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Avoid generative AI malaise to innovate and build business value

CIO Business Intelligence

However such fear, uncertainty, and doubt (FUD) can make it harder for IT to secure the necessary budget and resources to build services. Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key.

Data Lake 142
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The state of data quality in 2020

O'Reilly on Data

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Adopting AI can help data quality.

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Boost Data Literacy to Overcome Skills Shortages

Jet Global

From Data Literacy to Fluency: Strategies for Becoming a Data-Driven Organization Download Now Four Steps to Achieving Data Fluency Another recent insightsoftware study , this time on building data fluency, highlights some key steps that organizations can take to shore up data processes and reduce time spent waiting for IT.

Finance 52
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How Remote Data Teams Are Winning in Times of COVID-19

Octopai

Businesses around the globe have been forced to reassess the way they conduct their operations, even if their methods have been in place for decades. Some business intelligence professionals are not only contributing to their organization’s survival during these difficult times; they are actually helping it thrive.

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Transforming FSI in ASEAN with Cloud Analytics

CIO Business Intelligence

However, many financial services companies still prefer to build their own data centers rather than leverage cloud solutions. Much of this reluctance stems from the regulatory environment, arising from lengthy reviews and approvals processes, or even simple near-term regulatory uncertainty. .

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The Art and Science of FP&A Storytelling

Timo Elliott

First, because uncertainty exploded. The rules of thumb and standard ways of doing business have been thrown out of the window. As I’ve said, data storytelling isn’t fundamentally about technology. Dashboards and analytics have been around for a long, long time. But recently, there has been a surge in demand. The key takeaways.

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Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability

DataKitchen

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Use?

Testing 176