Data: The Most Valuable Commodity of the Digital Age

Introduction

In the digital age, data is often regarded as the most valuable commodity, akin to oil in the previous century. However, like oil, data requires refining to unlock its full potential. This article explores the concept of reusable data, emphasizing its importance in driving analytics and artificial intelligence (AI) applications. Reusable data is characterized by its consistency, self-explanatory nature, and ease of access, aligning with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. The article outlines a step-by-step approach to making data reusable, including identifying data silos, transferring data to a unified storage location, harmonizing data structures, and ensuring data integrity. By adopting these practices, organizations can transform raw data into valuable assets that fuel innovation and strategic insights.

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Data: The Most Valuable Commodity of the Digital Age
In today's digital era, data is often considered the most valuable commodity. Treating it well is crucial for any business. This post will guide you on how to make your data reusable and how SciY can help transform your business.

Data as “the New Oil”
Data has been aptly compared to oil, the commodity that dominated the last century's economy. Like oil, data needs refining to be truly useful. This process transforms raw information into refined assets with practical applications. Reusable data fuels analytics tools and AI algorithms, leading to faster product creation and providing organizations with unique strategic insights. But what does refined data look like, and how do you achieve it?

Characteristics of Reusable Data

Reusable data has several key characteristics:

Consistency: It is structured in a consistent way, making it easy to use in visualizations or statistical analyses.
Self-Explanatory: It is understandable without needing explanations from its creators.
Findability: It is easy to locate and use, even years after its creation.

These attributes align with the FAIR guiding principles, which outline what makes data reusable. Since these guidelines were published in 2016, organizations handling scientific data have been updating their management strategies to meet current industry demands. The consensus is that achieving reusable data requires an effective ecosystem of tools.

Steps to Make Your Data Reusable
A core component of this ecosystem is a data repository that keeps data standardized and accessible. Here are the steps to make your data reusable:

Identify Data Silos
Locate where your data is currently stored. Different departments may have unique storage locations. The goal is to eliminate these data silos and create a unified data layer. If immediate restructuring isn't possible, replicate the silo content in the new data layer.
Transfer Data to the New Location
Move your data from existing silos to the new storage location. Choose between cloud storage, local storage, or a hybrid solution based on your organization's needs. Consider data safety and scalability. SciY ZONTAL Data Platform supports cloud, on-premise, or hybrid deployment options. Once transferred, remove redundant data silos.
Harmonize Data
Update the data structure to follow a consistent pattern that enables reuse. Preserve different types of information and store metadata for additional context. This process should produce self-reporting data assets, making the data interpretable without additional help. Harmonization also makes data interoperable between systems.
Ensure Data Integrity
Verify data integrity to ensure high quality. This involves data clean-up and cross-checking against existing standards. Ensure that metadata uses consistent vocabulary throughout the organization. Our Platform integrates with external systems like Accurids for this purpose.

Next Steps
Making data reusable may seem daunting, but the SciY team is ready to support your efforts. We offer life science data analytics tools to support your digital laboratory. While initial transformation provides benefits, a holistic approach that includes systems and processes will lead to lasting improvements. We can help you enhance your effectiveness and gain an advantage in data reusability. More importantly, we will guide you in developing robust data management principles to prepare for an increasingly digital future.