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市場調查報告書
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1630257

資料品質工具：市場佔有率分析、產業趨勢與成長預測（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個工作天內

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簡介目錄

資料品質工具市場預計在預測期內複合年成長率為 17.5%

數據品質工具-市場-IMG1

主要亮點

  • 根據《哈佛商業評論》(HBR) 報道，使用有缺陷的資料完成一個工作單元的成本高出 10 倍。
  • 資料品質工具通常涉及四個主要部分：資料清理、資料整合、主資料管理和元資料管理。由於資料品質是大型企業的主要關注點，因此軟體公司正在提案越來越多的工具來解決此類問題。這些工具的範圍正在從特定用例（例如重複資料刪除、地址規範化）轉向更全局的觀點，整合資料品質的所有部分（例如分析、規則發現）。
  • 行動技術的最新進展使用戶可以自動在線記錄資料，並且資料量迅速增加。此外，雲端運算基礎設施的能力和規模不斷加速，幾乎超出了我們利用其提供的機會的能力。
  • 此外，製造公司處理多個資料流，需要對其進行分析以最佳化業務資源。這些行業通常需要處理常規、結構化工廠資料、模擬資料以及企業資源規劃 (ERP) 系統和各種流程自動化和控制系統等應用程式產生的資訊。保持資料品質對於最佳化製造供應鏈至關重要。例如，積層製造(AM) 需要資料管理工具來確保品質、可重複性、可追溯性和可靠性，特別是在嚴格監管的航空和醫療產業。
  • 在 COVID-19 大流行期間，許多公司都擔心在這種不確定的大流行期間確保資料品質和存取。對幫助企業分析資料的各種解決方案的需求正在獲得巨大的吸引力，並且採用趨勢也在改善。世界向遠端工作和雲端採用的轉變進一步增加了對有助於提高工作效率和效力的解決方案的需求。由於大多數員工因 COVID-19 大流行而遠端工作，公司投資於流程和基礎設施，以實現資料的民主化和存取。

資料品質工具市場趨勢

醫療保健預計將實現顯著成長

  • 醫療保健領域的資料管理是一個複雜的過程。資料管理由幾個關鍵要素組成：資料管治、資料整合、資料充實、資料儲存和資料分析。資料處理系統正在成為業務決策和個人化護理流程的關鍵組成部分，但糟糕的資料品質和管理正在成為阻礙業務成功的關鍵因素，給我所採用的這些方法帶來了巨大的壓力。
  • 醫療保健產業中最商業化的資料收集工具是企業資料倉儲 (EDW)。 EDW 旨在將多個來源的資料聚合到一個統一的資料儲存庫中。資料嵌入在 EDW 中，允許用戶分析先前固定的資料並從現有來源系統中獲得更多投資回報。此外，醫院和護理提供者正在採用巨量資料分析和人口健康管理技術，以滿足新的醫療保健標準的要求以及患者日益成長的需求和期望。
  • 此外，醫院和護理提供者正在實施巨量資料分析和人口健康管理技術，以滿足新的醫療保健標準的要求以及不斷成長的患者需求和期望。 BI 工具透過識別系統缺陷並了解遺失的資料來幫助提高品質績效。分析電子健康記錄(EHR) 和基因研究等資料的醫療商業智慧(BI) 解決方案可應用於個人化治療。
  • COVID-19 大流行需要設計用於記錄護理的系統，因為系統產生的資料用於產生服務規劃所需的知識。這些資訊的實際重要性增強了高品質資料所能提供的真正價值。它匯集了許多資料點，包括生存資料、共病和住院時間，最終有助於改善患者體驗和改善結果。
  • 醫療保健公司正在採用新工具並合作共用資料以改善醫療保健系統。例如，去年8月，沃爾瑪宣布參與QCC，有助於提昇放射服務的資料品質。 QCC 是一項全國性計劃，將付款人、提供者和自保雇主聚集在一起，以大規模提高放射護理品質。

亞太地區預計將創下最高成長率

  • 從銷售額來看，亞太資料品質工具市場成長最快。這主要是由於對資料品質改進解決方案的興趣增加以及對資料驅動的科學和戰略決策技術的關注增加。隨著智慧城市的發展和物聯網設備的激增，預計該地區未來將經歷前所未有的成長。新興企業應對力推動該地區市場的關鍵因素。
  • 去年10月，中國國務院宣布計劃建造“國家綜合政務巨量資料系統”，到2025年將實現數百萬政府資料“一地可用”。將大量資料收集到一處需要動態更新資料庫和目錄以不斷提高資料品質。
  • 企業在管理資料和獲得符合監管要求的有意義的見解方面面臨重大挑戰。例如，根據印度儲備銀行（RBI）的數據，去年 6 月印度行動銀行交易額超過 171,490.7 億印度盧比（2,102.47 億美元）。

由於資料量如此之大，銀行和金融服務業的資料品質問題風險很高。產業中的這些資料品質問題直接影響客戶體驗、互動、交易等。這意味著企業必須支付更多費用並遭受損失，從而產生了該領域對資料品質工具的需求。

資料品質工具產業概述

資料品質工具市場可能更具凝聚力，多家國內外公司提供先進的解決方案。由於市場上有大量供應商，激烈的競爭促使每個供應商都專注於能夠擴大其對不同地區客戶的影響力的細分市場。此外，各種資料品質工具提供者越來越注重向客戶提供全面的解決方案集，以增加市場吸引力。

2022 年 10 月，完整的資料品質平台公司 Anomalo 宣布與 dbt Labs 合作，為 dbt 指標（新 dbt 語意層的一部分）提供資料品質。

2022 年 1 月，專門與 IBM 公司和技術企業合作的全球投資公司 Francisco Partners 宣布，Francisco Partners 已簽訂最終協議，從 IBM 收購醫療保健資料和分析資產。 Francisco Partners 購買多種類型的資料和產品，包括 MarketScan、Health Insights、臨床開發、Micromedex、社交專案管理和影像軟體。

其他好處

  • Excel 格式的市場預測 (ME) 表
  • 3 個月分析師支持

目錄

第1章簡介

  • 研究假設和市場定義
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章市場洞察

  • 市場概況
  • 產業價值鏈分析
  • 產業吸引力－波特五力分析
    • 供應商的議價能力
    • 消費者議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭公司之間敵對關係的強度
  • 評估 COVID-19 對市場的影響

第5章市場動態

  • 市場促進因素
    • 由於行動連線的成長，外部資料來源的使用增加
  • 市場限制因素
    • 潛在用戶缺乏有關解決方案的資訊和認知

第6章 市場細分

  • 依部署類型
    • 雲端基礎
    • 本地
  • 按組織規模
    • 小型企業
    • 主要企業
  • 按成分
    • 軟體
    • 服務
  • 按行業分類
    • BFSI
    • 政府機構
    • 資訊科技/通訊
    • 零售/電子商務
    • 醫療保健
    • 其他
  • 地區
    • 北美洲
    • 歐洲
    • 亞太地區
    • 拉丁美洲
    • 中東/非洲

第7章 競爭格局

  • 公司簡介
    • 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8章投資分析

第9章市場的未來

簡介目錄
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