Remove Optimization Remove Predictive Modeling Remove Risk Remove Uncertainty
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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. AI initiatives may also require significant considerations for governance, compliance, ethics, cost, and risk. There’s a lot of overlap between these factors. Defining them precisely isn’t as important as the fact that you need all three.

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Sound Decisions in Dynamic Times – Forecasts and Simulations Support Modern Corporate Management

BI-Survey

Markets and competition today are highly dynamic and complex, and the future is characterized by uncertainty – not least because of COVID-19. This uncertainty is currently at the forefront of everyone‘s minds. 75 percent of companies confirm that predictive models provide good forecasts for them, even in volatile markets.

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Sound Decisions in Dynamic Times – Forecasts and Simulations Support Modern Corporate Management

BI-Survey

Markets and competition today are highly dynamic and complex, and the future is characterized by uncertainty – not least because of COVID-19. This uncertainty is currently at the forefront of everyone‘s minds. 75 percent of companies confirm that predictive models provide good forecasts for them, even in volatile markets.

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Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast. A single model may also not shed light on the uncertainty range we actually face.

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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

But the database—or, more precisely, the data model —is no longer the sole or, arguably, the primary focus of data engineering. If anything, this focus has shifted to the ML or predictive model. In the second place, data-in-motion behaves less predictably than data-at rest.

IoT 20