Data Strategy
The cornerstone of a successful RAG implementation is the quality of your data
DataStax • Retrieval Augmented Generation (RAG) Explained: Understanding Key Concepts
Also, eliminating irrelevant or sensitive information such as personally identifiable information (PII) is crucial to align with privacy standards
DataStax • Retrieval Augmented Generation (RAG) Explained: Understanding Key Concepts
This brings us to our third point: Because data only has meaning within a particular context, consumers of data and information need metadata to help them decide how to use it. This is an important difference between data and other assets. You don’t need much metadata when deciding whether to spend a $20 bill, but you do need metadata when trying t... See more
Larry Burns • The Currency of Information: What Kind of Asset Is Data? (Part Two)
The purpose of metadata is not simply to describe data and information assets, but rather to proactively answer questions that consumers might have about them. Where did this data come from? How up to date is it? How trustworthy is it? What business process(es) created it? What business process(es) use it? What transformations or filtering have bee... See more
Larry Burns • The Currency of Information: Managing Data as an Asset (Part Three)
One of the problems with owning your own data is that it ignores the question of what format that data is in. Data formats are sometimes considered carefully, but they can also be hammered out fast to get a minimum viable product out the door.
Byrne Hobart • The Promise and Paradox of Decentralization
Meta-data management efforts provide for the management and traceability of all components of the BI environment. Meta-data needs range from ensuring that definitions and business rules associated with BI applications are made available to business users to providing source data mapping information to manage the environment or answer questions rega
... See moreSteve Williams • The Profit Impact of Business Intelligence
The amount of data we now access has grown far faster than the general level of data literacy in companies. Most companies have too much data, it’s stored in too many places, it’s not ‘clean’ and it’s often more confusing than helpful when it comes to what matters – making decisions with it. We need to ensure companies create centralized yet custom
... See moreTom Goodwin • Digital Darwinism: Survival of the Fittest in the Age of Business Disruption (Kogan Page Inspire)
The starting point of any RAG system is its source data, often consisting of a vast corpus of text documents, websites, or databases
DataStax • Retrieval Augmented Generation (RAG) Explained: Understanding Key Concepts
Data is always an abstraction of reality based on underlying assumptions as to how to categorize the unstructured phenomena of the real world.