Balancing DPDP Compliance and Fraud Detection in India
India’s Digital Personal Data Protection (DPDP) Act limits cross-border data flow, creating challenges for fraud detection systems that rely on global insights. This blog explores how enterprises can stay compliant without losing analytical strength through approaches like federated learning, hybrid frameworks, and governance-first design — showcasing how DAAS LABS helps balance compliance with intelligent fraud prevention.
At DAAS Labs, we believe technology has the power to solve the toughest enterprise problems and shape a smarter, better future. And today, we couldn’t be prouder to celebrate a milestone that’s close to our hearts. We’re sending a big, loud, and joyful congratulations to our partner and industry peer, SCIKIQ, for being named one […]
In today’s hyper-competitive landscape, data isn’t just an asset — it’s the foundation for innovation, agility, and AI-powered transformation. But while most companies recognize the need to become data-driven, few have the time or resources for 12–18 month implementation cycles and with AI intelligence being part of data platforms Deploying a Governed Data Platform in […]
In today’s AI-first world, enterprises are no longer asking if they should prepare for AI—but how fast they can. As generative models, autonomous agents, and predictive systems begin reshaping every industry, one thing is clear: the real differentiator isn’t the AI model—it’s the data platform that feeds it. Traditional data stacks—built for reports, not reasoning—are […]
Organizations often struggle with inconsistent reporting despite significant investments in analytics tools. This leads to conflicting data, delayed decisions, and a lack of trust in business intelligence. The core issue lies in a fragmented BI layer where different teams use different tools and definitions for key metrics.
To address this, leading companies are shifting from building isolated dashboards to creating unified data views through a central semantic layer. This layer standardizes KPIs and definitions across all BI platforms, ensuring everyone speaks the same data language. SCIKIQ offers an innovative solution to this problem, recognized by Forrester for its ability to unify multi-platform BI environments. It provides a common semantic layer, virtualized real-time access to distributed data, and end-to-end data lineage for complete transparency. This approach not only resolves reporting inconsistencies but also prepares organizations for AI-ready insights and trusted executive dashboards.
Explore how generative AI and the innovative Open Network for Digital Commerce (ONDC), is transforming its e-commerce landscape in India.
Introduction to data standardization in logistics and its importance in modern supply chain management Data standardization refers to the process of developing and implementing a set of rules and protocols for exchanging data between different systems or entities. In logistics, data standardization plays a critical role in modern supply chain management by ensuring that all […]
The Importance of Data Analytics in Retail Data analytics is becoming increasingly important in the retail industry, and for good reason. With the vast amounts of data available to retailers, it’s now possible to gain valuable insights into customer behaviour, preferences, and buying patterns. This information can be used to improve sales and marketing strategies, […]
The Importance of Data Analytics in Retail Data analytics is becoming increasingly important in the retail industry, and for good reason. With the vast amounts of data available to retailers, it’s now possible to gain valuable insights into customer behaviour, preferences, and buying patterns. This information can be used to improve sales and marketing strategies, […]