Sisense on Thursday unveiled Compose SDK for Fusion, a code-first set of application programming interfaces that enable developers to quickly and simply build analytics tools to embed within the workflows of business users.
Now in public preview, Compose SDK for Fusion is a toolkit that enables trained developers to tailor data products with a composable approach to development.
Developers can pick and choose from more than 500 APIs, data libraries and prebuilt visualizations to assemble data products. The approach, which essentially provides developers with building blocks they can piece together however they like before embedding the finished product, saves time and effort compared with coding starting from the beginning, while at the same time enabling customization.
Based in New York, Sisense specializes in embedded analytics and in 2021 renamed its platform Sisense Fusion to reflect that focus. Other embedded analytics specialists include Logi Analytics, which is now part of Insightsoftware, and Domo.
More recently, in January Sisense was among the first to integrate with OpenAI after the generative AI developer released ChatGPT in November 2022. The move marked the beginning of generative AI becoming the product development focus of most data management and analytics vendors.
In April, Amir Orad stepped down as CEO after eight years at Sisense and Ariel Katz, who had been the vendor's chief products and technology officer, was named his replacement. Shortly after, in July, Sisense reportedly laid off about 15% of its workforce.
A code-first approach
Generative AI has led to a new wave of natural language processing (NLP) tools, including features that enable users to query data and receive responses without writing code and capabilities that translate text to code to enable development. Compose SDK for Fusion, however, is a code-first toolkit.
Sisense offers low-code/no-code tools including NLP capabilities. But the code-first approach enables more complex development, according to David Menninger, an analyst at Ventana Research.
Low-code/no-code tools can enable data exploration and analysis and rudimentary application and data pipeline development. But deep development operations (DevOps) that enable organizations to continuously integrate and continuously deliver (CI/CD) data to keep applications up to date requires code, he noted.
David MenningerAnalyst, Ventana Research
"The code-first approach supports organizations' DevOps processes," Menninger said. "DevOps includes continuous integration and continuous delivery -- or continuous deployment. CI/CD is based around source code control systems so it's difficult or impossible to support CI/CD with no-code tools."
Ayala Michelson, Sisense's recently appointed chief products and technology officer, likewise said that a code-first approach provides greater control over development.
She noted that some users prefer low-code and no-code capabilities that enable them to build applications in an hour or two, populate them with some existing reports and dashboards and get them up and running.
Others, however, want something more.
"We want to cater to the other side of the spectrum, where users want to build more sophisticated, intelligent analytics applications that aren't bound to a dashboard or rigid [data product]," Michelson said. "They want to have analytics insights imbedded deep in the application or business workflow. This is where Compose SDK comes into play."
She added that Compose SDK for Fusion marks an expansion of Sisense's target audience to include hard-core developers.
Sisense's existing capabilities let customers build applications with low-code and no-code tools. But as organizations recognize the benefits of a composable approach to development -- Gartner predicts that by 2025, 60% of custom business applications will be built with components -- Sisense also aims to serve the needs of those building advanced analytics applications.
"Compose SDK is essentially … a developer-first approach because we're looking at how applications are going to be built [in the future]," Michelson said. "Compose SDK allows deeper customization and can deliver micro-analytics in ways we couldn't before."
Menninger, meanwhile, said Sisense is wise to expand its target audience to include developers.
He noted that Ventana's research shows that nearly two-thirds of organizations consider embedded analytics important, which rates even higher than AI and machine learning.
By targeting developers -- and offering more than 500 different components to choose from -- Sisense is enabling organizations to build advanced data products that can be embedded into business users' workflows. The products can then be continually managed and updated without bringing them back to the development environment.
Domo likewise recently added what it termed pro-code tools to its analytics platform to expand its target audience beyond self-service users and enable more sophisticated application development. Meanwhile, GoodData similarly has taken a composable approach to development.
"Compose SDK turns analytics on its head targeting the developer as the primary persona rather than a secondary persona," Menninger said. "Compose provides more granular objects, making it easier to embed them into other applications."
With Compose SDK for Fusion now in public preview, Sisense's next product development plans include launching new generative AI capabilities including improved natural language query and generation capabilities, according to Michelson.
In addition, she noted that Sisense already enables customers to integrate their own language models with the vendor's capabilities.
Meanwhile, developers will continue to be a focus for Sisense. The company's roadmap includes more code-first tools, in addition to the low-code and no-code capabilities enabled by generative AI, according to Michelson.
"We will continue investing in our stack of no-code, low-code and pro-code capabilities to cater to the full set of requirements and needs to build and embed analytics and data products," she said. "We will continue with pro-code investment to help teams build advanced analytics."
Menninger said one area Sisense needs improvement is in enabling collaboration.
Business decisions are rarely made by just one person. Therefore, the more analytics tools enable users to work together throughout the decision making process, the better. As a result, numerous vendors including Domo, Knime, Qlik and Tableau and have added capabilities that enable users to share analysis and collectively reach insights.
"Sisense has a feature-rich platform," Menninger said. "But one area where they could make more investment is in the area of collaboration, with more support for the decision-making activities that happen in association with analytics."
Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.