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Data Analytics: Strategies to Demonstrate Value and Achieve Transformation

CIO

Recently, chief information officers, chief data officers, and other leaders got together to discuss how data analytics programs can help organizations achieve transformation, as well as how to measure that value contribution. This is when data analytics programs deliver their greatest value. Arguing with data?

Analytics 263
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8 data strategy mistakes to avoid

CIO

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. Unfortunately, the road to data strategy success is fraught with challenges, so CIOs and other technology leaders need to plan and execute carefully. Here are some data strategy mistakes IT leaders would be wise to avoid.

Strategy 340
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Sport analytics leverage AI and ML to improve the game

CIO

Nearly 10 years ago, Bill James, a pioneer in sports analytics methodology, said if there’s one thing he wished more people understood about sabermetrics, pertaining to baseball, it’s that the data is not the point. Improving player safety in the NFL The NFL is leveraging AI and predictive analytics to improve player safety.

Sport 287
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6 strategic imperatives for your next data strategy

CIO

According to the MIT Technology Review Insights Survey, an enterprise data strategy supports vital business objectives including expanding sales, improving operational efficiency, and reducing time to market. The problem is today, just 13% of organizations excel at delivering on their data strategy.

Strategy 289
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Meet Your Goals with a Practical Product Strategy

Speaker: Nils Davis, Principal, NPD Associates

But do you have a strategy? Strategy and goals are different. It's your strategy that allows you to make decisions that help you meet your goals in the first place. If you want to have an articulated strategy that you can use to make decisions, stay on-track, and meet your product goals, this is the webinar for you!

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5 tips for excelling at self-service analytics

CIO

One potential solution to this challenge is to deploy self-service analytics, a type of business intelligence (BI) that enables business users to perform queries and generate reports on their own with little or no help from IT or data specialists. But there are right and wrong ways to deploy and use self-service analytics.

Analytics 342
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Two great reads (and one listen) to prepare for CIO’s Data, Analytics & AI Summit

CIO

At our upcoming Data, Analytics & AI Summit – a virtual event taking place April 11 – attendees will hear from CIO editors and contributors, including Paula Rooney, Lucas Merian, Issac Sacolick, and Today in Tech podcast host Keith Shaw. Interested in even more data, analytics and AI coverage? We have you covered.

Analytics 276
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How to Scale a Data Literacy Program at Your Organization

Speaker: Megan Brown, Director, Data Literacy at Starbucks; Mariska Veenhof-Bulten, Business Intelligence Lead at bol.com; and Jennifer Wheeler, Director, IT Data and Analytics at Cardinal Health

Join data & analytics leaders from Starbucks, Cardinal Health, and bol.com for a webinar panel discussion on scaling data literacy skills across your organization with a clear strategy, a pragmatic roadmap, and executive buy-in. You’re invited! Unlocking enhanced levels of value and insight from data using a semantic layer.

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How Product Managers Can Learn to Love Reporting

Speaker: Eric Feinstein, Professional Services Manager, Looker

How to evaluate embedded analytic solutions as strategy to greatly reduce initial and on-going engineering effort. He will discuss working through personas, data types, reporting needs analysis and ultimately how this comes together to form a roadmap for reporting functionality and interface.

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Ask the "Right" Questions: Your Analytics-Guided Product Strategy

Speaker: Yoav Yechiam, Founder and Head Instructor, productMBA

Analytics are highly important for product managers - and yet, analytic implementations often fail to actually help us. Analytics are there to answer important product questions, not just to collect data. How can we be mindful of our analytics so they enable us, rather than confine us?

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Are You Ready For Predictive Analytics?

Speaker: Anita Lauper Wood, Product Strategist

As a product or technology leader, you likely know there’s a tremendous value that can be gained from predictive analytics. That said, successful implementation of predictive analytics can feel unpredictable. There are risks that need to be consciously addressed, and successful implementation requires the right strategy.

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Differentiate Your Product With Unstructured Data Analytic Capabilities

Computing surveyed 150 individuals representing companies from a wide variety of industries that are actively involved in using, testing, evaluating, or procuring data analytics tools at their organization. Download now to learn: The state of data analytics in end-user organizations.

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How to Develop a Recession-Proof Product-Led Strategy

Speaker: Wes Bush, Author of "Product-Led Growth"

As PMs, we all know the importance of building a successful product-led growth strategy. Zoom, Stripe, and Airtable are all examples of software companies with strong PLG strategies. What features do their strategies have that allow them to see continued success in this ever-changing market? But what else do they have in common?

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Embedded BI and Analytics: Best Practices to Monetize Your Data

Speaker: Azmat Tanauli, Senior Director of Product Strategy at Birst

By creating innovative analytics products and expanding into new markets, more and more companies are discovering new potential revenue streams. Join Azmat Tanauli, Senior Director of Product Strategy at Birst, as he walks you through how the data that you're likely already collecting can be transformed into revenue!

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How King Crushes New Product Development using Data-Driven Insights

Speaker: Ian Thompson, Head of Business Intelligence at King, and Zara Wells, Strategic Customer Success Manager at Looker

King uses almost a competitive launch strategy for new games, as each game has a series of KPIs that it needs to meet. King’s product managers rely heavily on analyzing product features using analytics data and visualization to improve outcomes. The key is the strategy and tools for accessing product data at the level that you'd like.