Author: Admin

Customer-facing platforms are essential for modern businesses. From e-commerce sites to data portals, these platforms handle sensitive information, including personal data, payment details, and account credentials. Protecting this data is critical, as breaches can damage trust, lead to regulatory penalties, and result in financial losses. A clear approach to cybersecurity ensures both the business and its customers remain safe.Implement Strong AuthenticationAuthentication is the first line of defense. Multi-factor authentication adds a critical layer of protection by requiring additional verification beyond a password. Biometrics, authentication apps, and one-time codes significantly reduce the risk of unauthorized access. Password policies that enforce complexity…

If you’ve been anywhere near a data team, you already know the existential crisis happening right now. Here are just a few questions data leaders and our partners have shared with us:Why does data governance still feel like a slog?Can AI fix it, or is it making things worse?How do we move from governance as a roadblock to governance as an enabler?These were the big questions tackled in this year’s Great Data Debate, where a powerhouse panel of data and AI leaders dove deep into dove deep into how governance needs to evolve.Meet the Experts This discussion brought together industry leaders…

If you’re learning LangGraph or exploring more about it then it’s nice to know about the pre-built node-level caching in LangGraph. Caching not only eliminates unnecessary computation but also fastens the latency. We’ll be looking at the implementation of the same in the article.  It’s assumed that you have an idea about agents and nodes in LangGraph as we won’t be focusing on that side of the story, so without any further ado let’s walk into the concepts and implementation.  What is Caching? Caching stores data in temporary storage so the system can retrieve it quickly. In the context of…

Key Takeaways Modern AI empowers regulated organizations to communicate faster and smarter while staying fully compliant. Use cases like discovering content, ensuring the right tone, handling conversations efficiently, and delivering accessibly shows how AI drives measurable impact. EngageOne software helps leaders adopt AI safely to improve speed, accuracy, and customer engagement without compromising compliance or introducing operational risk. The Pressure to Modernize Without Losing Control In regulated industries such as financial services, insurance, and utilities, leaders face a constant balancing act. They must deliver fast, personalized customer experiences while maintaining compliance and consistency. Legacy systems, disconnected content libraries, and manual…

Sovereignty has mattered since the invention of the nation state—defined by borders, laws, and taxes that apply within and without. While many have tried to define it, the core idea remains: nations or jurisdictions seek to stay in control, usually to the benefit of those within their borders. Digital sovereignty is a relatively new concept, also difficult to define but straightforward to understand. Data and applications don’t understand borders unless they are specified in policy terms, as coded into the infrastructure. The World Wide Web had no such restrictions at its inception. Communitarian groups such as the Electronic Frontier Foundation,…

Today, AWS announced that Amazon Kinesis Data Streams now supports record sizes up to 10MiB – a tenfold increase from the previous limit. With this launch, you can now publish intermittent larger data payloads on your data streams while continuing to use existing Kinesis Data Streams APIs in your applications without additional effort. This launch is accompanied by a 2x increase in the maximum PutRecords request size from 5MiB to 10MiB, simplifying data pipelines and reducing operational overhead for IoT analytics, change data capture, and generative AI workloads. In this post, we explore Amazon Kinesis Data Streams large record support,…

What is Business Intelligence?As organizations collect more and more data, they need a process that turns raw data into meaningful strategies and operations. Business Intelligence (BI) refers to the set of infrastructure, tools, applications and best practices that organizations leverage to help them drive their strategic decision-making. While traditional BI has focused on collecting, integrating and analyzing historical data to support better decision‑making, modern BI increasingly incorporates advanced business analytics, including predictive insights, to help organizations drive growth.The term “business intelligence” can encompass a combination of data warehousing, business analytics, data visualization and reporting tools. However, the BI lifecycle begins…

Something that we like writing about on Smart Data Collective is how data analytics is reshaping the payment processes in e-commerce, offering new levels of insight, control and responsiveness. You will find in this blog post a detailed look at how analytics are applied in payments, you will see emerging trends, and you will understand key statistics that highlight the scale of change.You, as a stakeholder in e-commerce payments, are increasingly confronted with a business environment where the market for big‐data solutions is growing rapidly: a report by Markets.us states that the market for Big Data in e-commerce was valued…

Revel in the glory I imagine that many developers today don’t properly appreciate the glory that is REST/JSON because it is such an elegant and beautiful solution. In 2000, it was Roy Fielding who had a “light bulb over the head” moment and saw the connection between standard CRUD operations and the GET, POST, PUT, and DELETE verbs of the HTTP protocol. His lovely insight opened our eyes to the notion that the web was more than a platform for serving documents. The web was, in and of itself, a giant computing platform. Just like that, all of the marshalling and crazy…

AI’s next breakthrough won’t come from bigger models—it’ll come from better infrastructure. As enterprises move from experimentation to execution, they’re realizing that scalable, secure, and connected systems are what make AI real. The race is no longer just about data science; it’s about the infrastructure that lets intelligence run anywhere. At NVIDIA GTC in Washington, D.C., this week, Cisco shared how we’re advancing Cisco Secure AI Factory with NVIDIA—the enterprise foundation for AI that runs securely, observably, and at scale. The momentum spans four pillars: security, observability, core AI infrastructure, and ecosystem partnerships. We’ll focus here on core AI infrastructure—the…