Glossary term

Composable Analytics

In times of macroeconomic uncertainty and amidst the fallout of a global pandemic, businesses are realizing the true value of operational agility. Having multi-functional tools that can adapt to unexpected circumstances and provide stability during turbulent times are no longer a luxury—they’re a necessity. 

In data science, composable analytics in particular can help organizations reach peak agility. 

What are Composable Analytics? 

Composable analytics are more than a specific set of tools, but instead the use of many modular data analytics tools in conjunction with one another. Composable analytics integrates all analytics capabilities from across the business and enables them to communicate and collaborate with each other for faster, more intelligent insights. 

Successfully implementing composable analytics techniques provides an adaptable, end-to-end data pipeline, from storage and distribution to analysis and presentation. This pipeline is accessible to all members of the organization and can act as the foundation of a data-driven enterprise.  

By leveraging components of many smaller analytics assets and integrating them into one seamless machine that multiple departments can access, composable analytics can democratize data analytics, accelerate workflows, and drive value across the organization.  

The Advantages of Composable Analytics 

Composable analytics offers businesses many benefits, including: 


The greatest attraction of composable analytics is its flexibility and adaptability. By design, composable techniques are modular and interchangeable, meaning previous assets are constantly reused and repurposed to create new solutions. This feature allows an unparalleled level of efficiency and adaptability and allows composable analytics solutions to be easily tailored to address any specific request or requirements. 


For maximum impact, composable platforms are built on low- or no-code programming alternatives. This comes with many benefits, principally, ensuring all personas within an enterprise have equal access and understanding of the solution.  

By democratizing your business’s data analytics tools and building a composable platform off of a no-code alternative, you provide an environment where stakeholders with any level of data science experience can contribute and generate value. In addition, domain experts can directly and efficiently combine their specialized knowledge with high level data analysis to generate actionable insights.  

By allowing all members of the organization to contribute and benefit, the composable platform can continually grow and develop.  


Building a composable analytics platform on a visual and intuitive interface lends itself to collaboration between individuals and teams within an organization. 

Solutions can be shared between teams, copied, adjusted, and repurposed to serve new initiatives and generate insights. When all members of an organization understand the interface, regardless of their coding ability, it’s easy for them to build on top of one another’s work and continue advancing the organization’s products and services.   


As they excel in flexibility and explainability, composable analytics are an obvious fit for businesses aiming to implement scalable AI solutions that can grow alongside them. As it gains more traction within an organization, a modular data system grows with each use, providing more resources, pre-built workflows, and past examples to new users. As the business develops, more data sources can be added, new tools can be integrated, and more members can make use of the platform’s extensive library of analytical capabilities.  

Composable Analytics in Action 

Say an organization has just hired a new member for their sales enablement team. How can they utilize their business’s composable analytics platform? 

Being a new employee at a growing business can be intimidating, and learning to use a company’s BI tools can be difficult. By introducing new employees, regardless of their role, to composable analytics tools on day one, organizations empower everyone to use data to their advantage from the get-go.

Nearly all composable analytics solutions make setting up a data catalog fast and easy. Assuming proper access is set up in advance of their state date, this new sales enablement employee, for example, would have complete visibility into all data that’s relevant for their role. They could easily search through the catalog, pull data that meets new project requirements, or request access to data that other teams and functions might have ownership of. During the onboarding period, a data catalog provides a great foundation and understanding of what data each employee has at their disposal.

Say this sales enablement team member was given the task of helping a sales rep improve an existing customer relationship. This is a fairly common scenario, and it’s likely another team member might have already used the org’s composable analytics solution to build a machine learning model and conduct an analysis of it.

As composable analytics are so flexible, it can be as simple as cloning the project, adjusting the necessary variables, making any final tweaks, and running the updated model. There’s no need to waste time and effort building new models from scratch.  

Lastly, when it comes to presenting their findings to colleagues and managers, composable analytics can integrate with existing BI tools and feed a model’s results directly into data visualization software. They can interpret and make modifications to the suggested visualization. The sales enablement employee could have a Tableau dashboard to present to the wider team during their first week on the job.

In the end, composable analytics saves time and resources at every step of the data pipeline, from sourcing to presentation. With just a little training and experience, employees at all levels will be leveraging AI and machine learning to generate valuable business insights. 

Wrapping Up 

In preparation for macroeconomic headwinds, put your business’s best foot forward and adapt to the data-driven world. Composable analytics offers your organization unparalleled levels of operational agility, collaboration, and efficiency. 

People are the backbone of any data-driven organization and preparing them for digital transformation can be challenging.

To learn more about upskilling your workforce, take a look at our blog about how data science upskilling can transform your teams. 

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