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Data Quality vs Data Condition: The Power of Context

Anmut

Facts, events, statements, and statistics without proper context have little value and only lead to questions and confusion.?This This is true for life in general, but it’s especially applicable to the data you use to power your business. Data quality vs data condition: basic definitions & differences.

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15 best data science bootcamps for boosting your career

CIO Business Intelligence

An education in data science can help you land a job as a data analyst , data engineer , data architect , or data scientist. The course includes instruction in statistics, machine learning, natural language processing, deep learning, Python, and R. On-site courses are available in Munich.

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Why you should care about debugging machine learning models

O'Reilly on Data

Residual plots place input data and predictions into a two-dimensional visualization where influential outliers, data-quality problems, and other types of bugs often become plainly visible. Small residuals usually mean a model is right, and large residuals usually mean a model is wrong. If so, have fun debugging! [1]

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How AWS helped Altron Group accelerate their vision for optimized customer engagement

AWS Big Data

Altron is a pioneer of providing data-driven solutions for their customers by combining technical expertise with in-depth customer understanding to provide highly differentiated technology solutions. Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices.

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Data Science, Past & Future

Domino Data Lab

He was saying this doesn’t belong just in statistics. He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. To some extent, academia still struggles a lot with how to stick data science into some sort of discipline.

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The Gartner 2022 Leadership Vision for Data and Analytics Leaders Questions and Answers

Andrew White

We found anecdotal data that suggested things such as a) CDO’s with a business, more than a technical, background tend to be more effective or successful, and b) CDOs most often came from a business background, and c) those that were successful had a good chance at becoming CEO or CEO or some other CXO (but not really CIO).

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Systems Thinking and Data Science: a partnership or a competition?

Jen Stirrup

The foundation should be well structured and have essential data quality measures, monitoring and good data engineering practices. Systems thinking helps the organization frame the problems in a way that provides actionable insights by considering the overall design, not just the data on its own.