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Tableau: 9 years a Leader in Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

Tableau

Gartner has again recognized Tableau as a Leader—for our ninth consecutive year. . I first want to thank you, the Tableau Community, for your continued support and your commitment to data, to Tableau, and to each other. With your input, we released more than 200 new capabilities across the Tableau platform in 2020.

Tableau 102
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Data scientist

Dataconomy

Roles and responsibilities of a data scientist Data scientists are tasked with several important responsibilities that contribute significantly to data strategy and decision-making within an organization. Analyzing data trends: Using analytic tools to identify significant patterns and insights for business improvement.

professionals

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What is a data fabric?

Tableau

Senior Manager, Product Marketing, Tableau. By now, you’ve heard the good news: The business world is embracing data-driven decision making and growing their data practices at an unprecedented clip. At Tableau, we believe that the best decisions are made when everyone is empowered to put data at the center of every conversation.

Tableau 102
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What is a data fabric?

Tableau

Senior Manager, Product Marketing, Tableau. By now, you’ve heard the good news: The business world is embracing data-driven decision making and growing their data practices at an unprecedented clip. At Tableau, we believe that the best decisions are made when everyone is empowered to put data at the center of every conversation.

Tableau 98
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Tableau: 9 years a Leader in Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

Tableau

Gartner has again recognized Tableau as a Leader—for our ninth consecutive year. . I first want to thank you, the Tableau Community, for your continued support and your commitment to data, to Tableau, and to each other. With your input, we released more than 200 new capabilities across the Tableau platform in 2020.

Tableau 52
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Turn the face of your business from chaos to clarity

Dataconomy

Data scientists must decide on appropriate strategies to handle missing values, such as imputation with mean or median values or removing instances with missing data. The choice of approach depends on the impact of missing data on the overall dataset and the specific analysis or model being used.

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Big Data vs. Data Science: Demystifying the Buzzwords

Pickl AI

Real-World Example: Healthcare systems manage a huge variety of data: structured patient demographics, semi-structured lab reports, and unstructured doctor’s notes, medical images (X-rays, MRIs), and even data from wearable health monitors. Ensuring data quality and accuracy is a major challenge.