查看购物车
  • Traditional Chinese
  • English
  • Japanese
  • Korean
封面
市场调查报告书
商品编码
1630257

资料品质工具：市场占有率分析、产业趋势与成长预测（2025-2030）

Data Quality Tools - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3个工作天内

价格

※ 本网页内容可能与最新版本有所差异。详细情况请与我们联繫。

简介目录

资料品质工具市场预计在预测期内复合年增长率为 17.5%

数据品质工具-市场-IMG1

主要亮点

  • 根据《哈佛商业评论》(HBR) 报道，使用有缺陷的资料完成一个工作单元的成本高出 10 倍。
  • 资料品质工具通常涉及四个主要部分：资料清理、资料整合、主资料管理和元资料管理。由于资料品质是大型企业的主要关注点，因此软体公司正在提案越来越多的工具来解决此类问题。这些工具的范围正在从特定用例（例如重复资料删除、地址规范化）转向更全局的观点，整合资料品质的所有部分（例如分析、规则发现）。
  • 行动技术的最新进展使用户可以自动在线记录资料，并且资料量迅速增加。此外，云端运算基础设施的能力和规模不断加速，几乎超出了我们利用其提供的机会的能力。
  • 此外，製造公司处理多个资料流，需要对其进行分析以优化业务资源。这些行业通常需要处理常规、结构化工厂资料、模拟资料以及企业资源规划 (ERP) 系统和各种流程自动化和控制系统等应用程式产生的资讯。保持资料品质对于优化製造供应链至关重要。例如，积层製造(AM) 需要资料管理工具来确保品质、可重复性、可追溯性和可靠性，特别是在严格监管的航空和医疗产业。
  • 在 COVID-19 大流行期间，许多公司都担心在这种不确定的大流行期间确保资料品质和存取。对帮助企业分析资料的各种解决方案的需求正在获得巨大的吸引力，并且采用趋势也在改善。世界向远端工作和云端采用的转变进一步增加了对有助于提高工作效率和效力的解决方案的需求。由于大多数员工因 COVID-19 大流行而远端工作，公司投资于流程和基础设施，以实现资料的民主化和存取。

资料品质工具市场趋势

医疗保健预计将实现显着成长

  • 医疗保健领域的资料管理是一个复杂的过程。资料管理由几个关键要素组成：资料管治、资料整合、资料充实、资料储存和资料分析。资料处理系统正在成为业务决策和个人化护理流程的关键组成部分，但糟糕的资料品质和管理正在成为阻碍业务成功的关键因素，给我所采用的这些方法带来了巨大的压力。
  • 医疗保健产业中最商业化的资料收集工具是企业资料仓储 (EDW)。 EDW 旨在将多个来源的资料聚合到一个统一的资料储存库中。资料嵌入在 EDW 中，允许用户分析先前固定的资料并从现有来源系统中获得更多投资回报。此外，医院和护理提供者正在采用巨量资料分析和人口健康管理技术，以满足新的医疗保健标准的要求以及患者日益增长的需求和期望。
  • 此外，医院和护理提供者正在实施巨量资料分析和人口健康管理技术，以满足新的医疗保健标准的要求以及不断增长的患者需求和期望。 BI 工具透过识别系统缺陷并了解遗失的资料来帮助提高品质绩效。分析电子健康记录(EHR) 和基因研究等资料的医疗商业智慧(BI) 解决方案可应用于个人化治疗。
  • COVID-19 大流行需要设计用于记录护理的系统，因为系统产生的资料用于产生服务规划所需的知识。这些资讯的实际重要性增强了高品质资料所能提供的真正价值。它汇集了许多资料点，包括生存资料、共病和住院时间，最终有助于改善患者体验和改善结果。
  • 医疗保健公司正在采用新工具并合作共用资料以改善医疗保健系统。例如，去年8月，沃尔玛宣布参与QCC，有助于提昇放射服务的资料品质。 QCC 是一项全国性计划，将付款人、提供者和自保雇主聚集在一起，以大规模提高放射护理品质。

亚太地区预计将创下最高成长率

  • 从销售额来看，亚太资料品质工具市场成长最快。这主要是由于对资料品质改进解决方案的兴趣增加以及对资料驱动的科学和战略决策技术的关注增加。随着智慧城市的发展和物联网设备的激增，预计该地区未来将经历前所未有的成长。新兴企业应对力推动该地区市场的关键因素。
  • 去年10月，中国国务院宣布计划建造“国家综合政务巨量资料系统”，到2025年将实现数百万政府资料“一地可用”。将大量资料收集到一处需要动态更新资料库和目录以不断提高资料品质。
  • 企业在管理资料和获得符合监管要求的有意义的见解方面面临重大挑战。例如，根据印度储备银行（RBI）的数据，去年 6 月印度行动银行交易额超过 171,490.7 亿印度卢比（2,102.47 亿美元）。

由于资料量如此之大，银行和金融服务业的资料品质问题风险很高。产业中的这些资料品质问题直接影响客户体验、互动、交易等。这意味着企业必须支付更多费用并遭受损失，从而产生了该领域对资料品质工具的需求。

资料品质工具产业概述

资料品质工具市场可能更具凝聚力，多家国内外公司提供先进的解决方案。由于市场上有大量供应商，激烈的竞争促使每个供应商都专注于能够扩大其对不同地区客户的影响力的细分市场。此外，各种资料品质工具提供者越来越注重向客户提供全面的解决方案集，以增加市场吸引力。

2022 年 10 月，完整的资料品质平台公司 Anomalo 宣布与 dbt Labs 合作，为 dbt 指标（新 dbt 语意层的一部分）提供资料品质。

2022 年 1 月，专门与 IBM 公司和技术企业合作的全球投资公司 Francisco Partners 宣布，Francisco Partners 已签订最终协议，从 IBM 收购医疗保健资料和分析资产。 Francisco Partners 购买多种类型的资料和产品，包括 MarketScan、Health Insights、临床开发、Micromedex、社交专案管理和影像软体。

其他好处

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

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

第四章市场洞察

  • 市场概况
  • 产业价值链分析
  • 产业吸引力－波特五力分析
    • 供应商的议价能力
    • 消费者议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争公司之间敌对关係的强度
  • 评估 COVID-19 对市场的影响

第五章市场动态

  • 市场驱动因素
    • 由于行动连线的成长，外部资料来源的使用增加
  • 市场限制因素
    • 潜在用户缺乏有关解决方案的资讯和认识

第六章 市场细分

  • 依部署类型
    • 云端基础
    • 本地
  • 按组织规模
    • 小型企业
    • 大公司
  • 按成分
    • 软体
    • 服务
  • 按行业分类
    • BFSI
    • 政府机构
    • 资讯科技/通讯
    • 零售/电子商务
    • 医疗保健
    • 其他的
  • 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
    • IBM Corporation
    • Informatica LLC
    • Oracle Corporation
    • SAP SE
    • SAS Institute Inc.
    • Talend Inc.
    • Experian PLC
    • Information Builders Inc.
    • Pitney Bowes Inc.
    • Syncsort Inc.
    • Ataccama Corporation

第八章投资分析

第9章市场的未来

简介目录
Product Code: 66505

The Data Quality Tools Market is expected to register a CAGR of 17.5% during the forecast period.

Data Quality Tools - Market - IMG1

Key Highlights

  • Furthermore, growing mobile connectivity and IoT adoption across all industries have resulted in a massive data explosion, necessitating data extraction from a variety of sources.The demand for data quality tool solutions is driven by these complex data types and formats.According to the Harvard Business Review (HBR), completing a unit of work with flawed data costs ten times more, and finding the right data quality tools has always been a challenge. One can implement a system of reliability by choosing and leveraging smart, workflow-driven, self-service data quality tools with embedded quality controls.
  • Data quality tools generally address four primary areas: data cleansing, data integration, master data management, and metadata management. As data quality is a major concern for large organizations, software companies propose increasing the number of tools that address such issues. The scope of these tools is shifting from specific applications (deduplication, address normalization, etc.) to a more global perspective, integrating all areas of data quality (profiling, rule detection, etc.).
  • Recent advances in mobile technology allowed users to automatically record data online, creating massive amounts of data that increased rapidly. Moreover, the capability and size of cloud computing infrastructures are continuing to accelerate, nearly beyond our abilities to leverage the opportunities provided.
  • Moreover, the manufacturing sector handles multiple data streams that need to be analyzed to optimize business resources. These industries typically require handling routine, structured in-factory data, analog data, and information churned out from applications, including enterprise resource planning (ERP) systems and various process automation and control systems. Maintaining data quality would be significant for optimizing the manufacturing sector's supply chain. For instance, additive manufacturing (AM) needs tools to manage data to ensure quality, repeatability, traceability, and reliability, especially in the heavily regulated aviation and medical industries.
  • Amid the COVID-19 outbreak, many companies were concerned about ensuring the quality and access to their data during this uncertain pandemic. The demand for various solutions that aid enterprises in data analytics has garnered significant attention and a positive trend in adoption. The global shift toward remote working and cloud adoption further intensified the demand for solutions that help increase work efficiency and effectiveness. Companies invested in processes and infrastructure to democratize data and enable access when the majority of the workforce works remotely as a result of the COVID-19 outbreak.

Data Quality Tools Market Trends

Healthcare is Expected to Witness Significant Growth

  • Data management in the healthcare sector is a complex process. It is composed of several key ingredients: data governance, data integration, data enrichment, data storage, and data analysis. While data processing systems are becoming critical components of operational decision-making and individualized treatment processes, poor data quality and management are becoming a primary interference with operational success and are causing significant strain on such methods.
  • The healthcare industry's most commercial data collection tools are enterprise data warehouses (EDWs). They are designed to cluster data from multiple sources into a single, unified, and integrated data repository. The data is embedded within the EDW, so users can analyze the previously fixed data and get more ROI from existing source systems. Moreover, hospitals and care providers are adopting big data analytics and population health management technologies to meet the new healthcare standards' requirements and the growing demands and expectations of patients.
  • Moreover, hospitals and care providers are adopting big data analytics and population health management technologies to meet the requirements of the new healthcare standards and the increasing demand and expectations of patients. BI tools can help improve quality performance by identifying system flaws and capturing missing data content.Healthcare business intelligence (BI) solutions, which analyze the data in electronic health records (EHRs), genetic studies, etc., can be applied for individualized treatment.
  • The COVID-19 pandemic created a need for designing systems for the recording of care, as it would be used to create knowledge that the data generated from the system would be needed to plan services. The real-world importance of this information reinforced the real value that high-quality data can provide. It pulled together many data points, including survival data, comorbidities, and length of stay, which ultimately helped improve the patient experience and improve outcomes.
  • Companies in healthcare are adopting new tools and collaborating to share data for an improved healthcare system. For instance, in August last year, Walmart announced that it joined the QCC, which supports data quality improvement in radiology services. The QCC is a national program to bring together payers, providers, and self-insured employers to improve radiology quality at scale.

Asia-Pacific Expected to Register the Highest Growth Rate

  • In terms of revenue, the data quality tools market in Asia-Pacific is the one that is growing the fastest. This is primarily due to the increasing interest in data quality improvement solutions and a rising focus on data-driven scientific and strategic decision-making practices. With the growth of smart cities and the proliferation of IoT devices, the region is expected to witness unprecedented growth in the future. Also, the start-up culture, the government's ability to be flexible, and the growth of the eCommerce business are all important factors driving the market in the region.
  • In October last year, China's State Council outlined a plan to create a "National Integrated Government Affairs Big Data System" that, by the year 2025, is expected to make millions of government data sets available from one place. The huge amount of data in one place would create the need for dynamic updates of databases and catalogs with continuous improvement of data quality.
  • The firms are facing significant challenges with managing data for regulatory requirements and gaining meaningful insights. For example, the Reserve Bank of India (RBI) says that mobile banking transactions in India were worth more than INR 17,149,070 million (USD 2,102,47 million) in June of last year.

With such an abundance of data, there is a considerable risk of data quality issues in the banking and financial services industries. These data quality problems in the sector have a direct effect on the customer experience, interactions, transactions, and many other things. This means that the company has to pay more and loses money, which creates a need for data quality tools in the sector.

Data Quality Tools Industry Overview

The market for data quality tools could be more cohesive, with several domestic and international companies offering advanced solutions. Due to the presence of significant vendors in the market, the intense competition encourages them to focus on areas to enhance their customer reach across various geographies. Additionally, different data quality tool providers are focusing more on providing a comprehensive set of solutions to their customers to gain increased market traction.

In October 2022, Anomalo, the complete data quality platform company, announced a partnership with dbt Labs to provide data quality for dbt metrics, a part of the new dbt Semantic Layer. dbt is a transformation framework that enables businesses to transform, test, and document data in the cloud, producing data that the entire organization can use.

In January 2022, IBM Corporation and Francisco Partners, a global investment firm specializing in partnering with technology businesses, announced the signing of a definitive agreement under which Francisco Partners is expected to acquire healthcare data and analytics assets from IBM, which are presently part of the Watson Health business. Francisco Partners bought a lot of different kinds of data and products, such as MarketScan, Health Insights, Clinical Development, Micromedex, Social Program Management, and imaging software.

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 INSIGHT

  • 4.1 Market Overview
  • 4.2 Industry Value Chain Analysis
  • 4.3 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.3.1 Bargaining Power of Suppliers
    • 4.3.2 Bargaining Power of Consumers
    • 4.3.3 Threat of New Entrants
    • 4.3.4 Threat of Substitute Products
    • 4.3.5 Intensity of Competitive Rivalry
  • 4.4 Assessment of COVID -19 impact on the market

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Increasing Use of External Data Sources Owing to Mobile Connectivity Growth
  • 5.2 Market Restraints
    • 5.2.1 Lack of information and Awareness about the Solutions Among Potential Users

6 MARKET SEGMENTATION

  • 6.1 By Deployment Type
    • 6.1.1 Cloud-based
    • 6.1.2 On Premise
  • 6.2 By Size of the Organization
    • 6.2.1 Small and Medium Enterprises
    • 6.2.2 Large Enterprises
  • 6.3 By Component
    • 6.3.1 Software
    • 6.3.2 Services
  • 6.4 By End-user Vertical
    • 6.4.1 BFSI
    • 6.4.2 Government
    • 6.4.3 IT & Telecom
    • 6.4.4 Retail and E-commerce
    • 6.4.5 Healthcare
    • 6.4.6 Other End-user Industries
  • 6.5 Geography
    • 6.5.1 North America
    • 6.5.2 Europe
    • 6.5.3 Asia-Pacific
    • 6.5.4 Latin America
    • 6.5.5 Middle East and Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 IBM Corporation
    • 7.1.2 Informatica LLC
    • 7.1.3 Oracle Corporation
    • 7.1.4 SAP SE
    • 7.1.5 SAS Institute Inc.
    • 7.1.6 Talend Inc.
    • 7.1.7 Experian PLC
    • 7.1.8 Information Builders Inc.
    • 7.1.9 Pitney Bowes Inc.
    • 7.1.10 Syncsort Inc.
    • 7.1.11 Ataccama Corporation

8 INVESTMENT ANALYSIS

9 FUTURE OF THE MARKET