Low-Code Embedded Analytics Market Report Scope & Overview:

The low-code embedded analytics market size was valued at USD 14.9 billion in 2024 and is expected to reach USD 34.0 billion by 2032, growing at a CAGR of 10.89% during 2025-2032.

The low-code embedded analytics market growth is accelerating as enterprises turn to embedded solutions that allow them to surface live contact insights into the workflow of their applications without requiring complex coding. Such a market can allow business users to easily create, customize, and deploy interactive dashboards, reports, and other visualizations, truly embedding analytics within business workflows. The increase in digital transformation initiatives drives this demand, and the need to make data-driven decisions and a shortage of skilled developers. Low-code embedded tools enable organizations to integrate software applications into various user interfaces, enhancing the user experience, reducing time to market, and gaining a competitive edge. Consequently, enterprises across sectors, such as BFSI, healthcare, retail, and manufacturing are leveraging low-code embedded tools. Finally, such platforms are also driving innovation by integrating AI/ML and automation.

In the U.S. Low-Code Embedded Analytics Market, growth is driven by the growing enterprise needs for integrated insights and self-service BI tools. The market was valued at USD 3.9 billion in 2024 and is projected to reach USD 8.9 billion by 2032, growing at a CAGR of 10.69%. Key Low-Code Embedded Analytics Market trend includes the utilization of artificial intelligence-based low-code platforms that provide organizations with fast, scalable, and wide-ranging integration across sectors.

Market Dynamics:

Drivers:

• Rising Demand for Real-Time Decision-Making Leads to Increased Adoption of Self-Service Low-Code Embedded Analytics Platforms

With virtual and physical workforces working in silos and the need for real-time decision-making and access to data, low-code embedded analytics platforms have become in demand. Organizations have also started pushing self-service analytics, enabling non-technical users to derive insights independently with limited reliance on the IT team. Analytic integration in operational applications through low-code tools provide users with insights to make decisions where they work. The increasing adoption of agility, cost-effectiveness, and faster deployment is one of the prominent driving forces that is expected to support the growth of cloud app security across various industries, including retail, BFSI, and healthcare. A drag-and-drop interface is enabling greater customization of dashboards and reports for embedded analytics, leading to higher adoption.

According to a Forrester Analytics Business Technographics Data & Analytics Survey (2024), 70% of enterprises stated that enabling real-time decision-making was among their top three objectives for analytics investment.

Restraints:

• Data security concerns and legacy system complexities result in slower adoption among highly regulated industries

Though it helps in deploying an analytics solution with ease, without LCP applications, it can face serious data security and other integration challenges with legacy systems. One of the reasons organizations are hesitant to embed analytics into mission-critical applications is due to security vulnerabilities. Without appropriate IT governance, joining these platforms with the different data sources, on-premise systems, and APIs can be challenging. Such integrations can also result in data silo, compliance, and performance problems. The whole rigmarole around security protocols, access controls, and audit capabilities needs to be closely configured, requiring immense backend know-how. This is especially true in highly regulated sectors, including finance and healthcare, where such tailspins can inhibit adoption due to compliance-related concerns.

A 2024 survey found that 62% of organizations in regulated sectors (healthcare, BFSI, and government) identified data security and compliance as their primary barrier to adopting embedded analytics platforms.

Opportunities:

• Growing low-code adoption among SMBs creates new market avenues for affordable embedded analytics solutions

With the increasing adoption of low-code embedded analytics, small, and medium-sized businesses will be able to compete on par with large enterprises. They provide low-cost and scalable solutions, mitigating the dependency on big development teams and giving the edge of time to market in acquiring data applications. Given that SMBs are trying to get data-driven without too much investment in infrastructure and talent, the low-code analytics is something very appealing. Cloud deployment models combined with a pay-as-you-go pricing model additionally make it accessible. In addition, with computing power and storage becoming cheaper, the AI and automation are enabling these platforms to provide predictive and prescriptive insights for smaller datasets as well. This trend leaves countless opportunities on the table for vendors who target market segments overlooked by others or have traditionally only focused on low-budget requests.

Challenges:

• Limited Customization in Low-Code Tools Hinders Scalability for Complex Enterprise-level Analytics Use Cases

Low-code platforms are great for many reasons but may fail on specific and advanced analytics for large enterprise size. Workflows that are even a little bit complex will require integrations deep in the backend, custom visualizations, or custom machine learning models, beyond the capabilities of drag and drop. As businesses scale, the analytics workload and complexity usually increase, and they require higher customization and flexibility, which is not efficiently provided by low-code delivery platforms. This means that, to get things working, developers will have to step in, thus meeting the speed benefits of low-code environments ineffective. This limitation in scalability conjunction with vendor lock-in risk, is a critical problem for enterprises with long-term digital transformation paths and shifting analytics needs.

Segmentation Analysis:

By Deployment:

The cloud-based platforms segment dominated the market in 2024 and accounted for 75% of the low-code embedded analytics market share, as cloud-based platforms provide higher scalability, lower upfront cost, and are more efficiently integrated with SaaS Applications. They provide analytical access in real time and remote work environments. Cloud deployment trend through 2032, due to rapid migration of work to the cloud and a shift in priorities of both SMBs and enterprises for agile and data-informed decision making.

In September 2024, Jitterbit enhanced its cloud-based Harmony low-code integration platform with AI-driven capabilities, automating connector creation, building logic via drag-and-drop, and adding documentation querying features. 

On-premises platforms are expected to register the fastest CAGR due to highly regulated industries, such as healthcare and BFSI, where data sovereignty and stringent compliance are of utmost importance. This boom is being driven by organizations putting a premium on control and infrastructure. Driven by growing demand for data-sensitive use cases and shifting preferences between on-premises and cloud deployments, the trend toward private cloud and hybrid models is expected to strengthen steadily through 2032.

By Enterprise Size:

Large enterprises dominated the low-code embedded analytics market in 2024 and accounted for 81% of revenue share, due to the significant digital base, bigger analytics budgets, and demand for real-time insights and generation across their multi-layered operations. These organizations value embedded analytics as an operational and strategic tool. Large enterprises till 2032 will remain adoption leaders as they are primarily automating AI integration, capturing cross-departmental analytics demand, and increasing investments will be made in enterprise-wide low-code partnerships.

In March 6, 2025, Appian introduced version 25.1, enhancing its enterprise low‑code platform with improved AI-driven document processing and centralized dashboards. The release supports syncing up to 10 million rows per record type, enabling large enterprises to embed high-performance analytics into mission-critical applications. 

SMEs are expected to register the fastest CAGR owing to increasing accessibility of low-code platforms via the cloud and the rising demand for affordable analytics solutions. SMEs, which are already strapped with limited IT resources, prefer intuitive tools that cut down on development time. The need for embedded analytics will grow rapidly, with small and medium-sized businesses (SMBs) that are adapting digitally, especially those in retail, services, and logistics, becoming a key driver of demand by 2032.

By Application:

CRM analytics dominated the low-code embedded analytics market in 2024 and accounted for a significant revenue share, owing to their increasing demand for real-time customer insights, personalized customer engagement, and integration of automated sales intelligence. Low-code tools are used by enterprises to integrate analytics inside the CRM systems, such as Salesforce and HubSpot. CRM analytics will continue leading the feasible market for companies aiming for a customer-centric strategy with every lead, conversion, and retention based on data-driven decision-making until 2032.

Supply chain analytics is expected to register the fastest CAGR during the forecast period, driven by the increasing volatility in global logistics, time-sensitive demand forecasting needs and risk mitigation. Real-time dashboards for inventory, suppliers, and disruptions can be deployed quickly using low-code platforms. Embedded analytics will grow rapidly due to the digital supply chain transformation and IoT data integration opportunities across logistics and manufacturing verticals through 2032.

By Industry:

The BFSI sector dominated the low-code embedded analytics market in 2024 and accounted for a significant revenue share, owing to the industry necessity for real-time fraud detection, regulatory compliance, and providing personalized financial services. For instance, financial institutions utilize embedded analytics to score credit, model risk, and segment customers. BFSI continues to lead through 2032 as secure and low-code analytics solutions capable of being integrated into data-centric operations and automated processes become the preferred choice for investment.

Healthcare is expected to register the fastest CAGR, owing to the rising adoption of embedded analytics in EHR, diagnostics, and optimizations in delivering patient care. Low-code platforms make it easier to develop applications in real-time so that organizations can get insights on patient data, treatment outcomes, and the utilization of the resources. Regulatory changes and digital health transformation will lead to analytic deployment across hospitals and clinics skyrocketing by 2032.

Regional Analysis:

North America dominated the low-code embedded analytics market owing to early technology adoption, the presence of key vendors, and a mature enterprise ecosystem in the region. The growth is propelled by several factors, including increased demand for real-time data insight in various sectors, especially BFSI, IT, and healthcare verticals. Meanwhile, continued capital expenditures in cloud infrastructure and machine-learning-based analytics will further sustain North America’s dominance in this market through 2032.

Asia-Pacific is expected to register the fastest CAGR, driven by a rise in cloud adoption and the expansion of SMEs in countries, such as India, China, and the countries in Southeast Asia. The demand is being fueled by government initiatives promoting innovation in tech and affordable analytics tools. The growth of the region will further accelerate by 2032 as enterprises will crave for scalable and low-code analytics that facilitate real-time decision making and localization.

Europe's growth in the low-code embedded analytics market is owing to the exponentially increasing adoption of them in banking, manufacturing, and healthcare. Demand for secure analytics solutions is growing due to regulatory compliance (such as GDPR). The uptake of low-code analytics will continue to widen through 2032 as organizations look to spread the benefits of digital transformation initiatives and enterprise AI narratives throughout the region.

Germany leads the European market due to its strong industrial base, early enterprise digitalisation, and analytics applications in manufacturing and automotive sectors. Germany will continue to be a dominant force in the adoption of embedded analytics between 2025 and 2032 and there are rising investments in Industry 4.0 and increasing need for real time insights into operational action.

Key Players:

The major low-code embedded analytics market companies are  Microsoft Corporation, Salesforce Inc., Google LLC, Amazon Web Services, QlikTech International AB, Sisense Inc., TIBCO Software Inc., SAP SE, Oracle Corporation, Zoho Corporation Pvt. Ltd., Domo Inc., MicroStrategy Incorporated, Infor, GoodData Corporation, ThoughtSpot Inc., Logi Analytics, Looker Data Sciences LLC, Yellowfin International Pty Ltd, Appian Corporation, InsightSoftware, and others.

Recent Developments:

• April 2024: Microsoft introduced AI Copilot features in Power Fx, enabling natural language formula generation for low-code embedded analytics.

• March 2024: Sisense launched Compose SDK for Fusion to enable embedded analytics via code-first integration.

• March 2025: Appian launched version 25.1 with large-scale record handling for on-prem analytics