Connected Data Ecosystems in the Era of AI

Growth of Connected Ecosystems

Various industrial sectors have either already invested in or are rapidly increasing their focus on connected data ecosystems. According to a survey, an overwhelming 90% of respondents indicated plans to sustain or accelerate their investment in connected data ecosystems this year and the next.

Data is one of the most valuable assets for businesses today. However, without a connected data ecosystem, many organizations struggle to extract meaningful insights. This often happens because operational data is scattered across the organization, making it difficult to enrich with relevant third-party data sources. This ecosystem relies on a technology platform consisting of four broad components: applications that execute business processes within a company; data management infrastructure for processing and storing data; integration tools to aggregate data from various disparate and relevant sources; and analytics engines, which often include AI capabilities, to help derive meaningful insights from the data.
 

Advantages of Harnessing Connected Data Ecosystems!

The primary motivations for using a connected data ecosystem include enhancing business agility, streamlining process automation, improving systems integration, and expanding data-sharing with partners—often driven by environmental, social, and governance (ESG) considerations. For example, Deutsche Bank Research introduced dbDIG and a-DIG platforms, using Natural Language Processing and Artificial Intelligence to analyze ESG issues and company intangibles like human capital and innovation. Moreover, for traditional incumbents, connected data ecosystems present a valuable opportunity to enhance their influence and defend against disruption from agile digital challengers. For instance, BFSI companies risk losing up to half of their margins to fintech competitors but can potentially boost their margins by a comparable amount by taking on the role of ecosystem orchestrators.

A varied range of industries such as CPG & retail, media, energy, automotive, and telecom are looking to leverage connected data ecosystem supported by AI/ML models to enable usecases, including supply chain optimization, predictive maintenance and asset management, personalized content recommendations, autonomous vehicle development, network optimization and customer experience enhancements.

 

In each of these industries, a connected data ecosystem supported by AI offers significant potential to enhance operations, improve customer experience, and support innovation and sustainability. For example, Unilever has implemented Universal Data Lake, a centralized repository which supports 10-year data history to leverage machine learning and predictive modeling and facilitates the processing of data relevant to specific functions such as marketing and supply chain. Meanwhile, Enbridge is leveraging big data, machine learning, and predictive analytics through its PASA solution to optimize wind power performance and reduce maintenance costs, driving efficiency in renewable energy operations.

However, building and managing Connected Data Ecosystems comes with several technical, organizational, security, privacy and regulatory challenges. These challenges vary across industries but share common themes, such as data silos, privacy concerns, and integration complexities. For example, while automotive companies are facing issues around integrating new IoT systems with existing business operations such as ERP and MES, BFSI companies are grappling with data migration issues due to mismatched schemas, and operational inefficiencies slowing down the data consolidation process.Join us for this exclusive webinar on 20th February 2025 as we uncover how to harness the power of AI-driven data ecosystems for your industry. Understand how connected data ecosystems are evolving with advancements like multi-cloud environments, real-time analytics, and IoT. Discover the factors pushing businesses to adopt these ecosystems, including operational efficiency, improved customer experiences, and regulatory compliance.