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Building your First Power BI Report from Scratch

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. What is equally important here is the ability to communicate the data and insights from your predictive models through reports and dashboards. PowerBI is used for Business intelligence. And […].

Reporting 389
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Top 10 Power BI Interview Questions in 2022

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Power BI interviews will provide insights from a variety of data by modelling data and telling stories from data visualizations using reports and dashboards. Source: [link] […].

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

In the following section, two use cases demonstrate how the data mesh is established with Amazon DataZone to better facilitate machine learning for an IoT-based digital twin and BI dashboards and reporting using Tableau. From here, the metadata is published to Amazon DataZone by using AWS Glue Data Catalog.

IoT 107
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Marketing Dashboard: Secretes To Adapt To Fast-Changing Market

FineReport

One of the most difficult problems faced by marketers is how to analyze all the information, which comes from customer surveys, from complex computer models, and from various channels. Marketing dashboard can do you a favor. What is a marketing dashboard? Use of Reports and Dashboard. Dashboard Interface of FineReport.

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Managing machine learning in the enterprise: Lessons from banking and health care

O'Reilly on Data

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Sources of model risk. Model risk management. Image by Ben Lorica.

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How REA Group approaches Amazon MSK cluster capacity planning

AWS Big Data

Hydro is powered by Amazon MSK and other tools with which teams can move, transform, and publish data at low latency using event-driven architectures. However, it wouldn’t be wise to display an excessive number of metrics on our monitoring dashboards because that could lead to less clarity and slower insights on the cluster.

Metrics 87
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What you need to know about product management for AI

O'Reilly on Data

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. The model is produced by code, but it isn’t code; it’s an artifact of the code and the training data.