글로벌 데이터 품질 도구 시장 규모, 점유율 및 추세 분석 보고서 – 산업 개요 및 2031년까지의 예측

데이터 품질 도구 시장 분석

데이터 품질 도구 시장은 다양한 산업에서 정확하고 신뢰할 수 있는 데이터에 대한 수요가 증가함에 따라 강력한 성장을 경험하고 있습니다. 조직이 데이터 중심 의사 결정에 의존함에 따라 데이터 무결성을 보장하는 것이 가장 중요해졌습니다. 이러한 도구는 데이터의 정리, 검증 및 보강을 용이하게 하여 기업이 고품질 데이터 자산을 유지할 수 있도록 합니다. 최근 개발에는 인공 지능 과 머신 러닝의 발전이 포함되며, 이는 데이터 품질 도구의 기능을 향상시켜 자동화된 데이터 프로파일링 및 이상 탐지를 가능하게 합니다. 클라우드 기술의 통합도 시장을 재편하여 데이터 품질 관리를 위한 확장 가능한 솔루션을 제공하고 있습니다. 또한 규정 준수와 데이터 거버넌스에 대한 강조가 커지면서 조직이 열악한 데이터 품질과 관련된 위험을 완화하려고 하면서 이러한 도구의 채택이 촉진되고 있습니다. 전반적으로 데이터 품질 도구 시장은 상당한 성장을 앞두고 있으며, 진화하는 비즈니스 요구 사항을 충족하기 위한 혁신이 계속 등장하고 있습니다.

데이터 품질 도구 시장 규모

글로벌 데이터 품질 도구 시장 규모는 2023년에 15억 9천만 달러로 평가되었으며, 2031년까지 60억 6천만 달러에 도달할 것으로 예상되며, 2024년에서 2031년까지의 예측 기간 동안 CAGR은 18.20%입니다. Data Bridge Market Research 팀이 큐레이팅한 시장 보고서에는 시장 가치, 성장률, 시장 세그먼트, 지리적 범위, 시장 참여자, 시장 시나리오와 같은 시장 통찰력 외에도 심층적인 전문가 분석, 수입/수출 분석, 가격 분석, 생산 소비 분석, 페슬 분석이 포함되어 있습니다.

데이터 품질 도구 시장 동향

“클라우드 기반 데이터 품질 솔루션에 대한 수요 증가”

데이터 품질 도구 시장은 조직이 데이터 정확성과 신뢰성을 점점 더 우선시함에 따라 상당한 추세를 보이고 있습니다. 인공 지능과 머신 러닝의 혁신은 이러한 도구를 변형하여 자동화된 데이터 정리, 검증 및 강화 프로세스를 가능하게 합니다. 주목할 만한 추세 중 하나는 클라우드 기반 데이터 품질 솔루션에 대한 수요가 증가하여 팀 간 실시간 데이터 모니터링 및 협업이 가능하다는 것입니다. 이러한 솔루션은 모든 규모의 기업에 적합한 확장성과 유연성을 제공합니다. 또한 데이터 품질 도구와 데이터 거버넌스 프레임워크를 통합하여 조직이 높은 데이터 표준을 유지하면서 규정을 준수하는 능력을 향상시키고 있습니다. 데이터 기반 인사이트의 중요성이 계속 커짐에 따라 기술 발전과 진화하는 비즈니스 요구 사항에 따라 데이터 품질 도구 시장이 빠르게 확장될 것으로 예상됩니다.

보고서 범위 및 데이터 품질 도구 시장 세분화  

Data Quality Tools Market Definition

Data quality tools are software solutions that ensure the accuracy, consistency, and reliability of data. They perform functions like data profiling, cleansing, validation, and monitoring to identify and resolve issues. These tools enhance data integrity, facilitate effective decision-making, and support regulatory compliance by maintaining high data quality standards within an organization.

Data Quality Tools Market Dynamics

Drivers

• Emergence of Big Data and IoT

The rise of big data analytics and Internet of Things (IoT) applications significantly amplifies the complexity and volume of data that organizations must manage. As businesses increasingly rely on real-time data from various connected devices, the amount of information generated grows exponentially. This surge in data presents challenges in maintaining accuracy, consistency, and relevance, necessitating robust data quality tools. Effective quality solutions are essential for organizations to ensure reliable data streams, enabling insightful analytics and decision-making. Consequently, the demand for data quality tools is driven by the need to handle this complex data landscape effectively, ensuring optimal operational performance and strategic advantage.

• Increasing Data Proliferation

The increasing volumes of data generated by businesses across various sectors necessitate effective data management and quality assurance practices. As organizations adopt digital transformation strategies and leverage advanced technologies, they accumulate vast amounts of structured and unstructured data daily. This data, if not managed properly, can lead to inaccuracies, inconsistencies, and unreliable insights. Consequently, there is a heightened need for data quality tools that can effectively profile, cleanse, and validate data, ensuring its integrity and usability. This growing demand for effective data management solutions is a significant market driver, enabling organizations to make informed decisions and maintain a competitive edge in the marketplace.

Opportunities

• Small Cloud-based Solutions

As organizations migrate to cloud environments, the demand for cloud-compatible data quality tools is rapidly increasing. This shift allows businesses to store and process vast amounts of data efficiently while benefiting from the scalability and flexibility of cloud infrastructure. However, with this transition comes the challenge of maintaining data quality across diverse cloud applications and services. Vendors have a significant opportunity to develop and offer tailored data quality solutions that integrate seamlessly with cloud platforms. These tools can enhance data governance, ensure compliance, and enable real-time analytics, ultimately empowering organizations to harness the full potential of their data in cloud environments.

• Customization and User-Friendly Interfaces

Offering customizable and user-friendly data quality solutions presents a significant market opportunity, particularly for smaller businesses with limited IT resources. Many small to medium-sized enterprises (SMEs) often struggle to implement complex data management systems due to budget constraints and a lack of specialized personnel. By providing tools that are intuitive and easily adaptable to various business needs, vendors can cater to this underserved market segment. Customizable features allow organizations to tailor solutions to their specific data challenges, while user-friendly interfaces enable quick adoption without extensive training. This approach broadens the customer base and fosters long-term relationships with SMEs seeking effective data quality management.

Restraints/Challenges

• Lack of Skilled Personnel

A significant challenge in the data quality tools market is the lack of skilled personnel knowledgeable in data quality management and analytics. Many organizations struggle to find qualified professionals who can effectively implement and utilize these tools, which can limit their potential benefits. Without the right expertise, companies may encounter difficulties in configuring, maintaining, and maximizing the capabilities of data quality solutions. This skills gap can lead to inefficient data management practices and poor data quality outcomes. Consequently, organizations may fail to realize the full value of their investments in data quality tools, hindering overall performance and decision-making capabilities.

• High Implementation Costs

One of the key restraints in the data quality tools market is the initial investment and ongoing costs associated with deploying these solutions. For small and medium-sized enterprises (SMEs), these financial barriers can be particularly prohibitive, limiting their ability to implement effective data management strategies. The costs include not only the purchase of the software but also expenses related to installation, training, and maintenance. Additionally, ongoing operational costs can strain the budgets of SMEs, making it challenging to allocate resources for continuous improvement in data quality. As a result, many organizations may delay or forego investing in data quality tools, impacting their overall data management capabilities.

Data Quality Tools Market Scope

The market is segmented on the basis of data type, business function, deployment model, organization size, and vertical. The growth amongst these segments will help you analyze meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

Data Type

• Customer Data
• Product Data
• Financial Data
• Compliance Data
• Supplier Data

Business Function

• Software
• Services

Deployment Model

• On-Premises
• On-Demand

Organization Size

• Large Enterprises
• Small and Medium-Sized Enterprises

Vertical

• Banking
• Financial Services and Insurance
• Telecommunications and IT
• Retail and E-Commerce
• Healthcare and Life Sciences
• Manufacturing
• Government
• Energy and Utilities
• Media and Entertainment
• Others

Data Quality Tools Market Regional Analysis

The market is analyzed and market size insights and trends are provided by data type, business function, deployment model, organization size, and vertical as referenced above.

The countries covered in the market report are U.S., Canada, Mexico in North America, Germany, Sweden, Poland, Denmark, Italy, U.K., France, Spain, Netherland, Belgium, Switzerland, Turkey, Russia, Rest of Europe in Europe, Japan, China, India, South Korea, New Zealand, Vietnam, Australia, Singapore, Malaysia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in Asia-Pacific (APAC), Brazil, Argentina, Rest of South America as a part of South America, U.A.E, Saudi Arabia, Oman, Qatar, Kuwait, South Africa, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA).

North America is expected to dominate the data quality tools market throughout the forecast period, driven by the increasing adoption of data quality services. The substantial growth in the volume of data collected daily further amplifies the demand for effective data quality tools across various sectors. As organizations strive to harness this data effectively, the need for robust data quality solutions becomes essential for maintaining data integrity and supporting informed decision-making.

Asia-Pacific region is projected to experience significant growth in the data quality tools market, fueled by rising data collection efforts in countries such as China and India. As these nations rapidly digitize their economies and generate vast amounts of data, the need for effective data quality solutions becomes increasingly critical. This trend presents a valuable opportunity for vendors to cater to the growing demand for tools that ensure data accuracy and reliability in this dynamic market.

The country section of the report also provides individual market impacting factors and changes in market regulation that impact the current and future trends of the market. Data points such as down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.

Data Quality Tools Market Share

The market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies' focus related to market.

Data Quality Tools Market Leaders Operating in the Market Are:

• IBM (U.S.)
• Informatica Inc. (U.S.)
• Oracle (U.S.)
• SAP (Germany)
• SAS Institute Inc. (U.S.)
• Cloud Software Group, Inc. (U.S.)
• Precisely (U.S.)
• Tamr (U.S.)
• KNIME (Switzerland)
• The MathWorks, Inc. (U.S.)
• Alteryx (U.S.)
• FICO (U.S.)
• Minitab LLC. (U.S.)
• Microsoft (U.S.)
• Pitney Bowes Inc. (U.S.)
• Talend Inc. (France)
• Experian Information Solutions, Inc. (U.K.)
• Trianz (U.S.)
• Quadient (France)
• TECHTARGET (U.S.)
• Symphonic Source Inc. (U.S.)

Latest Developments in Data Quality Tools Market

• In April 2024, IBM unveiled an upgrade to its IBM InfoSphere Information Server, incorporating advanced data quality enhancements. The updated platform features real-time data validation and cleansing capabilities, aimed at improving data governance and analytics. This upgrade is designed to empower organizations to manage their data more effectively, ensuring higher quality and reliability for informed decision-making
• 2023년 11월, Informatica는 데이터 관리 프로세스를 개선하도록 설계된 혁신적인 AI 기반 데이터 품질 플랫폼을 출시했습니다. 이 플랫폼은 고급 머신 러닝 알고리즘을 활용하여 데이터 이상을 자동으로 식별하고 수정하여 수동 데이터 정리의 필요성을 최소화하는 동시에 정확도를 크게 높입니다. 이러한 프로세스를 간소화함으로써 Informatica의 솔루션은 조직이 높은 데이터 품질을 보다 효율적이고 효과적으로 유지할 수 있도록 지원합니다.
• 2023년 2월, 통합 데이터 관리 플랫폼의 저명한 공급업체인 Ataccama는 Data Cloud 회사인 Snowflake와 Ataccama ONE 플랫폼의 향상된 통합을 발표했습니다. 이 통합은 푸시다운 처리 및 데이터 관찰 기능을 도입하여 공유 고객이 Snowflake의 통합 플랫폼에서 직접 데이터를 처리할 수 있도록 합니다. 결과적으로 조직은 더 빠르고 비용 효율적이며 안전한 데이터 결과를 달성하여 데이터 관리 프로세스를 최적화할 수 있습니다.
• 2022년 9월, DataCebo는 MIT 컴퓨터 과학 및 인공지능 연구실에서 분사하여 개발한 새로운 도구인 Synthetic Data(SD) Metrics를 출시했습니다. 이 혁신적인 솔루션을 통해 기업은 기계에서 생성된 합성 데이터의 품질을 실제 데이터 세트와 평가하고 비교할 수 있습니다. SD Metrics는 데이터 충실도에 대한 귀중한 통찰력을 제공함으로써 다양한 산업에서 합성 데이터 애플리케이션의 신뢰성과 효과를 향상시키는 것을 목표로 합니다.

SKU-25182