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How an EPM Solution Supports Managing Economic Uncertainty

Jedox

Dean Boyer as a guest to the Jedox Blog for our series on “Managing Uncertainty” Mr. Boyer is a Director of Technology Services at Marks Paneth LLP, a premier accounting firm based in the United States. He shares his expertise on how an EPM solution supports managing economic uncertainty, particularly in times of crisis.

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Decision Making with Uncertainty Requires Wideward Thinking

Andrew White

COVID-19 and the related economic fallout has pushed organizations to extreme cost optimization decision making with uncertainty. The models are practically useless. Oh, and by the way, you now have less time to make the decisions (see How to Manage Your Predictive Models During the Pandemic’s Rapid Changes ).

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How an EPM Solution Supports Managing Economic Uncertainty

Jedox

Dean Boyer as a guest to the Jedox Blog for our series on “Managing Uncertainty” Mr. Boyer is a Director of Technology Services at Marks Paneth LLP, a premier accounting firm based in the United States. He shares his expertise on how an EPM solution supports managing economic uncertainty, particularly in times of crisis.

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Real-time Data, Machine Learning, and Results: The Evidence Mounts

CIO Business Intelligence

They identified two architectural elements for processing and delivering data: the “data platform,” which covers the sourcing, ingestion, and storage of data sets, and the “machine learning (ML) system,” which trains and productizes predictive models using input data. Data Architecture, IT Leadership

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IT leaders embrace the role of business change maker

CIO Business Intelligence

Foundry / State of the CIO That distinct view, coupled with ongoing pressure to accelerate digital business brought on by pandemic-era changes and economic uncertainties , have launched CIOs into the change management hot seat.

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

DataKitchen

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. Data engineers ensure that all the ingested, processed, and transformed data culminates in actionable, reliable products—be it a predictive model, a dashboard, or a data export.

Testing 169
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How to Set AI Goals

O'Reilly on Data

Technical competence results in reduced risk and uncertainty. Likewise, AI doesn’t inherently optimize supply chains, detect diseases, drive cars, augment human intelligence, or tailor promotions to different market segments. There’s a lot of overlap between these factors.