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Composable analytics is a revolutionary approach to data and analytics that is transforming the way organizations build and deploy custom analytics applications.
With composable analytics, businesses can quickly adapt to changing business needs by creating tailored analytics applications that integrate diverse data sources and technologies.
In this blog post, we will provide an introduction to composable analytics, highlighting its benefits and explaining how organizations can implement it.
Whether you are a data analyst, business intelligence professional, or IT professional, understanding composable analytics is essential for staying ahead in the rapidly evolving world of data and analytics. So let's dive in and explore the power of composable analytics!
Composable analytics represents a modular approach to data and analytics. This approach empowers users to assemble the necessary packaged data and analytics components to meet specific needs.
The essence of composable analytics lies in its adaptability. It allows organizations to tailor their analytics applications to specific needs- ensuring that the tools and processes in place are perfectly aligned with the unique challenges and objectives of the business.
This approach not only streamlines data processing but also facilitates a more agile response to changing business environments or requirements.
Gartner's 2023 Analytics & BI Platforms Magic Quadrant webinar, held on 13 September 2023, provided a comprehensive overview of the current trends and shifts in the analytics and business intelligence domain.
Among the various insights shared, the webinar conducted three pivotal polls, gathering responses from over 1,042 participants to gauge the most impactful trends shaping the choice of ABI platforms in the upcoming year.
The poll results painted a clear picture of the analytics landscape:
D&A Ecosystems took the lead, with 43% of the 301 respondents highlighting the importance of cloud portfolios, self-service analytics, governance, and cataloging.
Augmented Analytics, encompassing Generative AI, LLMs, NLQ, and automated insights, was the second most impactful trend, garnering 22% of the votes.
Data Science and its integration with ABI, termed as "worlds collide," secured 15%.
Decision Intelligence, focusing on decision-centric UI and frameworks, received 14%.
Lastly, Composable Data and Analytics, which includes headless BI, metrics store, and analytics as code, was identified as a key trend by 6% of the respondents.
While composable analytics might have secured a smaller percentage in the polls, its inclusion in the top five trends underscores its emerging significance in the data and analytics ecosystem.
The modular approach of composable analytics, as highlighted by Gartner, is gradually gaining traction, promising a more adaptive and efficient analytics experience for businesses.
Composable analytics offers a wide range of benefits that can revolutionize the way organizations approach data and analytics. Let's explore some of these key advantages.
Composable analytics offers increased flexibility and agility- allowing organizations to rapidly adapt to changing business needs.
It enables the creation of custom analytics applications tailored to specific requirements and supports quick adjustments as business needs evolve.
Composable analytics also facilitates the integration of diverse data sources and technologies and provide organizations with a comprehensive view of their data landscape.
With composable analytics, the data analysis process is streamlined- reducing the time and effort required to access, transform, and analyze data. It simplifies complex tasks such as data preparation and integration- saving time and enabling real-time and near real-time analytics for faster decision-making.
Composable analytics promotes collaboration among stakeholders involved in the data analysis process and facilitate knowledge sharing and providing a centralized platform for sharing and reusing analytics components and workflows.
It also ensures data governance and compliance through centralized control and monitoring capabilities- allowing organizations to establish standardized processes for data management.
In the realm of composable analytics, the narrative of a top commercial bank leveraging the Pandora metrics platform reflects a prime example of modular analytical architecture. By adopting Pandora, the bank transitioned into a self-service analytics paradigm, significantly reducing the end-to-end delivery time of business metrics to just 5 workdays. This efficiency was primarily due to the availability of 30 pre-defined metrics in Pandora's repository, alongside the flexibility to derive additional 15 metrics through simple transformations. This modular approach, akin to composable analytics, allowed the business intelligence engineers to focus solely on creating 5 new metrics, exemplifying how composable components can drive agility and expedite analytical delivery.
Implementing composable analytics requires careful planning and consideration. Here are some key strategies to successfully implement composable analytics in your organization.
Before implementing composable analytics, define specific business objectives. Identify areas where it provides value and align with your data and analytics strategy. Clear goals ensure focused implementation addressing specific business needs.
Choosing the right composable analytics platform is crucial. Evaluate platforms based on features, scalability, and integration capabilities. Consider compatibility with existing infrastructure and tools.
Look for a user-friendly interface, required data connectors, and advanced analytics capabilities that align with your business requirements.
Assemble a cross-functional team with expertise in data analysis, business intelligence, and IT. This team will be responsible for driving the implementation of composable analytics in your organization.
Provide training and support to help them acquire the necessary skills to build custom applications using composable analytics.
By following these implementation strategies, you can maximize the benefits of composable analytics in your organization.
Composable analytics is a rapidly evolving field, and its future holds exciting possibilities for organizations. Let's explore some key trends and advancements that we can expect to see in the future of composable analytics.
Automation and AI technologies will play a significant role in enhancing the capabilities of composable analytics. With AI-powered insights and recommendations, organizations can make more informed decisions based on real-time data analysis.
These advancements will enable businesses to extract valuable insights from their data faster and with greater accuracy.
Integrating blockchain ensures secure and transparent data sharing and collaboration- preserving data integrity and trustworthiness.
As organizations recognize the benefits, composable analytics adoption will grow. Businesses embrace it for advanced analytics and potentially gain a competitive edge.
Composable analytics platforms will evolve to enhance scalability, performance, ease of use, and integration. Standardization efforts and best practices will emerge for effective implementation.
Composable analytics offers powerful benefits for organizations. It enables rapid creation and deployment of custom analytics applications and allows businesses to adapt quickly. However, implementation requires careful planning for challenges like data integration and security.
Looking ahead, composable analytics has an exciting future. Advancements in automation and AI enhance capabilities, while integration with emerging technologies like IoT and blockchain provides real-time analytics and secure collaboration.
We can say that adoption of composable analytics will continue to grow and drive more innovation and maturity.