Data-driven Management Optimization 
datapine
APRIL 16, 2019
The term ‘big data’ alone has become something of a buzzword in recent times – and for good reason. By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data driven decisions that will drive your business forward.
CIO Business Intelligence
NOVEMBER 19, 2024
The next phase of this transformation requires an intelligent data infrastructure that can bring AI closer to enterprise data. The challenges of integrating data with AI workflows When I speak with our customers, the challenges they talk about involve integrating their data and their enterprise AI workflows.
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AWS Big Data
MARCH 10, 2025
Although traditional scaling primarily responds to query queue times, the new AI-driven scaling and optimization feature offers a more sophisticated approach by considering multiple factors including query complexity and data volume.
O'Reilly on Data
MAY 14, 2020
In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. In this article, we shift our focus to the AI Product Manager’s skill set, as it is applied to day to day work in the design, development, and maintenance of AI products. The AI Product Pipeline.
Speaker: Claire Grosjean, Global Finance & Operations Executive
Finance teams are drowning in data—but is it actually helping them spend smarter? Key Takeaways: Data Storytelling for Finance 📢 Transforming complex financial reports into clear, actionable insights. Compliance and Risk Considerations ✅ Navigating data-driven finance while staying audit-ready.
datapine
MARCH 6, 2023
Also, a great way to collect employee engagement data is using Gallup’s Q12 survey , which consists of 12 carefully crafted questions that gauge the most crucial aspects of employee engagement. Work with managers to incorporate career conversations in regular meetings with their teams. Highly engaged employees are 2.3x
datapine
SEPTEMBER 29, 2022
1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.
Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network
In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.
Speaker: Kevin Kai Wong, President of Emergent Energy Solutions
In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets. ♻️ Manufacturing corporations across the U.S.
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Download this guide for practical advice on how to use a semantic layer to unlock data for AI & BI at scale. You’ll learn how a semantic layer delivers massive ROI with streamlined query performance, concurrency, cost management, and ease of use. How to enable data teams to model and deliver a semantic layer on data in the cloud.
Speaker: Evelyn Chou
We’ll explore essential criteria like scalability, integration ease, and customization tools that can help your business thrive in an increasingly data-driven world. Attendance of this webinar will earn one PDH toward your NPDP certification for the Product Development and Management Association. Register to save your seat!
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