Shubho's Blog

In today’s rapidly evolving tech landscape, data strategy is the cornerstone of business strategy. As organizations gather an ever-increasing amount of data, the need for efficient data management strategies becomes paramount.  Two prominent approaches that have gained traction in recent times are Data Mesh and Data Fabric . Both concepts aim to address the same very goal of Data Democratization while ensuring scalability, accessibility, and usability. In this blog, we’ll delve into the nuances of Data Mesh and Data Fabric, and provide recommendations for organizations seeking to fortify their data landscape. Data Mesh vs Data Fabric: Unpacking the Concepts Data Mesh is a domain-driven architectural approach to data management. It proposes treating data as a product and recommends a decentralized approach to data ownership with domain experts. Earlier, the Enterprise Data Lake approach focused on centralized data management and ownership whereas the Data Mesh architecture fo...

Do you know the world produces more bytes of data every hour than the grains of sand on this earth? Yes, just imagine how far we have come in the last decades. Over the last decades, the priorities for enterprises have changed; First, it was all about driving digital transformation. Now, it is all about data. At scale… At speed… In the age of digital transformation, cloud, and SaaS, data collection has become seamless. According to a  study published by IDC  in May 2022, the amount of new data created, captured, replicated, and consumed is expected to double in size by 2026. While this has unleashed new opportunities for businesses to create data-driven business strategies and improved efficiencies, it has also posed unprecedented challenges for data and security leaders.  Data is the most valuable asset for any business and the focus is on how to protect the data. Compliance with an increasing number of regulations can be daunting, failing which can be detrimental. As yo...

The emergence of Generative AI (GenAI) with Large Language Models (LLM) has unlocked promises of revolutionary possibilities driving newer business opportunities and customer experiences. It is not surprising that leading technology innovators like Microsoft, Google, Meta, NVIDIA, IBM, Databricks, Snowflake, and many others are investing heavily in LLMs to create business value for the next decade. If GenAI delivers in line with the early signs then the scale of economic impact will be huge.  McKinsey Global Institute estimates that generative AI will add between $2.6 and $4.4 trillion in annual value to the global economy, increasing the economic impact of Artificial Intelligence as a whole by 15% to 40% . In this article, I will focus on the implications of GenAI on data security, privacy, and governance, and discuss how organizations can adapt to ensure a secure and responsible future. Implications of GenAI on data security Data is critical to every business and it makes each en...

In my previous blog, I talked about what software supply chain attack is all about. It occurs when a threat actor infiltrates a network and employs malicious code in the software before the publisher sends it to their customers and then it compromises the customer’s systems. Such attacks affect all users of the compromised software and can have widespread consequences for organizations and their infrastructure and data. Traditionally, organizations developed applications in-house and this enabled developers to gain control over the entire codebase. However, this model cannot meet today’s time-to-market demands. As the expectations and pace increase, it’s impossible to meet the demand with home grown software. So, there is a need for open source software contributed by software professionals around the world. Open source software facilitates rapid development and release cycles. It enables developers to incorporate ready-made components into their application so they can quickly release...