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To understand the risks posed by AI, follow the money

O'Reilly on Data

It’s difficult to argue with David Collingridge’s influential thesis that attempting to predict the risks posed by new technologies is a fool’s errand. However, there is one class of AI risk that is generally knowable in advance. It is a predictable economic risk.

Risk 221
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A Beginner’s Guide To Inventory Metrics And Best Practices

datapine

At the same time, inventory metrics are needed to help managers and professionals in reaching established goals, optimizing processes, and increasing business value. We will finish by presenting a business dashboard that will show how those metrics work together when depicting an inventory data-story. What Are Inventory Metrics?

Metrics 286
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Take Advantage Of Operational Metrics & KPI Examples – A Comprehensive Guide

datapine

By establishing clear operational metrics and evaluate performance, companies have the advantage of using what is crucial to stay competitive in the market, and that’s data. Your Chance: Want to visualize & track operational metrics with ease? What Are Metrics And Why Are They Important?

KPI 269
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How to build a successful risk mitigation strategy

IBM Big Data Hub

.” This same sentiment can be true when it comes to a successful risk mitigation plan. The only way for effective risk reduction is for an organization to use a step-by-step risk mitigation strategy to sort and manage risk, ensuring the organization has a business continuity plan in place for unexpected events.

Risk 76
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How Big Data Impacts The Finance And Banking Industries

Smart Data Collective

Typically, this approach is essential, especially for the banking and finance sector in today’s world. Right now, Big Data tools are continuously being incorporated in the finance and banking sector. Here are a few of the advantages of Big Data in the banking and financial industry: Improvement in risk management operations.

Big Data 142
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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

6) Data Quality Metrics Examples. Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. The data quality analysis metrics of complete and accurate data are imperative to this step. Table of Contents. 2) Why Do You Need DQM?

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You Can’t Regulate What You Don’t Understand

O'Reilly on Data

Should we risk loss of control of our civilization?” If we want prosocial outcomes, we need to design and report on the metrics that explicitly aim for those outcomes and measure the extent to which they have been achieved. If every company had a different way of reporting its finances, it would be impossible to regulate them.

Metrics 284