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Organizing Analytics: Building Your Team and Specialties
This article is the final installment of our series on organizing analytics. Up to this point, we’ve explored how to select the right organizational model for your business, the common paths of model evolution within a company over time, and ways to coordinate analytics across the enterprise. To round out
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Organizing Analytics: Coordinating Across the Enterprise
This article is part of a blog series on organizing analytics. Please see the sidebar for the full discussion. As the first two blogs on selecting the right organizational model and evolving the organization over time made clear, no one organizational model is best in terms of meeting all goals
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Open Source: IIA Experts in Conversation - The Emergence of AI Literacy with Mike Congdon
IIA guides data and analytics leaders and their teams in the transition to enterprise-wide advanced analytics and AI. Our passion is helping data and analytics organizations at complex companies navigate the human hurdles in implementing data and analytics initiatives, challenges like stakeholder engagement, business alignment, and user adoption. IIA’s Research
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January: Best of the Web
Read below for a roundup of interesting sites, resources, and articles from around the web, curated and contextualized by unbiased analytics experts at IIA. Highlights include a podcast with Capital One's Head of Enterprise AI on the company's implementation of AI tools, an article on utilizing AI for data storytelling
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Common Obstacles to Analytics Success: The Business
What are the common hurdles encountered when putting analytics to work in a business, both in developing analytical models and applications and in building enterprise analytical capability? This question is central to IIA’s mission of helping organizations navigate the many challenges to achieving analytics maturity. Succeeding with analytics, and sustaining
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Common Obstacles to Analytics Success: Execution
What are the common hurdles encountered when putting analytics to work in a business, both in developing analytical models and applications and in building enterprise analytical capability? This question is central to IIA’s mission of helping organizations navigate the many challenges to achieving analytics maturity. Succeeding with analytics, and sustaining
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Common Obstacles to Analytics Success: Data and Technology
What are the common hurdles encountered when putting analytics to work in a business, both in developing analytical models and applications and in building enterprise analytical capability? This question is central to IIA’s mission of helping organizations navigate the many challenges to achieving analytics maturity. Succeeding with analytics, and sustaining
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Common Obstacles to Analytics Success: People
What are the common hurdles encountered when putting analytics to work in a business, both in developing analytical models and applications and in building enterprise analytical capability? This question is central to IIA’s mission of helping organizations navigate the many challenges to achieving analytics maturity. Succeeding with analytics, and sustaining
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Powering Your Journey with AI
We have come a long way in discussing why and how to accelerate your data innovation journey. We discussed the rapidly evolving healthcare landscape and how the digitization of the consumer experience (and data) is fueling business initiatives to improve access and outcomes, accelerate research, enrich patient and workforce experience
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Segmenting Your Analytics and AI Demand, Part 1: From Demand Patterns to Advocacy
Every organization has an information economy with a supply-side that provides data and tooling to analysts and a demand-side that consumes data and analyses to make decisions (see sidebar for blog series on your firm’s information economy and the balancing act between supply and demand). Analytics and AI programs require