Credit: ipopba/istock In the digital economy, an organization may gain sustainable competitive advantage only if the business and technology decisions are forward-looking, accurate, and rapidly acted upon. Data and analytics play an important role in driving decisions and delivering enterprise value. As per IDC, worldwide big data and business analytics solutions revenue is expected to reach $274.3 billion by 2022. Additionally, IDC’s estimation of 175ZB of data worldwide by 2025, in comparison to 33ZB in 2018, highlights the rate at which the amount of accessible data is growing. Some organizations are already using a combination of Hadoop Data Lakes, AI-embedded analytics, and data governance solutions for data-driven intelligence. However, these individual solutions suffer from integration complexities, scalability, and availability problems and high operating costs. TCS’ AWS Enterprise Data Lake (EDL) for Advanced Analytics, launched in 2018, provides a comprehensive AWS cloud solution to address these point solution challenges. As per IDC, banking, discrete manufacturing, professional services, process manufacturing, and federal/ government are the top five industries investing heavily in big data and analytics. When combined, these five industries accounted for nearly half ($91.4 billion) of worldwide big data and analytics revenues in 2019. Retail’s strong growth (15.2% CAGR) will carry it into the top five by 2022. TCS EDL on AWS has an underlying architecture and solution framework that is industry agnostic and flexible to align well with specific business needs and technical requirements within every vertical. TCS EDL is the foundation for all data-driven decisions and analytics across an organization. Initially, EDL offered scalable, centralized datastores for collecting rapidly growing data across an organization with batch and real-time data pipelines, pre-built ML models for advanced analytics, customizable data visualization dashboards for 360–degree customer views, and metadata management for meeting governance requirements. EDL has continued to innovate and now offers self-service analytics, immersive experiences with Amazon Sumerian virtual assistants and chatbots, real-time sentiment analysis, and data protection regulatory compliance. Additionally, the TCS EDL architecture has been iterated to further leverage AWS cloud-native services to provide the strongest combination of platform features, functionality, and availability. Some of the key benefits of TCS’ AWS EDL for enterprises are highlighted below: Figure 1: TCS’ AWS Enterprise Data Lake – Benefits Some customer references include: Large American investment management firm: Business decisions suffered from lack of accurate insights due to data silos and unutilized data. Additionally, redundant IT and application infrastructure to store and process data silos resulted in high operating costs. Implementation of TCS EDL allowed this customer to have an integrated view of data from multiple departments and offered faster and accurate insights for better business decisions. Key benefits include self-provisioning, a cost-optimized centralized data store, and business ownership of an implemented “Analytics Gold Copy.” Leading provider of automotive financial services: This organization was looking for a solution to improve customer experiences and increase sales through real-time promotions and campaigns based on customer movement inside dealerships. TCS EDL framework implemented for IoT proximity analytics helped in analyzing customers’ behavior in real-time and launch targeted campaigns and promotions. Leading provider of fixed annuities: As a part of their cloud migration journey, this customer was looking for consolidating data ingestion, data processing, and data visualization tools. TCS AWS EDL for advanced analytics served as a single solution not only for data management but also for business analytics, IT reporting, and regulatory requirements. For more information on TCS EDL, please reach out to us at atu.marketing@tcs.com. 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