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市場調查報告書
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1445663

巨量資料工程服務 - 市場佔有率分析、產業趨勢與統計、成長預測（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個工作天內

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簡介目錄

巨量資料工程服務市場規模預計到2024年為793.4億美元，預計到2029年將達到1622.2億美元，在預測期內（2024-2029年）CAGR為15.38%。

巨量資料工程服務-市場

應用程式介面對於資料整合和工程是必需的。資料工程師使用專門的工具、程序和設備來準備和分析資料以供以後分析。讓資料變得有價值從資料工程開始。

主要亮點

  • COVID-19 大流行為資料分析師提供了研究全球巨量資料模式的絕佳機會。任何組織都可以從這種資料工程策略方法中受益，但這對於銀行等旨在逐步發展同時快速創新的行業至關重要。
  • 金融業正在迅速變化並提供新的消費產品和服務。銀行業將大大影響數據工程市場。澳洲國民銀行和 Amazon Web Services 的合作夥伴關係不斷發展。據該銀行稱，其 70% 的程式現已遷移到雲端，並且它剛剛成為第一家轉換其線上商業銀行平台的澳洲大型銀行。
  • 醫療保健中使用的資料量正在快速成長。電子健康記錄是醫療保健產業最普遍的重要資料來源。與過去相比，當這些資訊儲存在手寫檔案中時，借助電子病歷創建的大量資料和機器學習等強大的分析技術，醫學研究人員現在可以創建預測模型。
  • 對於資料工程專案來說，不理解特定使用者群組的需求是很困難的。不斷湧入的資料和處理價值不一致的問題很快就會變得不堪重負。透過資料治理計劃建立全面的資料管理策略是應對此資料工程課題的潛在應對措施。

巨量資料工程服務市場趨勢

銀行業巨量資料分析預計將顯著成長

  • 隨著科技的發展，消費者使用更多的設備來發起交易。金融部門正在迅速發展，並向消費者推出新的服務和商品。實際的困難在於如何保存新鮮資料、如何將其與所有舊資料連接起來以及如何在新產品和服務中使用。由於巧妙的資料設計可以帶來更具適應性的業務模型，因此資料工程是一個至關重要的領域。
  • 2022 年 7 月 - HDFC 銀行與 NIIT 金融、銀行和保險研究所 (NIIT IFBI) 簽署協議，培訓和僱用資料工程師。在此類計畫的幫助下，BFSI 部門將提高其數位技能，學生將能夠在資料工程領域發展紮實的職業生涯，並促進利用分析來獲得業務洞察力。該銀行預計每年透過該計劃聘用近 100 名資料科學家。
  • 2022 年 7 月 - 為了擴大數位經濟的勞動力，聯邦銀行與莫納什大學和皇家墨爾本理工大學合作建立一個中心，為 400 多名軟體開發人員、雲端工程師和網路專業人員提供服務。該計劃的目標是促進銀行業創新、技術和能力。

亞太地區將佔據主要市場佔有率

  • 由於網路、智慧型手機的普及和城市化的快速發展，亞太地區預計將擁有重要的市場。過去五年來，對數位能力的需求，特別是對人工智慧/機器學習、巨量資料分析和資料科學的人才的需求不斷上升。
  • NASSCOM 的一項調查顯示，由於對數據科學和人工智慧專家的需求不斷成長，到 2024 年，印度預計將擁有超過 100 萬名專家。印度在人工智慧人才集中度和技能滲透率報告中排名第一，在人工智慧科學出版物方面排名第五。截至 2022 年 8 月，印度已安裝的技能總數為 41.6 萬，對 DS&AI 的總體需求為 62.9 萬。現有人才總數的 46% 包括機器學習工程師和資料工程師。
  • 2022年3月 - 為了為數據相關行業的高潛力員工創建全行資料分析計劃，中國建設銀行股份有限公司（CCB）與香港大學商學院合作。由於這種關係，銀行可以更好地識別消費者對貸款、金融產品和付款的需求。

巨量資料工程服務業概況

憑藉差異化和加值服務的新機遇，適度分散的巨量資料工程服務市場有可能改變競爭格局。由於眾多產業都在人工智慧方面進行廣泛投資，因此對巨量資料工程技術和能力的需求很高。為了在智慧領域獲得市場佔有率並擴大其服務範圍，埃森哲等知名廠商Plc 和Capgemini SE 正在對新公司和新技術進行收購和投資。

  • 2022 年 11 月 - 埃森哲與日本人工智慧和巨量資料分析服務公司合作，增加了龐大的資料科學家團隊。為了做出更好、更快的決策，企業現在需要對其營運進行 360 度視角。需要數據科學專業知識和人工智慧能力才能獲得這種全面的觀點並能夠複製組織的每個領域。
  • 2022 年 12 月 - Cognizant 宣布與企業資料管理領域的市場領導者 Syniti 建立策略合作夥伴關係。Syniti 知識平台 (SKP) 透過簡化資料轉換加快向SAP S/4HANA 的遷移。對於基於SAP 的轉換，使用SAPAP高階資料遷移的客戶管理階層發現資料遷移速度提高了 46%。

額外的好處：

  • Excel 格式的市場估算 (ME) 表
  • 3 個月的分析師支持

目錄

第 1 章：簡介

  • 研究假設和市場定義
  • 研究範圍

第 2 章：研究方法

第 3 章：執行摘要

第 4 章：市場動態

  • 市場概況
  • 市場促進因素
    • 由於互連設備和社群媒體的驚人成長，非結構化資料量不斷增加
    • 數據服務公司提供具有成本效益的服務和尖端專業知識
  • 市場限制
    • 服務提供者無法提供即時洞察
  • 波特五力分析
    • 新進入者的威脅
    • 買家/消費者的議價能力
    • 供應商的議價能力
    • 替代產品的威脅
    • 競爭激烈程度
  • COVID-19 對市場的影響評估

第 5 章：新興科技趨勢

第 6 章：市場區隔

  • 依類型
    • 資料建模
    • 數據整合
    • 數據品質
    • 分析
  • 依業務職能
    • 行銷與銷售
    • 金融
    • 營運
    • 人力資源
  • 依組織規模
    • 中小企業
    • 大型企業
  • 依部署類型
    • 雲
    • 本地部署
  • 依最終用戶產業
    • BFSI
    • 政府
    • 媒體和電信
    • 零售
    • 製造業
    • 衛生保健
    • 其他最終用戶垂直領域
  • 地理
    • 北美洲
    • 歐洲
    • 亞太
    • 拉丁美洲
    • 中東和非洲

第 7 章：競爭格局

  • 公司簡介
    • 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 8 章：投資分析

第 9 章：市場機會與未來趨勢

簡介目錄
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. Making data valuable begins with data engineering.

Key Highlights

  • The COVID-19 pandemic has provided data analysts with fantastic opportunities to research global Big Data patterns. Any organization would benefit from this strategic approach to data engineering, but it is crucial for businesses in sectors like banking that aim to develop gradually while simultaneously innovating quickly.
  • The financial industry is quickly changing and providing new consumer products and services. The Banking Industry would significantly impact Data Engineering Market. The National Australia Bank and Amazon Web Services partnership have 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. In contrast to the past, when 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.
  • 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 challange.

Big Data Engineering Services Market Trends

Big Data Analytics in Banking is Expected to Grow Significantly

  • As technology develops, there are more devices being used by consumers to initiate transactions. The financial sector is evolving rapidly and introducing new services and goods to consumers. The actual difficulty is how fresh data is kept, connected to all the old data, and used in new product and services. Because clever data design can lead to more adaptable business models, data engineering is a crucial field.
  • July 2022 - HDFC bank signed a deal with NIIT Institute of Finance, Banking and Insurance (NIIT IFBI), to train and hire Data Engineers. With the help of such programs, the BFSI sector will improve its digital skills, and students will be able to develop a solid career in data engineering and foster the use of analytics to gain business insights. The bank anticipates hiring close to 100 data scientists through this initiative each year.
  • July 2022 - In order to expand the workforce for the digital economy, Commonwealth Bank teams up with Monash University and RMIT University to build a centre that will serve more than 400 software developers, cloud engineers, and cyber professionals. The program's goal is to advance banking innovation, technology, and competency.

Asia Pacific to Hold Major Market Share

  • The Asia Pacific region is expected to hold a significant market Due to the rapid growth of the internet, the smartphone generation, and urbanization. The demand for digital capabilities, particularly for talent in artificial intelligence/machine learning, big data analytics, and data science, has risen over the last five years.
  • According to a NASSCOM survey, India is expected to have more than 1 million experts by 2024 due to the rising demand for Data Science & AI specialists. India ranked first in the report for AI talent concentration and skill penetration and fifth for AI scientific publications. India had a total installed skill base of 416K and a 629K overall demand for DS&AI as of August 2022. 46% of the total established talent comprises ML engineers and data engineers.
  • March 2022 - To create a bank-wide data analytics program for high-potential employees working in data-related sectors, China Construction Bank Corporation (CCB) cooperated with HKU Business School. As a result of this relationship, the bank can better identify consumer needs for loans, financial products, and payments.

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. Because so many sectors are investing extensively in AI, 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.

  • November 2022 - Accenture tied up with Japanese AI and big data analytics services to add a large team of data scientists.To make better and quicker decisions, businesses now require a 360-degree view of their operations. Data science expertise and AI capabilities are needed to obtain this comprehensive viewpoint and be able to replicate every area of the organization.
  • December 2022 - Cognizant announced a strategic partnership with Syniti the market leaders in enterprise data management.Syniti Knowledge Platform (SKP) speeds migration to SAP S/4HANA by streamlining data transformation.For their SAP-based transformations, customers who use SAP Advanced Data Migration and Management see a 46% faster data migration.

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 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