Big Data and Data Engineering Services Market Share Report 2028F

Summary

Report Description

Forecast Period	2024-2028
Market Size (2022)	USD 70.46 Billion
CAGR (2023-2028)	16.27%
Fastest Growing Segment	Small & Medium-Sized Enterprises
Largest Market	North America

Market Overview

The projected market size for the global big data and data engineering services market is expected to reach USD 70.46 billion by the end of 2022, with a compound annual growth rate (CAGR) of 16.27% during the forecast period. The global big data and data engineering services market is a rapidly expanding sector driven by the exponential growth of data and the need for businesses to extract meaningful insights. These services encompass a comprehensive range of solutions that manage, process, and analyze vast and complex datasets. With the increasing recognition of data as a strategic asset, organizations across industries are leveraging these services to make informed decisions, drive innovation, and enhance their competitive edge. The integration of advanced technologies like AI and machine learning further propels the market's growth, enabling predictive and prescriptive analytics. As data continues to play a pivotal role in shaping business strategies, the Big Data and Data Engineering Services market is poised to evolve, offering scalable solutions that address the challenges of data management, integration, and analysis in an increasingly interconnected world.

Key Market Drivers

Exponential Growth of Data

The relentless growth of data, often referred to as the "data explosion," is a primary driver propelling the global Big Data and Data Engineering Services market. With the advent of digital technologies, IoT devices, and social media, the volume, variety, and velocity of data generated have reached unprecedented levels. Organizations across industries are grappling with massive datasets, creating a demand for services that can effectively manage, process, and analyze this information. Big Data and Data Engineering Services provide the infrastructure and tools needed to handle these vast datasets, extracting valuable insights to drive decision-making, innovation, and competitive advantage.

Data-Driven Decision-Making

In today's data-driven business landscape, organizations are increasingly relying on data to make informed decisions. Big Data and Data Engineering Services empower businesses to transform raw data into actionable insights. By leveraging these services, organizations gain the ability to analyze historical patterns, identify trends, and forecast future outcomes. Data-driven decision-making enhances operational efficiency, optimizes resource allocation, and fosters innovation. As businesses recognize the significance of data-driven strategies, the demand for services that enable efficient data processing and analysis continues to surge.

Rise of Cloud Computing

The proliferation of cloud computing has revolutionized the Big Data and Data Engineering Services market. Cloud platforms offer scalable, cost-effective solutions that cater to the storage, processing, and analysis of massive datasets. Cloud-based services provide flexibility, enabling organizations to dynamically scale their infrastructure as data volumes grow. This scalability is particularly crucial in handling unpredictable workloads, ensuring optimal performance without incurring significant upfront costs. The accessibility and ease of deployment of cloud-based Big Data and Data Engineering Services have democratized their adoption, enabling businesses of all sizes to leverage advanced data capabilities.

Advancements in Analytics and AI

The convergence of Big Data and artificial intelligence (AI) has paved the way for advanced analytics that extract deeper insights from complex datasets. Machine learning algorithms can uncover hidden patterns, correlations, and anomalies that traditional methods may overlook. As AI-driven predictive and prescriptive analytics gain prominence, businesses are leveraging Big Data and Data Engineering Services to build and deploy AI models. These services enable organizations to develop and fine-tune algorithms that enhance customer experiences, optimize operations, and drive innovation across various industries.

Regulatory Compliance and Data Security

The evolving regulatory landscape, including regulations like GDPR and CCPA, has placed increased emphasis on data privacy and security. Organizations are under pressure to ensure the responsible and secure handling of customer data. Big Data and Data Engineering Services offer solutions that aid in data governance, encryption, and secure data transmission. These services help organizations comply with regulations while maintaining the integrity of sensitive information. The growing awareness of data breaches and the need for robust security measures drive the adoption of these services, fostering trust among customers and stakeholders.

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Key Market Challenges

Data Privacy and Security Concerns

As organizations increasingly rely on big data and data engineering services to extract insights and drive decision-making, the challenge of ensuring data privacy and security has become paramount. The massive volumes of data being processed and stored create attractive targets for cyberattacks and data breaches. Ensuring compliance with data protection regulations such as GDPR, HIPAA, and CCPA presents a significant hurdle. Balancing the need for data accessibility with stringent security measures while navigating evolving regulatory landscapes is a complex task.

Scalability and Performance Optimization

The exponential growth of data poses a substantial challenge in terms of scalability and performance optimization. As businesses generate and process massive amounts of data, traditional data processing frameworks often struggle to handle the load efficiently. Data engineering services need to develop and implement advanced techniques such as distributed computing, parallel processing, and real-time data processing to ensure that systems can scale seamlessly and deliver high performance without bottlenecks.

Data Quality and Integration

The diverse sources from which data is collected often lead to issues of data quality, consistency, and integration. Different data formats, structures, and varying levels of data accuracy can hinder the effectiveness of Big Data and Data Engineering initiatives. Addressing these challenges requires robust data cleansing, transformation, and integration strategies. Ensuring that the data being processed is accurate, reliable, and consistent is essential to derive meaningful insights and make informed decisions.

Talent Shortage and Skill Gap

The rapidly evolving landscape of Big Data and Data Engineering services has led to a shortage of skilled professionals in the field. There is a significant gap between the demand for data engineers, data scientists, and related roles, and the availability of qualified individuals to fill these positions. This challenge is compounded by the need for expertise in areas such as machine learning, artificial intelligence, and cloud technologies. Organizations must invest in training and upskilling initiatives to build a workforce that can effectively manage and leverage complex data ecosystems.

Cost Management and ROI Demonstration

While investing in big data and data engineering services holds the promise of delivering valuable insights and driving business growth, managing the associated costs, and demonstrating a clear return on investment (ROI) remains a challenge. Implementing and maintaining the required infrastructure, tools, and talent can be expensive. Additionally, quantifying the tangible benefits of data-driven initiatives in terms of revenue generation, cost savings, or improved operational efficiency can be challenging. Organizations need to develop robust metrics and analytics frameworks to measure the impact of their data initiatives accurately.

Key Market Trends

Evolution towards Real-time Data Processing and Analytics

One of the prominent trends shaping the global Big Data and Data Engineering Services market is the increasing shift towards real-time data processing and analytics. Traditional batch processing methods are no longer sufficient to meet the demands of modern businesses that require instant insights for quick decision-making. Organizations are adopting real-time data processing frameworks like Apache Kafka and technologies like stream processing to analyze and respond to data as it is generated. This trend is particularly relevant in sectors such as e-commerce, finance, and IoT, where timely actions based on up-to-the-moment data are crucial. As a result, data engineering services are focusing on developing architectures that support low-latency processing, ensuring that businesses can extract actionable insights from their data in real time.

Cloud-Native Data Engineering and Serverless Computing

The migration to cloud-native solutions and the adoption of serverless computing models are significant trends influencing the Big Data and Data Engineering Services market. Cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud offer scalable and flexible infrastructure that allows organizations to store, process, and analyze large volumes of data without the need for extensive upfront investments in hardware. Serverless computing simplifies data processing by automatically managing the infrastructure, enabling data engineers to focus more on designing data pipelines and less on managing the underlying infrastructure. This trend is driving the demand for cloud-native data engineering services, including expertise in cloud-based data storage, computation, and integration.

Segmental Insights

Business Function Insights

Based on business function, the marketing & sales segment emerges as the predominant segment, exhibiting unwavering dominance projected throughout the forecast period. This prominence underlines the critical role that data-driven insights play in shaping modern marketing and sales strategies. As businesses endeavor to engage customers in an increasingly personalized and targeted manner, the utilization of big data and data engineering services becomes paramount. The marketing & sales segment leverages these services to unravel consumer behavior patterns, preferences, and trends, thereby enabling organizations to refine their outreach efforts and tailor their offerings more effectively. By transforming raw data into actionable insights, this segment empowers businesses to optimize customer experiences, streamline marketing campaigns, and enhance sales conversion rates.

End User Insights

Based on end user, the BFSI segment emerges as a formidable frontrunner, exerting its dominance and shaping the market's trajectory throughout the forecast period. This sector's commanding presence underscores its strategic recognition of the transformative potential of big data and data engineering. As financial institutions strive to remain competitive in an increasingly data-driven landscape, the BFSI segment harnesses these services to extract valuable insights, enhance risk management, personalize customer experiences, and optimize operational efficiency. With vast amounts of transactional and customer data at their disposal, banks and insurance companies deploy big data and data engineering services to decipher patterns, detect anomalies, and tailor products and services to meet the evolving demands of their clientele. This dominance signifies the sector's commitment to leveraging cutting-edge technologies to remain at the forefront of innovation, setting a precedent for other industries. As data continues to drive the financial services landscape, the BFSI segment's influential position is projected to persist, shaping the trajectory of the global big data and data engineering services market.

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Regional Insights

North America remains steadfast in its position of dominance within the global big data and data engineering services market, reaffirming its pivotal role in shaping the industry's trajectory. North America stands out as a significant powerhouse in the big data and data engineering services market. This prominence can be attributed to the concentration of technology giants, startups, and enterprises that have embraced data-driven decision-making as a cornerstone of their operations. The region's advanced IT infrastructure, substantial investments in research and development, and early adoption of emerging technologies have propelled it to the forefront. The United States, in particular, houses many industry leaders and innovative startups, fostering a culture of technological innovation and entrepreneurship that has fueled the growth of this market segment.

Recent Developments

In February 2023, a groundbreaking partnership has emerged between Bright Data, a global frontrunner in web data platforms, and Snowflake Data Cloud. This alliance ushers in a transformative era where public data sets will be seamlessly delivered to clients with unprecedented speed and efficiency. Through this collaboration, Snowflake customers can access and consume data sets from Bright Data without the need for cumbersome data copying or transfer processes. This innovative integration streamlines the data acquisition journey, enabling clients to directly purchase and utilize public data sets from Bright Data, all within the ecosystem of Snowflake Data Cloud.
In January 2023, a significant development unfolded in the tech landscape as DataStax, a prominent player in real-time AI, announced its acquisition of Kaskada, a dynamic machine learning company. This strategic move showcases DataStax's commitment to bolstering its capabilities in the realm of AI-driven solutions. With this acquisition, DataStax harnesses Kaskada's expertise in machine learning, thereby enhancing its ability to cater to the ever-evolving needs of modern businesses.
In November 2022, a significant move shook the tech and consulting landscape as Accenture, a global leader in professional services, announced its acquisition of ALBERT Inc., a distinguished Japanese data science company. This strategic acquisition underscores Accenture's commitment to enhancing its data and AI capabilities, equipping the company with a substantial team of skilled data scientists. The integration of ALBERT's expertise into Accenture's arsenal not only fortifies its capabilities but also positions the company to provide unparalleled support to clients as they navigate the transformative journey of business reinvention in the next decade.

Key Market Players

· 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

By Service Type	By Organization Size	By Business Function	By End User	By Region
Data Modelling Data Integration Analytics Data Quality	Small & Medium-sized Enterprises Large Enterprises	Finance Marketing & Sales HR Others	Media & Telecom BFSI Manufacturing Government Others	North America Europe South America Middle East & Africa Asia Pacific

Report Scope:

In this report, the global big data and data engineering services market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Global Big Data and Data Engineering Services Market, By Service Type:

o Data Modelling

o Data Integration

o Analytics

o Data Quality

Global Big Data and Data Engineering Services Market, By Organization Size:

o Small & Medium-sized Enterprises

o Large Enterprises

Global Big Data and Data Engineering Services Market, By Business Function:

o Finance

o Marketing & Sales

o HR

o Others

Global Big Data and Data Engineering Services Market, By End User:

o Media & Telecom

o BFSI

o Manufacturing

o Government

o Others

Global Big Data and Data Engineering Services Market, By Region:

o North America

o Europe

o South America

o Middle East & Africa

o Asia Pacific

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Big Data and Data Engineering Services Market.

Available Customizations:

Global Big Data and Data Engineering Services market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

Detailed analysis and profiling of additional market players (up to five).

Global Big Data and Data Engineering Services Market is an upcoming report to be released soon. If you wish an early delivery of this report or want to confirm the date of release, please contact us at [email protected]

Table of content

1. Service Overview

1.1. Market Definition

1.2. Scope of the Market

1.2.1. Markets Covered

1.2.2. Years Considered for Study

1.2.3. Key Market Segmentations

2. Research Methodology

2.1. Objective of the Study

2.2. Baseline Methodology

2.3. Key Industry Partners

2.4. Major Association and Secondary Sources

2.5. Forecasting Methodology

2.6. Data Triangulation & Validation

2.7. Assumptions and Limitations

3. Executive Summary

4. Impact of COVID-19 on Global Big Data and Data Engineering Services Market

5. Voice of Customer

6. Global Big Data and Data Engineering Services Market Overview

7. Global Big Data and Data Engineering Services Market Outlook

7.1. Market Size & Forecast

7.1.1. By Value

7.2. Market Share & Forecast

7.2.1. By Component (Data Modelling, Data Integration, Analytics, Data Quality)

7.2.2. By Organization Size (Small & Medium-Sized Enterprises, Large Enterprises)

7.2.3. By Business Function (Finance, Marketing & Sales, HR, Others)

7.2.4. By End User (Media & Telecom, BFSI, Manufacturing, Government, Others)

7.2.5. By Region

7.3. By Company (2022)

7.4. Market Map

8. North America Big Data and Data Engineering Services Market Outlook

8.1. Market Size & Forecast

8.1.1. By Value

8.2. Market Share & Forecast

8.2.1. By Component

8.2.2. By Organization Size

8.2.3. By Business Function

8.2.4. By End User

8.3. North America: Country Analysis

8.3.1. United States Big Data and Data Engineering Services Market Outlook

8.3.1.1. Market Size & Forecast

8.3.1.1.1. By Value

8.3.1.2. Market Share & Forecast

8.3.1.2.1. By Component

8.3.1.2.2. By Organization Size

8.3.1.2.3. By Business Function

8.3.1.2.4. By End User

8.3.2. Canada Big Data and Data Engineering Services Market Outlook

8.3.2.1. Market Size & Forecast

8.3.2.1.1. By Value

8.3.2.2. Market Share & Forecast

8.3.2.2.1. By Component

8.3.2.2.2. By Organization Size

8.3.2.2.3. By Business Function

8.3.2.2.4. By End User

8.3.3. Mexico Big Data and Data Engineering Services Market Outlook

8.3.3.1. Market Size & Forecast

8.3.3.1.1. By Value

8.3.3.2. Market Share & Forecast

8.3.3.2.1. By Component

8.3.3.2.2. By Organization Size

8.3.3.2.3. By Business Function

8.3.3.2.4. By End User

9. Europe Big Data and Data Engineering Services Market Outlook

9.1. Market Size & Forecast

9.1.1. By Value

9.2. Market Share & Forecast

9.2.1. By Component

9.2.2. By Organization Size

9.2.3. By Business Function

9.2.4. By End User

9.3. Europe: Country Analysis

9.3.1. Germany Big Data and Data Engineering Services Market Outlook

9.3.1.1. Market Size & Forecast

9.3.1.1.1. By Value

9.3.1.2. Market Share & Forecast

9.3.1.2.1. By Component

9.3.1.2.2. By Organization Size

9.3.1.2.3. By Business Function

9.3.1.2.4. By End User

9.3.2. United Kingdom Big Data and Data Engineering Services Market Outlook

9.3.2.1. Market Size & Forecast

9.3.2.1.1. By Value

9.3.2.2. Market Share & Forecast

9.3.2.2.1. By Component

9.3.2.2.2. By Organization Size

9.3.2.2.3. By Business Function

9.3.2.2.4. By End User

9.3.3. France Big Data and Data Engineering Services Market Outlook

9.3.3.1. Market Size & Forecast

9.3.3.1.1. By Value

9.3.3.2. Market Share & Forecast

9.3.3.2.1. By Component

9.3.3.2.2. By Organization Size

9.3.3.2.3. By Business Function

9.3.3.2.4. By End User

9.3.4. Spain Big Data and Data Engineering Services Market Outlook

9.3.4.1. Market Size & Forecast

9.3.4.1.1. By Value

9.3.4.2. Market Share & Forecast

9.3.4.2.1. By Component

9.3.4.2.2. By Organization Size

9.3.4.2.3. By Business Function

9.3.4.2.4. By End User

9.3.5. Italy Big Data and Data Engineering Services Market Outlook

9.3.5.1. Market Size & Forecast

9.3.5.1.1. By Value

9.3.5.2. Market Share & Forecast

9.3.5.2.1. By Component

9.3.5.2.2. By Organization Size

9.3.5.2.3. By Business Function

9.3.5.2.4. By End User

10. South America Big Data and Data Engineering Services Market Outlook

10.1. Market Size & Forecast

10.1.1. By Value

10.2. Market Share & Forecast

10.2.1. By Component

10.2.2. By Organization Size

10.2.3. By Business Function

10.2.4. By End User

10.3. South America: Country Analysis

10.3.1. Brazil Big Data and Data Engineering Services Market Outlook

10.3.1.1. Market Size & Forecast

10.3.1.1.1. By Value

10.3.1.2. Market Share & Forecast

10.3.1.2.1. By Component

10.3.1.2.2. By Organization Size

10.3.1.2.3. By Business Function

10.3.1.2.4. By End User

10.3.2. Argentina Big Data and Data Engineering Services Market Outlook

10.3.2.1. Market Size & Forecast

10.3.2.1.1. By Value

10.3.2.2. Market Share & Forecast

10.3.2.2.1. By Component

10.3.2.2.2. By Organization Size

10.3.2.2.3. By Business Function

10.3.2.2.4. By End User

10.3.3. Colombia Big Data and Data Engineering Services Market Outlook

10.3.3.1. Market Size & Forecast

10.3.3.1.1. By Value

10.3.3.2. Market Share & Forecast

10.3.3.2.1. By Component

10.3.3.2.2. By Organization Size

10.3.3.2.3. By Business Function

10.3.3.2.4. By End User

11. Middle East & Africa Big Data and Data Engineering Services Market Outlook

11.1. Market Size & Forecast

11.1.1. By Value

11.2. Market Share & Forecast

11.2.1. By Component

11.2.2. By Organization Size

11.2.3. By Business Function

11.2.4. By End User

11.3. Middle East & America: Country Analysis

11.3.1. Israel Big Data and Data Engineering Services Market Outlook

11.3.1.1. Market Size & Forecast

11.3.1.1.1. By Value

11.3.1.2. Market Share & Forecast

11.3.1.2.1. By Component

11.3.1.2.2. By Organization Size

11.3.1.2.3. By Business Function

11.3.1.2.4. By End User

11.3.2. Qatar Big Data and Data Engineering Services Market Outlook

11.3.2.1. Market Size & Forecast

11.3.2.1.1. By Value

11.3.2.2. Market Share & Forecast

11.3.2.2.1. By Component

11.3.2.2.2. By Organization Size

11.3.2.2.3. By Business Function

11.3.2.2.4. By End User

11.3.3. UAE Big Data and Data Engineering Services Market Outlook

11.3.3.1. Market Size & Forecast

11.3.3.1.1. By Value

11.3.3.2. Market Share & Forecast

11.3.3.2.1. By Component

11.3.3.2.2. By Organization Size

11.3.3.2.3. By Business Function

11.3.3.2.4. By End User

11.3.4. Saudi Arabia Big Data and Data Engineering Services Market Outlook

11.3.4.1. Market Size & Forecast

11.3.4.1.1. By Value

11.3.4.2. Market Share & Forecast

11.3.4.2.1. By Component

11.3.4.2.2. By Organization Size

11.3.4.2.3. By Business Function

11.3.4.2.4. By End User

12. Asia Pacific Big Data and Data Engineering Services Market Outlook

12.1. Market Size & Forecast

12.1.1. By Value

12.2. Market Share & Forecast

12.2.1. By Component

12.2.2. By Organization Size

12.2.3. By Business Function

12.2.4. By End User

12.3. Asia Pacific: Country Analysis

12.3.1. China Big Data and Data Engineering Services Market Outlook

12.3.1.1. Market Size & Forecast

12.3.1.1.1. By Value

12.3.1.2. Market Share & Forecast

12.3.1.2.1. By Component

12.3.1.2.2. By Organization Size

12.3.1.2.3. By Business Function

12.3.1.2.4. By End User

12.3.2. Japan Big Data and Data Engineering Services Market Outlook

12.3.2.1. Market Size & Forecast

12.3.2.1.1. By Value

12.3.2.2. Market Share & Forecast

12.3.2.2.1. By Component

12.3.2.2.2. By Organization Size

12.3.2.2.3. By Business Function

12.3.2.2.4. By End User

12.3.3. South Korea Big Data and Data Engineering Services Market Outlook

12.3.3.1. Market Size & Forecast

12.3.3.1.1. By Value

12.3.3.2. Market Share & Forecast

12.3.3.2.1. By Component

12.3.3.2.2. By Organization Size

12.3.3.2.3. By Business Function

12.3.3.2.4. By End User

12.3.4. India Big Data and Data Engineering Services Market Outlook

12.3.4.1. Market Size & Forecast

12.3.4.1.1. By Value

12.3.4.2. Market Share & Forecast

12.3.4.2.1. By Component

12.3.4.2.2. By Organization Size

12.3.4.2.3. By Business Function

12.3.4.2.4. By End User

12.3.5. Australia Big Data and Data Engineering Services Market Outlook

12.3.5.1. Market Size & Forecast

12.3.5.1.1. By Value

12.3.5.2. Market Share & Forecast

12.3.5.2.1. By Component

12.3.5.2.2. By Organization Size

12.3.5.2.3. By Business Function

12.3.5.2.4. By End User

13. Market Dynamics

13.1. Drivers

13.2. Challenges

14. Market Trends and Developments

15. Company Profiles

15.1. Accenture PLC

15.1.1. Business Overview

15.1.2. Key Financials & Revenue

15.1.3. Key Contact Person

15.1.4. Headquarters Address

15.1.5. Key Product/Service Offered

15.2. Genpact Inc.

15.2.1. Business Overview

15.2.2. Key Financials & Revenue

15.2.3. Key Contact Person

15.2.4. Headquarters Address

15.2.5. Key Product/Service Offered

15.3. Cognizant Technology Solutions Corporation

15.3.1. Business Overview

15.3.2. Key Financials & Revenue

15.3.3. Key Contact Person

15.3.4. Headquarters Address

15.3.5. Key Product/Service Offered

15.4. Infosys Limited

15.4.1. Business Overview

15.4.2. Key Financials & Revenue

15.4.3. Key Contact Person

15.4.4. Headquarters Address

15.4.5. Key Product/Service Offered

15.5. Capgemini SE

15.5.1. Business Overview

15.5.2. Key Financials & Revenue

15.5.3. Key Contact Person

15.5.4. Headquarters Address

15.5.5. Key Product/Service Offered

15.6. NTT Data Inc.

15.6.1. Business Overview

15.6.2. Key Financials & Revenue

15.6.3. Key Contact Person

15.6.4. Headquarters Address

15.6.5. Key Product/Service Offered

15.7. Mphasis Limited

15.7.1. Business Overview

15.7.2. Key Financials & Revenue

15.7.3. Key Contact Person

15.7.4. Headquarters Address

15.7.5. Key Product/Service Offered

15.8. L&T Technology Services

15.8.1. Business Overview

15.8.2. Key Financials & Revenue

15.8.3. Key Contact Person

15.8.4. Headquarters Address

15.8.5. Key Product/Service Offered

15.9. Hexaware Technologies Inc.

15.9.1. Business Overview

15.9.2. Key Financials & Revenue

15.9.3. Key Contact Person

15.9.4. Headquarters Address

15.9.5. Key Product/Service Offered

15.10. KPMG LLP

15.10.1. Business Overview

15.10.2. Key Financials & Revenue

15.10.3. Key Contact Person

15.10.4. Headquarters Address

15.10.5. Key Product/Service Offered

16. Strategic Recommendations

17. About Us & Disclaimer

Figures and Tables

Frequently asked questions

What was the market size of the Global Big Data and Data Engineering Services Market in 2022?

The market size of the global big data and data engineering services market was estimated to be USD 70.46 Billion in 2022.

Which was the dominant segment by end user in the Global Big Data and Data Engineering Services Market in 2022?

In 2022, BFSI was the dominant segment by end user in the global big data and data engineering services market. This sector's commanding presence underscores its strategic recognition of the transformative potential of big data and data engineering. As financial institutions strive to remain competitive in an increasingly data-driven landscape, the BFSI segment harnesses these services to extract valuable insights, enhance risk management, personalize customer experiences, and optimize operational efficiency.

Which are the key players in the Global Big Data and Data Engineering Services Market?

Key players in the market are 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, and others.

What are the major drivers for the Global Big Data and Data Engineering Services Market?

Rise of cloud computing and exponential growth of data are the major drivers for the global big data and data engineering services market.

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Press Release

Big Data and Data Engineering Services Market to be Led by Data-Driven Decision-Making across the Globe Through 2028

Nov, 2023

The Exponential Growth of Data is driving the Implementation of Big Data and Data Engineering Services market across the Globe.

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