NHL hockey is perhaps the fastest and most action-packed sport on the planet. With skating speeds up to 30mph and pucks regularly clocked over 100mph the tempo allows for virtually no time to stop and think and instead necessitates continuous split-second decisions. This year, in an attempt to have insight into the chaos, the NHL released an in-game app exclusively for coaching staff that...
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Chances are your legacy enterprise data warehouse is expensive, does not scale, has limited domain coverage, and comes with fragile ETL process that is very expensive to maintain and extend. Your recent Data Lake investment struggles to provide value it promised. You’ve probably heard about data virtualization and federation – is this the modern solution to the age-old problem?…
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Forrester just released the following report; “Data Warehouse Automation Platforms Help Close The Data-To-Insight Gap.” According to the report’s key takeaways, “agile BI requires more than just agile dashboards” and “DWA enables BI self-service for use cases requiring a data warehouse.” We are honored to see West Monroe’s Rapid Analytics Platform (RAP) cited in this report that covers...
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The truth about data in baseball and in the business Grab the David’s sunflower seeds and a baseball cap, it’s MLB season. While we’re all anxious to see how the season unfolds over the next 2,400 games or so, let’s not forget how this years’ players ended up on the field in their respective jerseys for the 2019 season.…
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Industry 4.0 is accelerating digital manufacturing and predictive analytics on the shop floor, much in the same way as the professional sports analytics revolution has allowed teams to do more pre-game planning and more real-time, in-game informed decision making on the field. As a manufacturer, do you have what it takes to build a winning team in Industry 4.0?…
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Thesis Statement > Topic Sentences > Supporting Evidence Throughout high school and college, the above formula for how to write a good essay followed me everywhere I went. The thesis statement defines the argument to be made, the topic sentences break up the argument into smaller points, and the supporting evidence drives it all home.…
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Organizations have grown increasingly enthusiastic about the business insights and other benefits that big data analytics can deliver, and rightfully so. But as they pursue the promise of business analytics, companies often come face to face with some hard truths. One of the most problematic: following the traditional process of first creating a data warehouse and then analyzing the data...
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In the world of big data and predictive analytics the standard approach for gathering and analyzing data follows the CRISP-DM approach. While the CRISP-DM model has been a good approach on which to structure many projects, it suffers from the same issues waterfall-style requirements gathering approaches to software design have suffered from, including: Longer time to understand the...
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As companies incorporate data science and machine learning to help them push into the new AI frontier, some are finding it difficult to get data science operationalized. We know organizations have data, and lots of it, but not every organization achieves the same level of agility from its analytics and data science initiatives, meaning one organization may see the impact of data science more...
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Last week I was a panelist at the Utility Analytics Summit 2018 in Irvine, CA. This conference brought together IT and business leaders to share trends, insights, and challenges as they leverage data insights in their organizations. Below, I share some specific areas where the IT role is evolving in this exciting area.…
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Last September, I had the opportunity to attend Tech in Motion Chicago‘s Timmy Awards ceremony, where West Monroe Partners received an award for Best Tech Work Culture. The ceremony was hosted by 1871, a shared workspace for technology start-ups and other entrepreneurs to create, collaborate, accelerate, and celebrate new business ideas.…
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Some form of data governance is necessary for all organizations, regardless of industry or size. Data governance accomplishes many goals, from meeting regulatory requirements to fueling strategic initiatives that depend on data. While most organizations recognize the importance of data governance, they have trouble keeping momentum after starting. One issue is that data governance models are...
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