Research

The DataOps Transformation: 7 Steps To Prevent The Great War of Data Scientists

By Christopher Bergh, Mar 31, 2020

Available to Research & Advisory Network Clients Only

Join Christopher Bergh as he presents the seven steps to get these groups of people working together. These seven steps contain practical, doable steps that can help you achieve data agility through DataOps. This presentation will illustrate how to make changes to big data, models, and visualizations quickly, with high quality, using the tools teams love. We synthesize techniques from DevOps, Deming, and direct experience.

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Big Data and Analytics in the COVID-19 Era

By Jesse Anderson, Mar 26, 2020

Available to Research & Advisory Network Clients Only

Big Data and analytics are going to change in this COVID-19 era. In this Webinar, Jesse Anderson, leading expert in big data and related technologies and techniques, shares what he’s been telling his clients who call and ask, ‘Jesse, with all that’s going on what should we do now?’

Jesse explores a number of topics ranging from the implications of working from home to the tweaks that may be necessary to your current organizational models in the current economic climate.

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CAO Perspectives: Analytics Team Actions in Response to COVID-19

By Doug Hague, Mar 25, 2020

Available to Research & Advisory Network Clients Only

My Immediate Response:

  1. ALL HANDS ON DECK FOR OPERATIONAL REPORTING
    There will be new reporting needs and the frequency of information will need to speed up. Look for options and data that will be impacted by the current crisis. You will need to figure out how to quickly deliver information even if not perfect. Do the best you can, provide any glaring risks. Executives are starving for information. Make sure to provide the information to the most senior people first. Analytics teams can assist operations teams, data science people should even jump in as they have some of the best skills even if they are not using their modeling skills. Work with IT to pull information more quickly. Accept that you will be reporting off of sandboxes that are not production quality, get the exceptions from Risk and IT. You may need to time shift your team to earlier in the day as the executives will want things first thing when they come in if possible. Blend new data sets together to provide insights. Make sure to grab the customer feedback as even simple things like a word cloud may help.

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Analytics Applications Lifecycle Framework

By Doug Mirsky, Mar 02, 2020

Available to Research & Advisory Network Clients Only

Most analytics organizations at large companies do not own the entire lifecycle of their analytics applications. Instead, often-distributed analytical applications teams have to work with their partners in IT/IS organizations, as well as seek requirements, advice and consent from legal, compliance and governance functions within their organization. The essentially distributed nature of these work streams frequently results in inefficiencies or even full-on breakdowns in progressing an analytics application from proof of concept (PoC) to production. Success in distributed environments requires an overt, agreed-upon, stepwise plan along with the emotional intelligence to navigate the necessary conversations with your colleagues to build that plan.

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Competing on Analytics by Industry

By David Alles, Feb 17, 2020

Available to Research & Advisory Network Clients Only

Organizations today face an increasingly challenging business environment. Across industries, new companies and nimble competitors are taking advantage of analytics and leveraging the full potential of the internet, disrupting traditional business models and markets.

Cloud computing and open source have caused fundamental changes in analytics infrastructure, enabling the introduction of new technologies such as artificial intelligence and machine learning. The most nimble, innovative companies have quickly taken advantage of these new technologies — and the analytics they enable — to gain a competitive advantage.

Traditional companies are struggling to deal with this complexity and effectively compete on analytics. Though many top executives realize that high-quality data, analytics and AI are critical to the future success of their companies, up to 70 percent of analytics initiatives and projects fail to meet their objectives.

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Inquiry Response: Getting Started With HR Analytics

By IIA Expert, Bill Hoffman, Feb 10, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We’re just getting started with HR analytics, and we’re struggling with building a baseline reporting capability. There is an HRIS team; should HRIS own the analytics? Where should we start with our initial HR analytics projects? We use Workday for human capital management; can we use it for analytics too?

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Inquiry Response: Targeted Self-Serve Rollout

By IIA Expert, Jan 13, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We have a diverse analytics ecosystem across the enterprise with people using many different tools at various levels of competency. We want to provide more access to data in a self-service capacity, but in a targeted way. How do we decide who to target first?

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A Decade of IIA

By Thomas H. Davenport, Jack Phillips, Jan 08, 2020

Available to Research & Advisory Network Clients Only

We co-founded the International Institute for Analytics in 2010. Since it’s now 2020, our sophisticated math skills tell us that IIA has been around for about a decade—although our first full year of operation was in 2011. We thought it might be interesting to reflect on the state of the field that IIA addresses and how it has changed over time.

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2020 ANALYTICS PREDICTIONS AND PRIORITIES

By Thomas H. Davenport, Bill Franks, Drew Smith, Robert Morison, Dec 19, 2019

Each year, the International Institute for Analytics ends the year with a look at the latest analytics trends and the most pressing analytics challenges currently facing organizations. Our predictions are based upon our day-to-day work supporting and advising analytics leaders and organizations. We take advantage of the breadth of expertise and cross-industry perspectives we encounter every day from our clients, partners, and members of the IIA expert network. This is our 10th annual look toward the upcoming year, and our annual Predictions and Priority research brief and the associated webinar have become among IIA’s most popular content of the year. This year, we’ve stuck with our approach of augmenting each of our predictions with a specific priority for leaders to focus on as they attempt to address that prediction. As a result, each priority provides specific guidance as to how to best prepare for, and adapt to, its corresponding prediction.

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Open Source Analytics Software: A Primer

By Daniel Graham, Dec 17, 2019

Available to Research & Advisory Network Clients Only

Open-source software (OSS) is inevitable. For most corporations it’s not a question of “will we use OSS?” The right question is “how much OSS do we already have in production?” More than 90% of IT organizations have OSS in their mission-critical systems. Many commercial software products — from vendors such as IBM and Microsoft — also contain open source software.
Herein we explore these major OSS subjects:

  1. OSS history and concepts
  2. Quick tour of OSS analytics
  3. What does OSS really cost?
  4. Positives and negatives of OSS analytics
  5. Guidance

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