Posts

Showing posts with the label Data Management Books

How to Build an Effective Data Management Framework? | Tejasvi Addagada

Image
What is a Data Management Framework and Why is it Important? In today’s digital-first world, data is more valuable than ever. But just collecting it isn’t enough. What you do with data and how you manage, protect, and leverage it, defines your success. This is where a data management framework comes in. A data management framework is a structured approach that governs how data is collected, stored, processed, shared, and secured. It’s not just for IT teams; it’s a strategic tool that drives decision making across the entire business. I learned this firsthand while working with my current organization (HDFC Bank) struggling with scattered and siloed data. Once we implemented a unified framework, the transformation was immediate better decisions, improved collaboration, and fewer errors. How Can a Data Management Framework Improve Efficiency? A well-designed data management framework simplifies data handling by: Ensuring data consistency and accuracy Streamlining data access and reducin...

Generative AI and Data Quality: Essentials of Data Management- Tejasvi Addagada

Image
The rapid evolution of technology has brought new opportunities and challenges to managing data efficiently. Today, Generative AI and Data Quality play pivotal roles in shaping how businesses handle data. Combining the power of artificial intelligence with robust data management frameworks allows organizations to enhance data accuracy, streamline processes, and gain a competitive edge in a data-driven world. This blog explores the essentials of data management, the importance of data quality, and how generative AI is transforming the field. Generative AI and Data Quality Generative Artificial Intelligence (GenAI) is a subset of AI that uses algorithms to generate new content, such as text, images, or data, based on training data. In the realm of data quality, generative AI brings revolutionary potential. Businesses are now exploring its use in identifying and fixing data discrepancies, generating realistic datasets, and automating data management processes. Overview of Data Qua...