Data Strategy

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)

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

The cornerstone of a successful RAG implementation is the quality of your data

DataStax • Retrieval Augmented Generation (RAG) Explained: Understanding Key Concepts

Yet many of us who have tried to use data to inform decisions in organizations have experienced a different reality. One where we are constantly confused by how metrics are defined, bicker over how to interpret various analyses, and struggle to apply the insights into action.

Julie Zhuo • The Data-Informed Manifesto

How_to_Enable_Self-S_748717_ndx

The research outlines best practices for enabling self-service analytics, emphasizing alignment with business goals, collaborative development between IT and business, and lightweight management for effective data and analytics success.

Link

How to Enable Self-Service Analytics to Ensure D&A Success

Quality data is crucial for automation, pattern recognition, and training AI for advanced capabilities. A data-first mindset and a data-focused platform are essential for long-term success

oracle.com • Generative AI Changes Everything for the CFO and Finance

Data quality management ensures data is fit for consumption and meets the needs of data consumers. To be of high quality, data must be consistent and unambiguous. You can measure data quality through dimensions including accuracy, completeness, consistency, integrity, reasonability, timelines, uniqueness, validity, and accessibility.

Astasia Myers • 4 Data Trends to Watch in 2020

In today’s data world, there are so many options for an EL tool to avoid you developing your own extracting script and to help you gain a LOT of time.

Fivetran, Mage, and Airbyte to mention a few.

You don’t have to maintain custom scripts, these tools come with +300 connectors, basic scheduling, and error handling.

Jeremy • What I Learned After One Year of Building a Data Platform From Scratch

The starting point of any RAG system is its source data, often consisting of a vast corpus of text documents, websites, or databases