whyframeshot - stock.adobe.com
IBI on Thursday launched Data Intelligence, a new platform that integrates previously disparate data management processes to improve productivity and efficiency.
The suite includes application integration, data integration, data transformation, data quality, master data management and enterprise search. IBI previously offered many of those capabilities, but they were separate offerings and customers needed to integrate them on their own.
Features of Data Intelligence, meanwhile, include enabling users to automate complex data pipelines and discovering patterns and connections within an organization's data using AI and machine learning.
IBI -- formerly Information Builders -- is a unit of Cloud Software Group (CSG), which was formed after the merger between Citrix and Vista Equity Partners. IBI was acquired in 2020 by Tibco, now also a unit of CSG, and operated as part of Tibco until late 2022 when both were broken out as business units within the newly formed CSG.
Historically, Information Builders, which was an independent vendor from its founding in 1975 until its acquisition 45 years later, competed with vendors such as Cognos and Spotfire and later Tableau and Qlik. Now, also viewed as a data integration and management vendor, IBI's peers have expanded to include the likes of Alation and Informatica.
While IBI was part of Tibco, IBI's WebFocus analytics platform was updated to include a microservices architecture and natural language query capabilities.
Now, as its own unit within CSG, IBI is adding an integrated data management platform to its suite.
Data Intelligence is an AI-powered environment that centralizes IBI's previously separate data capabilities, which is a significant evolution according to Michael Moran, an analyst at Dresner Advisory Services.
When, for example, data ingestion, data integration and enterprise search capabilities are all separate from one another -- even if provided by the same vendor -- it's incumbent on an organization's IT department to integrate them on its own to create a cohesive data stack.
Otherwise, data gets isolated and is unable to be combined with other data to inform decisions.
The work to integrate separate tools, meanwhile, is both complex and labor-intensive.
But isolated data doesn't just hinder the productivity of data engineers and data scientists. It also hinders the self-service decision-making that leads to organizational agility. When data is lost or hidden with inaccessible systems, it's of no utility to end users making real-time decisions.
Therefore, vendors are now making their data management tools more cohesive. They're combining their tools in a single environment to make data more easily actionable and help data workers be more productive by freeing them from having to connect data tools as well as repeatedly make copies of data to combine it with data in other systems.
Michael MoranAnalyst, Drenser Advisory Services
However, despite its similarity to platforms from other vendors, Data Intelligence is nevertheless significant for IBI users. While it may not be unique, it will make a difference for IBI customers, according to Moran.
"Historically, capabilities such as data quality, data governance, master data management and metadata management developed within technology silos," Moran said. "The ability to address data governance on a more integrated basis … is increasingly contributing to competitive differentiation for those organizations that use data to support business decision-making."
In addition, Moran noted that most vendors do not offer fully integrated data management platforms. Users, as a result, frequently still have isolated systems.
"The distinguishing aspect is not how each component compares to IBI's competitors on a component-for-component basis, but rather how the integrated capabilities of the platform compare to what is [the] market status quo -- individual components that may or may not be integrated by end-user organizations," he said.
Among Data Intelligence's features are the following:
- A low-code centralized environment that uses AI and machine learning to make users more productive by discovering and surfacing patterns and connections as they orchestrate and automate data management workflows.
- Collaboration capabilities with the centralized environment.
- Data governance including data cleansing, data enrichment and user validation rules to help ensure data accuracy and consistency.
- A microservices architecture that enables users to deploy either on premises or in the cloud while providing users with choices related to how they construct their data management stack.
In addition, generative AI capabilities are infused throughout Data Intelligence, according to Vijay Raman, IBI's vice president of products and technology.
While traditional AI and machine learning augment data experts to make them more productive, generative AI enables users to use conversational language rather than code to work with data.
Similar to natural language processing tools that have been developed by other data management vendors over the past few months -- for example, Boomi and Dremio -- users can ask questions of their data using conversational language. They can also develop pipelines and undertake other complex tasks without having to write code.
"The whole goal of the AI is to be able to accomplish all of the data management tasks, such as creating data quality rules using natural language," Raman said. "We want to [enable users] to create models using natural language and then use the AI to match and merge to further enhance the value of the model."
Motivation for developing Data intelligence came largely from IBI customers, Raman continued.
He noted that the vendor both has a customer advisory council and does roadshows to get feedback from its users. Once it gets that feedback, IBI then meets with analysts and looks at market trends to confirm whether certain product development ideas are worth pursuing and goes forward from there.
"Customers drive a lot of how we have evolved," Raman said. "At the same time, we work … to validate that what our customers are asking for is what the market wants."
Data Intelligence is now in its first iteration, according to Raman. Like with any new suite of tools, the vendor already has plans to add new capabilities and improve those already included.
User experience was one of the primary focuses of the initial release, including a simple look and feel, Raman said. Future updates will make sure each of the components that makes up Data Intelligence have the same interface and usability.
More long term, IBI plans to make its data management and business intelligence platforms more harmonious, according to Raman.
"We have a large section of users on the analytics side and a large section of users on the data side," Raman said. "We think there is a unification that can happen. Our goal is to bring analytics use cases into [Data Intelligence], all the while augmenting them with artificial intelligence."
That combination of analytics and data management, meanwhile, is important, according to Moran.
He noted that IBI's initial effort should focus on marketing Data Intelligence so it can attract a significant user base.
Beyond that, however, as organizations look to develop large language models trained on their own data and generative AI technology continues to gain popularity, the convergence of data and AI governance will be key.
So, too, will cost control, as organizations execute more of their data operations in the cloud.
"The horizon for all the vendors competing in this space will be incorporating governance of AI/ML models as well as the data sets used to train the models," Moran said. "And as the scope of data governance expands and there is increased consumption of cloud-based compute, there should also a capability to monitor and manage costs associated with data governance activities."
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.