved customer service.
  • Moreover, the growth of digital banking and the proliferation of online transactions have further fueled the demand for big data solutions in the banking sector. By leveraging advanced analytics and machine learning algorithms, banks can offer personalized recommendations, streamline operations, and mitigate risks effectively.
  • In December 2023, Union Bank of India partnered with Accenture to create a scalable and secure enterprise data lake platform. This initiative aims to enhance operational efficiency, provide customer-centric banking services, and improve risk management. The platform will leverage predictive analytics, machine learning, and artificial intelligence to generate valuable insights from structured and unstructured data. Additionally, it will empower employees with robust data visualization and reporting capabilities across various functions.

Asia-Pacific to Hold Major Market Share

  • The big data engineering market in Asia-Pacific countries like China, Singapore, India, Malaysia, and others has experienced significant growth in recent years, driven by factors such as increasing adoption of digital technologies, rising demand for data-driven decision-making, and the proliferation of internet-connected devices. Companies in these regions are recognizing the value of harnessing vast amounts of data to gain insights and stay competitive in the global market.
  • Key players like Alibaba and Tencent have been at the forefront of big data innovation, leveraging their extensive user bases and advanced analytics capabilities to offer personalized services and improve operational efficiency. For example, Alibaba's cloud computing arm, Alibaba Cloud, provides a range of big data solutions, including data warehousing, analytics, and artificial intelligence services, catering to businesses across various industries.
  • Moreover, companies like Grab, a key super app in Southeast Asia, rely heavily on big data engineering to optimize their ride-hailing, food delivery, and financial services platforms. Grab utilizes data analytics to enhance user experiences, optimize driver allocation, and develop new products and services tailored to customer preferences, contributing to its rapid expansion and market dominance.
  • Meanwhile, in Malaysia, companies like AirAsia are leveraging big data engineering to transform the aviation industry, offering personalized travel experiences and optimizing flight operations through predictive analytics and machine learning algorithms. AirAsia's data-driven approach has enabled it to streamline processes, reduce costs, and maintain a competitive edge in the highly dynamic airline market.
  • Overall, the growth of the big data engineering market in Asia-Pacific countries reflects a broader trend toward digital transformation and innovation, with companies across various sectors harnessing the power of data to drive business success and unlock new opportunities for growth and differentiation in an increasingly competitive landscape.

Big Data Engineering Services Industry Overview

With new opportunities for differentiation and value-added services, the moderately fragmented big data engineering services market has the potential to change the competitive landscape. Moreover, many sectors are investing extensively in artificial intelligence, and there is a high demand for big data engineering technology and capabilities. In order to gain market share in the intelligence sector and expand the scope of their service offerings, well-known vendors, such as Accenture PLC and Capgemini SE, are making acquisitions and investments in new companies and technologies.

  • October 2023: Onix, a Google Cloud partner, acquired Datametica, an IP-driven consulting firm specializing in data migration, modernization, and BI/analytics. Datametica's suite of proprietary products automates the migration and modernization of data warehouses, databases, ETL processes, and analytical workloads to Google Cloud, delivering faster results and guaranteed outcomes for customers. This strategic move enhances Onix's data and AI capabilities, positioning them as a leader in IP-driven solutions for cloud transformation and data management.
  • February 2023: Alteryx introduced enhanced self-service and enterprise-grade features in its Alteryx Analytics Cloud Platform. The reimagined Alteryx Designer Cloud interface empowers modern data workers to profile, prepare, and pipeline their data interactively and collaboratively. Analysts and data engineers can now build interactive reports with ease, and Alteryx Auto Insights leverages machine learning to surface explanatory values and key drivers for better decision-making. The platform's scalability and security ensure that organizations can make faster and more informed decisions while maintaining data governance standards.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

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 Porter's 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 of the Impact of Macroeconomic Factors 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