Emerging Embedded Analytics Trends You Must Watch Out in 2023

Rahul Pattamatta

Rahul serves as the CEO and Co-Founder of Databrain, a platform that enables startups to develop customer-facing analytics features within minutes than months.


Emerging Embedded Analytics Trends You Must Watch Out in 2023

Rahul Pattamatta

Rahul serves as the CEO and Co-Founder of Databrain, a platform that enables startups to develop customer-facing analytics features within minutes than months.

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Embedded Analytics (EA) is a powerful tool that directly integrates data visualization, business intelligence, and reporting capabilities into business applications. 

Embedded analytics optimizes productivity and streamlines decision-making processes by allowing users to access analytics within their usual workflows. According to MarketsandMarkets, the global embedded analytics market is set to experience exponential growth from $52.6 billion in 2021 to $77.1 billion by 2026. This highlights the surging demand and significance of embedded analytics in various industries. 

As businesses increasingly adopt a data-centric approach, the transformative potential of embedded analytics is becoming apparent. Its ability to provide immediate, contextual insights enables rapid, informed decision-making—a critical capacity in an era overwhelmed by data. Efficient extraction, analysis, and interpretation of these valuable insights have thus become an indispensable part of business operations.

Recognizing the ever-growing significance of embedded analytics, this blog post delves into the top five trends currently shaping this field. These trends are gaining momentum within the tech community and promise to redefine the future of business intelligence. By driving innovation and establishing new benchmarks for data-driven decision-making, they are poised to have a considerable impact on how businesses leverage data in the future.

Top Embedded Analytics Trends to Keep an eye out for

With technology progressing at an unprecedented pace, embedded analytics continuously evolves and adapts to meet changing needs and demands. Several trends in the embedded analytics landscape are destined to redefine how businesses leverage analytics for strategic growth. These trends include:

  • Advancements in AI and machine learning
  • Personalization of analytics tools
  • Natural Language Processing (NLP)
  • the mobile-first approach
  • The shift towards cloud-based embedded analytics solutions

AI and Machine Learning in Embedded Analytics

Artificial Intelligence (AI) and machine learning have been at the forefront of technological innovation, and their integration with embedded analytics is revolutionary. AI-powered embedded analytics platforms are equipped to automatically identify patterns and trends in vast data sets, predict future outcomes, and offer actionable insights. 

Gartner predicts that by 2025, 75% of all data analytics will be automatically generated using AI, significantly reducing manual effort and enhancing accuracy and speed. This transformation enables businesses to maintain a competitive edge by rapidly responding to market trends and making data-driven decisions.

Personalization in Analytics Tools

The growing personalization trend in analytics tools signifies a notable shift towards creating user-centric experiences. As per a Forrester report, personalization will be a top priority for 36% of marketers in the coming years. 

Businesses increasingly demand analytics tools that cater to their unique needs and preferences, driving providers to focus on offering personalized dashboards, customizable reporting templates, and intuitive user interfaces. By making analytics tools more user-friendly and customized, user engagement gets enhanced, and a higher return on investment is achieved.

Natural Language Processing (NLP) in Analytics

The integration of NLP in embedded analytics symbolizes the democratization of data. NLP enables users to interact with the system using everyday language, making complex data analysis accessible to non-technical users. 

As per an Analytics Insight survey, nearly 80% of firms identify NLP as a critical feature for data exploration. This increased accessibility empowers all employees to make data-driven decisions, irrespective of their technical expertise, fostering a truly data-driven organizational culture.

Mobile-First Approach in Embedded Analytics

In today's digital age, the mobile-first approach has become an industry standard across technology sectors, and embedded analytics is no exception. IDC predicts that by 2022, 70% of all enterprise software interactions will occur on mobile devices. 

Accessing data and insights anytime, anywhere, offers unmatched flexibility and efficiency. Mobile-first embedded analytics allows users to access real-time data, empowering them to make immediate decisions and respond rapidly to evolving business environments.

Cloud-Based Embedded Analytics

Cloud-based solutions have transformed various technology domains, including embedded analytics. Cloud-based embedded analytics platforms offer numerous benefits, such as scalability, flexibility, cost-efficiency, and ease of access. 

As per a study by Cisco, 94% of workloads will be processed by cloud data centers by 2021. Organizations can scale their analytics capabilities as their business grows, eliminating infrastructure costs and complexities associated with on-premise solutions. Moreover, cloud-based solutions facilitate real-time analytics, empowering businesses to make timely, data-driven decisions.

Cybersecurity Concerns in Embedded Analytics

As data analytics continue to rise, so do the associated cybersecurity risks. A report from Cybersecurity Ventures predicts cybercrime damages will cost the world $6 trillion annually by 2021. 

Given the sensitive nature of the analyzed data, security is a critical concern in embedded analytics. Organizations invest heavily in robust security measures such as advanced encryption techniques, multi-factor authentication, and stringent access control to protect their data and analytics. Cybersecurity concerns will only magnify as embedded analytics becomes more integrated within business processes, underscoring the need for advanced, resilient security measures.

The Future of Embedded Analytics

The future of embedded analytics holds limitless potential, with expectations for embedded analytics platforms to become even more pervasive, intelligent, and integrated. McKinsey forecasts that the convergence of embedded analytics with emerging technologies such as the Internet of Things (IoT) and edge computing could have an economic impact of $3.9 trillion to $11.1 trillion annually by 2025. Real-time analytics on data collected by IoT devices can significantly enhance decision-making capabilities in industries like manufacturing and logistics, revolutionizing these sectors.

After exploring the vast landscape of embedded analytics and its emerging trends, it becomes evident that these advancements are reshaping business intelligence. The essence of these trends lies in the customer. Their needs, preferences, and challenges drive the evolution of embedded analytics.

Embedded analytics is a powerful transformative force, promising an exciting future where data-driven insights are effortlessly integrated into business operations. Amidst the multitude of solutions available in the market, Databrain distinguishes itself as a leader in the field of embedded analytics. 

With state-of-the-art features like AI-powered insights, NLP capabilities, personalized dashboards, mobile-first design, and robust security measures, Databrain delivers an unparalleled solution for businesses eager to harness the power of data for informed decision-making. By staying informed about these trends and understanding their potential, businesses can enhance their decision-making processes and maintain a competitive edge in the market with the help of solutions like Databrain.

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