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“The work [with Synaptiq] is unprecedented in its scale and potential impact,” Mortenson Center’s Managing Director Laura MacDonald MacDonald said. “It ties together our center’s strengths in impact evaluation and sensor deployment to generate evidence that informs development tools, policy, and practice.” 
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    A startup in digital health trained a risk model to open up a robust, precise, and scalable processing pipeline so providers could move faster, and patients could move with confidence after spinal surgery. 
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      Thwart errors, relieve in-take form exhaustion, and build a more accurate data picture for patients in chronic pain? Those who prefer the natural albeit comprehensive path to health and wellness said: sign me up. 
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        Using a dynamic machine vision solution for detecting plaques in the carotid artery and providing care teams with rapid answers, saves lives with early disease detection and monitoring. 
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          This global law firm needed to be fast, adaptive, and provide unrivaled client service under pressure, intelligent automation did just that plus it made time for what matters most: meaningful human interactions. 
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            Mushrooms, Goats, and Machine Learning: What do they all have in common? You may never know unless you get started exploring the fundamentals of Machine Learning with Dr. Tim Oates, Synaptiq's Chief Data Scientist. You can read and visualize his new book in Python, tinker with inputs, and practice machine learning techniques for free. 

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                  4 min read

                  AIQ: What Data Architecture & Governance Means for You

                  Featured Image
                  Synaptiq has spent the last decade studying data and artificial intelligence (AI) across a wide range of industries. We’ve consulted with clients, conferred with partners, collaborated with competitors, and conducted research to understand how and why organizations leverage these technologies.


                  Our ultimate takeaway?

                  AIQ: a novel approach to data and AI, centered on 11 key capabilities shown to facilitate successful workflow integration and return on investment (ROI).

                  This blog post will deep-dive into one of the 11 capabilities: Data Architecture & Governance. We’ll discuss what it is, how it’s done (when it’s done right), and why it matters. Or, you can read an overview of AIQ, including all 11 capabilities, in our blog post, AIQ™: What We Mean & What You Stand to Gain."


                  What is Data Architecture & Governance?

                  Imagine a vast chasm. On one side, there is data: electronic information, waiting to be given a purpose. On the other side, there are data uses: value-generating processes and products, including personalized marketing, predictive analytics, intelligent document processing, automated security, and many more. 

                  As a competitive organization, your objective is to bridge the gap between simply having data and actually generating value from that data. Several AIQ capabilities play a key role in this “bridging”; you can read more about them in our blogs on Data Engineering, Data Operations, and Data Product Management. However, Data Architecture & Governance has the most fundamental role to play:

                  • Data Governance is the framework of roles, standards, metrics, policies, etcetera that governs an organization’s use of data for value generation.

                  • Data Architecture outlines how data flows through the organization to inform the strategy for managing and governing data

                  Data Architecture and Data Governance are a packaged deal, one cannot work effectively without the other: hence their pairing into one capability.


                  Data Architecture & Governance Done Right

                  Data Governance & Architecture determines how an organization transforms its data into value⁠⁠—whether that value is revenue, improved workflow, or some other desired outcome. 

                  Consider a construction firm that has acquired data from a client for the purpose of improving an internal process. Data Governance includes data quality: “a measure of the condition of data based on factors such as accuracy, completeness, consistency, reliability and whether it's up to date.” It’s important to avoid using low-quality data for applications that require precision. Therefore, the construction firm ought to create standards for its client’s data to determine whether it has data quality issues that require remediation prior to internal use.

                  The construction firm should also account for data compliance: “the practice of following regulations set forth by corporate governance, industry organizations, and governments.” This will ensure that the construction firm doesn’t violate data privacy standards set by the client, the law, or other regulators. 

                  Finally, the construction firm must develop a Data Architecture to ensure that the abstract ideals it envisions from Data Governance (e.g., data quality and compliance) and Data Product Management are actually put into action. This includes understanding the underlying data entities (e.g., customers, products), which systems own specific entities (aka “Systems of Record”), and how that data should be transformed for use.

                  (How does Data Architecture become reality? Data Engineering).


                  Why Data Architecture & Governance Matters

                  Data Architecture & Governance defines and executes upon an organization’s practices and processes for its data (Governance) and the data relationships and transformations required to use it (Architecture). Without Data Architecture & Governance, organizations suffer from redundant, costly initiatives, islands of messy data, and frustrated internal staff and customers.

                  You can learn how Data Architecture & Governance fits into AIQ by reading our blog. Or, take our AIQ assessment to determine where your organization stands for each of the 11 capabilities.

                  Additional Reading:

                  Are 'Lionfish' Swimming in Your Digital Ecosystem? How Large Language Models Threaten Enterprise Security

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                  Transparency or Complexity: Understanding the Powers and Pitfalls of Black Box AI

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                  Whisking Words: Unlock the Power of LLMs for Your Business

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