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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. 

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            How Should My Company Prioritize AIQ™ Capabilities?

             

               

               

               

              Start With Your AIQ Score

                4 min read

                AIQ: What Business Intelligence Means for You

                Featured Image

                Photo by Chris Lee on Unsplash

                Synaptiq has spent the last decade studying data strategy and AI readiness across sectors and industries. We’ve consulted with clients, conferred with partners, collaborated with competitors, and conducted research to understand how and why organizations fail or succeed in their data and AI endeavors.

                 

                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: Business Intelligence. For a broader understanding of AIQ, refer to our blog post titled "AIQ: What We Mean & What You Stand to Gain."

                Business Intelligence

                Every organization collects data in one form or another, but using that data for decision-making requires Business Intelligence.  Business Intelligence is the mechanism by which an organization conducts data analysis and creates data visualizations to derive and illustrate actionable insights about its past, present, and future. Business Intelligence helps makes sense of data by revealing patterns through analysis and linking those patterns, positive or negative, to specific decisions. It can be used by teams across an organization to track key metrics and measure progress on goals, or by C-level executives to inform broader decision-making.

                Business Intelligence Done Right

                In many organizations, the simplest form of Business Intelligence happens in spreadsheets.  Employees export data from systems to spreadsheets, generate figurines (e.g., charts and tables), and share them to inform decision-making.  Unfortunately, spreadsheet-based Business Intelligence has a number of disadvantages:

                • Spreadsheets are often locked away on the computer or Cloud account of the individual who created them. Others may not have access, which leads to the confusing co-existence of different spreadsheets containing the same data created by individuals in the same organization.

                • Spreadsheets are often out of date because few individuals understand how to set them to self-update.

                • Spreadsheets cannot process as much data as more specialized, dedicated data analysis tools.

                • Individuals can easily (even accidentally) leak spreadsheets outside of their organization.

                Given these challenges and others, Business Intelligence done “right” demands—at minimum—robust data warehousing capabilities and specialized data analysis tools like Tableau or Microsoft PowerBI. A data warehouse is the unification of disparate data sources into a centralized location to support Business Intelligence. The ideal data warehouse stores both operational and customer data so that an organization’s Business Intelligence team can quickly access up-to-date data to conduct analysis and inform decision-making.

                Ultimately the purpose of Business Intelligence is to support the workflow within an organization. Understanding the metrics, processes, and cadence of the business allows the Business Intelligence team to distribute data visualizations with the right data insights to the right decision-makers at the right time.

                Why Business Intelligence Matters

                Without Business Intelligence, organizations are “flying blind”.  Decisions might be made without any basis beyond intuition or “gut instinct”.  In today’s accelerating digital world, this kind of recklessness is flat-out dangerous and results in massive loss of revenue or profit, disgruntled workers, and unsatisfied customers.

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

                 

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                About Synaptiq

                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. 

                Contact us if you have a problem to solve, a process to refine, or a question to ask.

                You can learn more about our story through our past projects, blog, or podcast

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