We channeled our expertise into AIQ: an innovative framework for AI-ready data strategy and AI implementation, focusing on 11 critical capabilities proven to effectively enhance workflow integration and return on investment.
In this blog post, we'll explore in detail one of these 11 capabilities: Data Sourcing. For a broader understanding of AIQ, refer to our blog post titled "AIQ: What We Mean & What You Stand to Gain."
Data Sourcing is the mechanism by which an organization identifies, extracts, and integrates data.
Today, data powers many of the digital applications that we take for granted, from search engines to social media. Data also powers many processes used in industry — from marketing to manufacturing. Any organization reliant upon data that can't be collected internally must define and execute a strategy to acquire it from external sources.
The first step is to define a data asset strategy (DAS). DAS allows an organization to manage and develop its data as a business asset. It uses data to enhance decision-making, product development, and other business-orientated processes and applications. The second step is to implement data discovery (DD): the process of finding valuable open-source, public, or third-party data or metadata (labeling) services.
Once an organization has DAS and DD, it must collect data to continue increasing its data asset value. For third-party data, oftentimes, this means acquiring data through licensing, partnerships, and procurement — a task for “data hunters.” Data hunters identify and negotiate with potential data partners: third parties willing to provide data. They determine which data partners have the most valuable data and negotiate its acquisition.
An organization must know its objectives, what data it needs to advance those objectives, and with whom it's willing to partner to procure third-party data. Data hunters cannot work effectively without this information.
Ultimately, Data Sourcing done right is a well-oiled machine for seeking and acquiring data. An organization should constantly evolve its DAS, update its DD practices to reflect that evolution, and use data hunters to partner (or renegotiate partnerships) to acquire the best data for its dynamic objectives.
In recent decades, we’ve watched data-powered applications and processes transform the way we work and data-first businesses disrupt entire industries. Organizations have a vested interest in Data Sourcing: the mechanism that determines the strategy to wield a data asset, extract insights from it, and increase its value through the integration of external data. Those that lack this capability will ultimately be out-competed.
You can learn about Data Sourcing and how it fits into AIQ by reading our blog. Or, take our AIQ assessment to determine where your organization stands for each of the 11 capabilities.
Synaptiq is an AI and data science consultancy based in Portland, Oregon. We collaborate with our clients to develop human-centered products and solutions. We uphold a strong commitment to ethics and innovation.
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