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Everything You Need to Know About Project Management Dashboard

FineReport

In the subsequent sections, we elucidate the key benefits in detail: Enhanced Project Visibility: Project management dashboards provide a centralized and real-time view of project data, allowing stakeholders to easily monitor and track project progress, tasks, and milestones.

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Managing risk in machine learning

O'Reilly on Data

There are also many important considerations that go beyond optimizing a statistical or quantitative metric. What is needed are data scientists who can interrogate the data and understand the underlying distributions, working alongside domain experts who can evaluate models holistically. Real modeling begins once in production.

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Analyst, Scientist, or Specialist? Choosing Your Data Job Title

Sisense

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Overall, however, what often characterizes them is a focus on data collection, manipulation, and analysis, using standard formulas and methods, and acting as gatekeepers of an organization’s data.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

Information retrieval The first step in the text-mining workflow is information retrieval, which requires data scientists to gather relevant textual data from various sources (e.g., The data collection process should be tailored to the specific objectives of the analysis.

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The path to embedded sustainability

IBM Big Data Hub

Our clients are improving their ability to measure and track progress against ESG metrics, while concurrently operationalizing sustainability transformation. Data not only provides the quantitative requirements for ESG metrics, but it also provides the visibility to manage the performance of those metrics.

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FRTB: Will 2023 Finally be the Year?

Cloudera

There will be an increased volume of data storage required, due to the longer history needed by the ES approach to risk measurement. And there will be expansions on the requirements for managing and monitoring both data lineage and data security. 30x increase in computational requirements. .

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What We Learned Auditing Sophisticated AI for Bias

O'Reilly on Data

As AI technologies are adopted more broadly in security and other high-risk applications, we’ll all need to know more about AI audit and risk management. applies external authoritative standards from laws, regulations, and AI risk management frameworks. Bias is about more than data and models.