Data Strategy

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

Tom Goodwin • Digital Darwinism: Survival of the Fittest in the Age of Business Disruption (Kogan Page Inspire)

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)

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

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)

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

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

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

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

Safeguarding sensitive information with Oracle's AI platform PII ...

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