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Data Wrangling Market to Expand by USD 1.49 Billion from 2024-2028, Benefits of Data Wrangling Solutions Drive Revenue, Report on AI-Redefined Market Landscape – Technavio

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NEW YORK, Nov. 7, 2024 /PRNewswire/ — Report with market evolution powered by AI – The global data wrangling market  size is estimated to grow by USD 1.49 billion from 2024-2028, according to Technavio. The market is estimated to grow at a CAGR of  14.8%  during the forecast period. Numerous benefits provided by data wrangling solutions is driving market growth, with a trend towards rising need of technology in healthcare sector. However, lack of awareness of data wrangling tools among smes  poses a challenge.Key market players include Altair Engineering Inc., Alteryx Inc., Dataiku Inc., DataRobot Inc., Dell Technologies Inc., eXalt Solutions Inc., Hitachi Ltd., Ideata Analytics, Impetus Technologies Inc., Innovative Routines International (IRI) Inc., International Business Machines Corp., Medallia Inc., Microsoft Corp., Oracle Corp., Rapid Insight Inc., SAS Institute Inc., Teradata Corp., TIBCO Software Inc., Wipro Ltd., and Zoho Corp. Pvt. Ltd..

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Forecast period

2024-2028

Base Year

2023

Historic Data

2018 – 2022

Segment Covered

Sector (BFSI, Government and public sector, Healthcare, and Others) and Geography (North America, Europe, APAC, Middle East and Africa, and South America)

Region Covered

North America, Europe, APAC, Middle East and Africa, and South America

Key companies profiled

Altair Engineering Inc., Alteryx Inc., Dataiku Inc., DataRobot Inc., Dell Technologies Inc., eXalt Solutions Inc., Hitachi Ltd., Ideata Analytics, Impetus Technologies Inc., Innovative Routines International (IRI) Inc., International Business Machines Corp., Medallia Inc., Microsoft Corp., Oracle Corp., Rapid Insight Inc., SAS Institute Inc., Teradata Corp., TIBCO Software Inc., Wipro Ltd., and Zoho Corp. Pvt. Ltd.

Key Market Trends Fueling Growth

The healthcare sector encounters numerous challenges, such as managing disease outbreaks and enhancing operational efficiency. With an influx of daily data, including patient details, medical history, treatment records, and payment information, healthcare organizations require solutions to prepare, clean, and format this data for insightful analysis. Data wrangling plays a vital role in this process by transforming raw data into structured formats. During the COVID-19 pandemic, data wrangling tools became essential for cleaning and organizing patient data, enabling quick decision-making. As healthcare adopts advanced technologies like AI and machine learning, the demand for data wrangling solutions increases, as these technologies rely on clean, structured data for accurate predictions and insights. The growing focus on personalized medicine and patient-centric care necessitates integrating diverse data sources, further emphasizing the importance of data wrangling for managing complexity and improving decision-making, patient outcomes, and healthcare system efficiency. As healthcare data volume expands, data wrangling’s role in driving innovation and quality care will continue to grow, positively impacting the market’s growth during the forecast period. 

In today’s digital world, businesses are generating and collecting massive amounts of data. This data needs to be processed and transformed into valuable insights to drive business growth. Trends like digital transformation, big data analytics, and e-commerce are leading the charge in data usage. Data integration, structuring, and transformation are key areas of focus for professional services and consulting firms. Data security is paramount, with encryption, access controls, and data protection laws ensuring data privacy. Technology hubs are emerging as centers for innovation in data munging, information mapping, and enterprise mobility. Industries like healthcare, telecommunications, financial services, and insurance are leveraging cloud solutions for data analysis. Data quality, edge computing, and financial services are also seeing significant investment. Anomalies in data require attention, with cloud-based analytics and data lineage tools helping to identify and address them. Metadata management, data cataloging, and data cleaning are essential for data unification and self-service data preparation. Big data, digitalization, finance, IoT devices, smart cities, and life sciences are all driving the need for data analysis tools. Data loss prevention is a critical concern, with firms investing in solutions to mitigate risk. Overall, the data wrangling market is thriving, with innovation and growth expected to continue. 

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Market Challenges

•         Data wrangling refers to the process of extracting valuable insights from raw data using advanced technologies like machine learning and big data analytics. Small and medium-sized enterprises (SMEs) primarily use conventional Extract, Transform, Load (ETL) tools due to their user-friendly interface and affordability. However, these tools lack the necessary functionality for SMEs to fully adopt data wrangling technology, limiting its growth potential. Moreover, in developing countries such as China and India, where there is a high concentration of businesses, the lack of awareness about data wrangling techniques among SMEs will hinder market expansion during the forecast period.

•         In today’s business world, managing data effectively is crucial for success. However, data wrangling presents several challenges for organizations. These include information mapping to connect data from various sources, enterprise mobility to access data on-the-go, ensuring data quality, and implementing edge computing for real-time analysis. Industries like financial services, insurance, and life sciences face unique data challenges. Cloud solutions offer scalability and flexibility, but data loss and security are major concerns. Data analytics tools help make sense of big data, but data lineage, metadata management, and data cataloging are essential for maintaining data accuracy. Self-service data preparation is important for enabling business users, while AI and machine learning require data cleaning and unification. Data management, data preparation, and real-time analysis are key for IT and telecom, while data governance is crucial for large enterprises and SMEs alike. IoT devices and smart cities generate vast amounts of data, requiring multi-cloud strategies and hybrid cloud solutions. Data analytics is the end goal, but data loss, data security, and data privacy are ongoing challenges that must be addressed.

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Segment Overview 

This data wrangling market report extensively covers market segmentation by

Sector 1.1 BFSI1.2 Government and public sector1.3 Healthcare1.4 OthersGeography 2.1 North America2.2 Europe2.3 APAC2.4 Middle East and Africa2.5 South America

1.1 BFSI-  The BFSI sector’s reliance on data wrangling has grown significantly due to the digitization of services and the resulting generation of large volumes of data. Data wranglers optimize operational processes and provide insights to agents for effective online customer interaction. They reduce data preparation time by more than 15 times, enabling a 360-degree client view. With massive data generation, proper management is crucial to prevent unwanted events like data breaches. The Royal Bank of Scotland, serving over 30 million customers globally, uses data wranglers to extract insights from unstructured data, particularly web chats. These factors are driving the demand for data wrangling solutions in the BFSI sector, ensuring secure and efficient data management.

Download complimentary Sample Report to gain insights into AI’s impact on market dynamics, emerging trends, and future opportunities- including forecast (2024-2028) and historic data (2018 – 2022) 

Research Analysis

The Data Wrangling Market is experiencing significant growth due to the increasing volume, variety, and velocity of data being generated across industries. Data loss and theft continue to be major concerns, driving the need for data management and security solutions. Artificial intelligence and machine learning are revolutionizing data analysis by automating data preparation and enabling real-time analysis. Cloud-based solutions and multi-cloud strategies are becoming increasingly popular for data management, offering flexibility and scalability. Data munging, information mapping, and data cleaning are essential data preparation tasks for ensuring data quality. Finance, insurance, and IoT devices are generating massive amounts of data, making data unification and self-service data preparation crucial. Big data and real-time analysis are transforming industries like finance and smart cities, requiring edge computing to process data at the source. Data analytics is at the heart of these trends, enabling businesses to gain valuable insights and make informed decisions.

Market Research Overview

The Data Wrangling Market is experiencing significant growth due to the increasing demand for Artificial Intelligence (AI) and Machine Learning (ML) applications in Data Analytics. Businesses are focusing on Data Management and Preparation to derive valuable insights from their data. Real-time analysis is becoming essential for Large Enterprises and SMEs in IT and Telecom, Finance, Healthcare, Telecommunications, E-commerce, and other sectors. On-premises and Cloud-based solutions are popular for Data Management, with Multi-cloud strategies and Hybrid cloud gaining traction. Data Security and Governance are top priorities, with Digital Transformation driving the adoption of Big Data Analytics, Data Integration, and Data Transformation. Data Structuring, Professional Services, and Consulting are crucial for Data Encryption, Access Controls, and Data Protection Laws. Technology hubs are investing in Data Analytics Tools and Edge Computing to support Digitalization and IoT devices. Data Quality, Anomalies, and Cloud-based Analytics are key areas of focus, along with Data Lineage, Metadata Management, Data Cataloging, Data Cleaning, and Data Unification. Self-service Data Preparation and Big Data are transforming industries such as Life Sciences, Finance, and Insurance. Data Loss prevention is a growing concern, with a need for advanced Data Analytics and AI-driven solutions. The market is expected to continue growing, driven by the increasing importance of Data in the Digital Age.

Table of Contents:

1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation

SectorBFSIGovernment And Public SectorHealthcareOthersGeographyNorth AmericaEuropeAPACMiddle East And AfricaSouth America

7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Trends
10 Company Landscape
11 Company Analysis
12 Appendix

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focuses on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.

With over 500 specialized analysts, Technavio’s report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio’s comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contacts

Technavio Research
Jesse Maida
Media & Marketing Executive
US: +1 844 364 1100
UK: +44 203 893 3200
Email: media@technavio.com
Website: www.technavio.com/

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SOURCE Technavio

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CM Global Services Announces Project Santos, a Planned 50-Megawatt AI Data Center Campus in ERCOT South

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21 minutes ago

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July 23, 2026

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CM Global Services targets a site and engages with strategic partners to become operational in the AI data center space.

DENVER, July 23, 2026 /PRNewswire/ — CM Global Services, LLC (CMGS) today announced Project Santos, its plan to develop a 50-megawatt AI data center campus for a site in the ERCOT South grid zone. CMGS is a long-standing strategic partner of Compass Mining, Inc. and is a global provider of logistics, hardware sales, and infrastructure services, with a growing focus on AI infrastructure and building site development. The announcement was made by Shanon Squires, Chief Mining Officer of Compass Mining, during a panel on bitcoin mining companies diversifying into AI infrastructure at the Energy Investors Forum.

CMGS intends to deliver Project Santos in two phases. The first phase, a 7-megawatt, 5 MW of IT Load Tier III facility purpose-built for AI inference workloads, is targeted for completion by the end of the first quarter of 2027. A subsequent 43-megawatt expansion, bringing the site to its fully planned 50-megawatt capacity

“This is a disciplined next step for CM Global Services, drawing upon its expertise in standing up infrastructure, while Compass Mining simultaneously continues to be the gold standard in Bitcoin mining-related services,” said Shanon Squires. “Bitcoin mining remains the core of Compass Mining. CMGS’ Project Santos reflects the power infrastructure and site development discipline CMGS built over years, and we’re pursuing this initiative on our own terms.”

“This is a new step forward for CMGS, as we continue building for the future,” said Vishnu Mackenchery, Managing Director at CMGS. “Project Santos marks our entry into AI infrastructure and inference, and we’re charting our own path, moving fast to get there.”

GPU-as-a-Service for Enterprise and Neocloud Customers

Project Santos is being developed as a GPU-as-a-Service (GPUaaS) platform. Rather than requiring customers to bring their own hardware, CMGS is securing NVIDIA GB300 Blackwell GPU capacity to offer directly to off-takers as dedicated, single-tenant or multi-tenant compute. The company’s ideal customer profile is AI enterprise organizations seeking dedicated capacity, and CMGS is also in active discussions with neocloud providers.

Project Status

Site: located in the ERCOT South grid zoneCompute: CMGS is securing NVIDIA GB300 Blackwell GPU capacity to offer as GPU-as-a-Service to off-takersTotal planned capacity: 50 megawatts, 35 MW of IT to be delivered in two phasesPhase 1: 7 megawatts, 5 MW of IT load Tier III, targeted for completion by end of Q1Phase 2: adding a 43-megawatt expansion, 30 MW of IT load with utility-supported expansionCustomer profile: AI enterprise companies are the ideal customer; CMGS is also in active discussions with neocloud providers

About CMGS

CM Global Services (CMGS) is a global provider of logistics, hardware sales, and infrastructure services, with a growing focus on AI infrastructure and building site development. CMGS supports clients with end-to-end logistics solutions, hardware procurement, and site-level execution for next-generation compute infrastructure.

About CMGS and Compass Mining Partnership

Compass Mining serves as a strategic partner and advisor to CM Global Services (CMGS), supporting its growth across global logistics, hardware sales, and infrastructure services. As CMGS expands its focus into AI infrastructure and site development, Compass Mining’s guidance helps shape its strategic direction and execution. Together, the two organizations continue to collaborate on delivering end-to-end solutions for clients building next-generation compute infrastructure.

Disclaimer

This communication contains forward-looking statements relating to a potential closing of a transaction. There can be no assurance that the proposed transaction will be completed on the terms described, or at all. Forward-looking statements are subject to significant business, economic, and competitive uncertainties, many of which are beyond our control. This communication is for informational purposes only and does not constitute an offer to sell, or a solicitation of an offer to buy, any securities of the company. Furthermore, investing in or engaging with our company involves substantial risk, and past performance or previous communications are not indicative of future results. There is no guarantee, assurance, or warranty that any specific financial outcome, return on investment, or overall results will be achieved. Actual results may differ materially and adversely from those expressed, projected, or implied in any forward-looking statements. Investors and stakeholders should not rely solely on preliminary press releases regarding potential transactions or projected financial metrics when making investment decisions. We undertake no obligation to publicly update or revise any forward-looking statements, whether as a result of new information, future events, or otherwise, except as required by applicable securities laws. Prospective investors are strongly encouraged to conduct their own independent due diligence and consult with a qualified, independent financial or legal advisor prior to making any investment.

Contact
All inquiries can be made to: Santos@CMGlobalServices.io 

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Advantech Unveils Next-Gen AI Infrastructure Solutions Powered by AMD EPYC™ 9006 Series Processors

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July 23, 2026

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TAIPEI, July 23, 2026 /PRNewswire/ — Advantech, a global leader in industrial edge computing and edge AI solutions, today announced its next-generation server and network platforms powered by the latest AMD EPYC™ 9006 Series processors. Designed to accelerate AI infrastructure from the data center to the intelligent edge, Advantech’s 6th Gen AMD EPYC-powered servers deliver the performance, scalability, and reliability organizations need for AI, HPC, storage, networking, and mission-critical industrial workloads.

At AMD Advancing AI 2026, Advantech will showcase its latest 2U 4-node edge server and EATX server board, demonstrating how its workload-ready server solutions enable customers to build scalable, high-performance AI and edge computing infrastructure with greater deployment confidence.

Continuing Performance Leadership with AMD EPYC 9006 Series Processors

6th Gen AMD EPYC server CPUs bring continued leadership in performance, efficiency, memory bandwidth, and next-generation I/O. Featuring up to 128 cores and 256 threads, advanced 2nm process technology, “Zen 6” and “Zen 6c” architecture, up to 20% average generational performance uplift, and up to 20% performance-per-watt improvement, AMD EPYC 9006 Series processors are designed to support more virtual machines, higher throughput, and better system efficiency. With up to 128 PCIe Gen6 lanes per CPU, CXL™ 3.1 memory expansion, and support for DDR5 8000NHz and MRDIMM 12800MHz for high memory bandwidth, Advantech edge server solutions deliver balanced compute, memory, and I/O performance for next-generation AI, telco, edge, and storage infrastructure.

Key Features Include:

Up to 128 cores / 256 threads with “Zen 6” and “Zen 6c” architectureAdvanced 2nm process technology for improved performance and efficiencyUp to 20% average generational performance uplift and 20% performance-per-watt improvementDDR5-8000 and MRDIMM 12.8G support for higher memory bandwidth and capacityPCIe® Gen6 scalability: up to 128 lanes for 1 CPU and up to 196 lanes for 2 CPUsCXL™ 3.1 support for optimized memory expansion

Comprehensive Edge Server Solutions from Edge to Cloud

Advantech’s edge server portfolio powered by AMD EPYC™ 9006 Series processors delivers a complete board-to-system lineup for AI infrastructure, data centers, cloud, HCI, HPC, edge computing, industrial applications, and high-performance networking. The first-wave portfolio includes:
(1) The SKY-642E5, 4U MGX GPU server, for large-scale AI acceleration
(2) The SKY-722E5, 2U DC-MHS server with DC-SCM support, for modular data center and edge AI deployments
(3) The SKY-712E5, 1U DC-MHS server, supporting HHHL and FH-3/4L expansion cards for high-density enterprise edge and cloud workloads
(4) The SKY-822E5, 2U short-depth DC-SCM modular server, supporting 2–3 dual-slot GPU cards for space-constrained edge data centers
(5) The SKY-924E5F, 2U 4-node front-access server, for distributed edge computing,
(6) The ASMB-982 & ASMB-832 server boards for flexible, high-expandability system designs.

These new platforms also support PCIe Gen6 scalability, GPU-optimized architecture, advanced DDR5/MRDIMM memory, and AFA-ready high-density E1.S/E3.S NVMe SSD storage to meet low-latency data access, high-throughput storage performance, and scalable infrastructure for data-intensive AI and edge-cloud workloads.

Expanding the portfolio further, Advantech also introduces the FWA-6084, the 2U network appliance and is designed for demanding network security and edge AI workloads. It features DDR5/MRDIMM memory capability, eight Gen6 network module cards, and one PCIe Gen5 x16 slot for GPU or add-on card expansion. It is well positioned to support line-speed multiple 200G network workloads without compromise.

Together with Advantech’s unique service advantages—including 3-5-10 service guarantee, strict revision control, stable component supply, worldwide local support, and custom-ready integration—the new portfolio supports customers reduce deployment risk, secure long-term product roadmaps, and accelerate workload-ready AI and edge-cloud infrastructure from concept to deployment.

Explore more product information, please contact us or visit the Advantech x AMD website.

About Advantech

Advantech is a global leader in IoT intelligent systems and embedded platforms, driven by its vision of “Enabling an Intelligent Planet.” To address the growth of edge computing and AI, Advantech focuses on five key markets: Edge Intelligence Systems, Manufacturing, Energy and Utilities, iHealthcare, and iCity Services & iRetail. By integrating edge computing hardware, WISE-IoT software, sector-specific AI solutions, and domain expertise, Advantech creates an orchestration model that connects industrial ecosystems and accelerates industrial intelligence with partners and customers.(www.advantech.com) 

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SOURCE Advantech Co., Ltd.

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MulticoreWare and AMD Collaborate to Advance Physical AI and Autonomous Robotics on AMD Platforms

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21 minutes ago

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July 23, 2026

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Companies Demonstrated Real-Time Multimodal AI and Vision-Language-Action Workflows on AMD Ryzen™ AI Platforms at AMD Advancing AI 2026

SAN JOSE, Calif., July 23, 2026 /PRNewswire/ — MulticoreWare, Inc., a global technology company specializing in AI software solutions, physical AI, accelerated computing, and engineering services, today announced its ongoing collaboration with AMD to advance autonomous robotics and edge intelligence on AMD platforms.

As part of this collaboration, MulticoreWare joined AMD at AMD Advancing AI 2026 to present ‘Enabling Physical AI on AMD’, demonstrating how advanced vision, language, and action (VLA) models can drive real-time robotic intelligence on AMD Ryzen™ AI Embedded platforms.

As AI increasingly moves from the cloud into robots, autonomous systems, and intelligent edge devices, organizations need efficient ways to run sophisticated AI models closer to where decisions need to be made. Together, AMD and MulticoreWare are helping developers bring advanced perception, reasoning, and action capabilities to AMD-powered systems.

At AMD Advancing AI 2026, AMD and MulticoreWare demonstrated how multimodal VLA models run on AMD Ryzen™ AI Embedded integrated GPUs using AMD ROCm™, enabling robots to perceive, reason, and act in real time. The session showcased practical guidance for AI developers, robotics engineers, and innovators building next-generation intelligent machines on AMD Embedded platforms.

“Physical AI is reshaping how machines perceive, decide and act in the real world,” said Sumit Shah, Head of Product Management and Marketing, Adaptive and Embedded Computing Group, AMD. “AMD Ryzen™ AI Embedded X100 Series processors deliver a scalable, open x86 Embedded platform that unifies AI, real-time control and industrial reliability to enable the generation of autonomous systems without locking developers into a single compute architecture or software stack.”

“A Physical AI system depends on a tightly integrated loop between perception and actuation. It must operate in real time, on real hardware, and in environments that are inherently unpredictable,” said Vish Rajalingam, VP & GM, Mobility and Transportation BU at MulticoreWare. “That makes it a hardware-software co-design challenge, not simply an AI inference problem. Building on the open-source AMD Robotics Software Suite, we work closely with OEMs to optimize the entire stack so that latency, reliability and accuracy targets are consistently achieved in production environments. That’s the integration MulticoreWare and AMD deliver together to move intelligent robotic systems from prototype to deployment.”

This session builds on more than 15 years of collaboration, with MulticoreWare delivering software optimization, AI, and engineering expertise across the AMD ecosystem, including Ryzen™ AI, Ryzen™, AMD EPYC™, AMD Instinct™, AMD Radeon™, and adaptive computing technologies.

About MulticoreWare

MulticoreWare, Inc. is a global technology company delivering AI software solutions and engineering services that accelerate innovation in Physical AI, Agentic AI, Robotics, Edge Intelligence, and Accelerated Computing. With expertise in multimodal AI, Vision-Language-Action (VLA) models, sensor perception and fusion, AI optimization, embedded systems, and high-performance software, MulticoreWare helps customers transform advanced AI technologies into production-ready solutions. Its innovations power applications across automotive, robotics, industrial automation, smart cities, healthcare, defense, and intelligent edge devices, while its video codec technologies enable next-generation video experiences worldwide.
www.multicorewareinc.com

AMD, the AMD Arrow logo, EPYC, Instinct, Radeon, Ryzen and combinations thereof are trademarks of Advanced Micro Devices, Inc.

Contact:
Suchithra Thyagarajan
VP – Corporate Marketing
marcom@multicorewareinc.com 

 

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