How big is the data observability market today, and what are its future growth expectations?
The data observability market size has grown rapidly in recent years. It will grow from $2.53 billion in 2024 to $2.94 billion in 2025 at a compound annual growth rate (CAGR) of 16.1%. The growth in the historic period can be attributed to increase in demand for data-driven decision-making, growth in volume of data, expansion of cloud-based solutions, rise in adoption of artificial intelligence and machine learning technologies, and emergence of big data analytics solutions.
The data observability market size is expected to rapid growth in the next few years. It will grow to $5.27 billion in 2029 at a compound annual growth rate (CAGR) of 15.8%. The growth in the forecast period can be attributed to rising need for enhanced compliance solutions, rising demand for real-time data insights, growing focus on data quality management, rising importance of automated monitoring solutions, and growing need for enhanced visualization tools. Major trends in the forecast period include advancements in real-time monitoring, automated anomaly detection, adoption of data lineage visualization, adoption of AI-driven insights, enhanced data quality management, integration with cloud platforms, and advancements alerting systems.
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What have been the primary factors driving the data observability market’s growth?
The expansion of cloud computing is expected to drive the growth of the data observability market going forward. Cloud computing delivers computing services such as servers, storage, databases, networking, software, and analytics over the internet, allowing users to access and utilize shared resources on demand while reducing the need for physical infrastructure management. The expansion of cloud computing is driven by scalability, flexibility, and cost efficiency, allowing organizations to quickly adapt to changing demands and optimize their information technology resources. Data observability solutions are essential in cloud computing environments, providing visibility and control over complex data flows to ensure real-time accuracy, performance, and compliance. For instance, in December 2023, according to Eurostat, a Luxembourg-based government agency responsible for statistics and data on Europe, in 2023, around 42.5% of European Union businesses purchased cloud computing services, primarily for email, file storage, and office software. This represents a 4.2 percentage point increase compared to 2021. Therefore, the expansion of cloud computing is driving the growth of the data observability market.
What are the key segments within the data observability market?
The data observability market covered in this report is segmented –
1) By Component: Solution, Services
2) By Deployment Model: Cloud-Based, On-Premises, Hybrid
3) By End-User: Banking, Financial Services, And Insurance (BFSI), Information Technology (IT) And Telecom, Government And Public Sector, Energy And Utility, Manufacturing, Healthcare And Life Science, Retail And Consumer Goods, Other End Users
Subsegments:
1) By Solution: Data Monitoring, Data Profiling, Data Lineage Tracking, Anomaly Detection
2) By Services: Consulting Services, Integration And Deployment Services, Support And Maintenance Services
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Which key players are shaping the data observability market?
Major companies operating in the data observability market are Alphabet (Google LLC), Microsoft Corporation, International Business Machines Corporation, Amazon Web Services Inc., Splunk Inc., Snowflake Inc., Datadog Inc., Informatica Corporation, Databricks Inc., Dynatrace LLC, Elastic NV, Alteryx Inc., New Relic Inc., TIBCO Software Inc., DataRobot Inc., AppDynamics Inc., Fivetran, Talend S.A., Cribl, Dremio, Acceldata Inc., Astronomer Inc., Monte Carlo Data Inc., DataKitchen, StackState
How will emerging trends drive the data observability market throughout the forecast period?
Major companies operating in the data observability market are focusing on technological advancements such as integrating artificial intelligence (AI) in data observability to enhance the accuracy, efficiency, and scalability of data monitoring, enabling real-time anomaly detection, predictive insights, and automated resolution of data issues across complex systems. Artificial Intelligence (AI) is the development of machines that can perform tasks requiring human intelligence, such as learning, problem-solving, and decision-making, improving through experience. For instance, in May 2024, Riverbed Technology LLC, a US-based information technology company, launched its AI-powered riverbed platform designed to optimize digital experiences by leveraging data and AI for enhanced observability and intelligence. Key features include a unified agent for simplified deployment across IT environments, the riverbed data store for processing data without needing separate repositories, and enhanced observability by integrating data from networks, applications, and cloud infrastructures. The platform also incorporates AIOps for automated analysis and remediation and new solutions such as Aternity mobile for mobile monitoring and NPM+ for network performance monitoring in cloud and zero trust environments.
How do regional factors impact the data observability market, and which region is the largest contributor?
North America was the largest region in the data observability market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the data observability market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
What Does The Data Observability Market Report 2025 Offer?
The data observability market research report from The Business Research Company offers global market size, growth rate, regional shares, competitor analysis, detailed segments, trends, and opportunities.
Data observability refers to the ability to monitor, track, and understand the health and behavior of data systems through comprehensive visibility into the entire data lifecycle. It proactively identifies and addresses real-time issues and ensures data reliability, quality, and performance. Data observability is crucial for organizations relying on data-driven decision-making by maintaining trust in data systems, reducing downtime, and ensuring the smooth functioning of data pipelines.
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