Data Architecture & Governance - AIQ Capability Overview
Data Governance is an overarching framework of processes, roles, policies, standards, and metrics that ensure the...
for the health of people
for the health of planet
for the health of business
FOR THE HEALTH OF PEOPLE: EQUITY
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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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DATA STRATEGY
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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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PREDICTIVE ANALYTICS
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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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MACHINE VISION
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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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INTELLIGENT AUTOMATION
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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. |
Start Chapter 1 Now ⇢ |
Data Governance is an overarching framework of processes, roles, policies, standards, and metrics that ensure the effective and efficient use of information, enabling an organization to achieve its data-driven goals while respecting compliance and privacy demands.
To coordinate internally, maintain data privacy, comply with regulatory needs, and take advantage of industry best practices and knowledge, companies need a forum for sharing knowledge about data and creating and enforcing standards. Once policies and standards are in place, they must be translated to technology. Data Architecture translates governance and business requirements to data schemas and technology designs.
Data architecture maps how data flows through its systems and provides a blueprint for managing data. The goal is to ensure that data is managed properly and meets business needs for information.
A system of record (SOR) is a data management term for an information storage system that is the authoritative data source for a given data element or piece of information.
An entity is any singular, identifiable and separate object(s). It refers to individuals, organizations, systems, bits of data or even distinct system components that are considered significant and used within your business systems.
Data transformation is the process of converting data from one format to another, typically from the format of a source system into the required format of a destination system.
Data governance requires (1) a policy framework designed by stakeholders to outline how data will be treated, (2) an actionable implementation plan defining tools and technology and assigning responsibility to data stakeholders and (3) commitment to ongoing assessment of policies & plan against business objectives.
Data governance requires collective effort for successful implementation. Buy-in and direction from the leaders of an organization is critical to ensure alignment with business objectives and strategy.
Data security refers to the process of protecting data from unauthorized access and data corruption throughout its lifecycle.
Data quality is a measure of the condition of data based on factors such as accuracy, completeness, consistency, reliability and timeliness.
Data privacy, sometimes also referred to as information privacy, is an area of data protection that concerns the proper handling of sensitive data including, notably, personal data but also other confidential data, such as certain financial data and intellectual property data.
Data Inventory is a comprehensive catalog of data assets held by an organization; which should include information on elements that can uniquely identify an individual (person) or other sensitive data.
GDPR and CCPA have regulations that provide data subjects an ability to control how their data is used, including requesting a complete erasure of their data. Companies that handle personal data must have procedures in-place to handle these types of requests.
Data Governance is an overarching framework of processes, roles, policies, standards, and metrics that ensure the...