Data visualization - see things differently. Natalie Yadrentseva
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The document discusses data visualization and methods for organizing data visually. It introduces planar and retinal variables as well as selective and associative organization as techniques for presenting data. Chronological, geographical, simple to complex, and common to details are listed as methods for organizing data visually. Value and size are also mentioned as ways to organize data. Contact information is provided at the end.
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So please join us for this webinar to learn about the:
Other primary drivers for enterprise Data Governance programs
Most common bottlenecks to program maturity and sustainability
Advantages of aligning Data Governance with the other data disciplines
In a post-COVID world, data has the power to be even more transformative, and 84% of business and technology professionals say it represents the best opportunity to develop a competitive advantage during the next 12 to 24 months. Let’s make sure your organization has the intelligence it needs about both data and data systems to empower stakeholders in the front and back office to do what they need to do.
Operational Risk Management Data Validation Architecture
This describes a structured approach to validating data used to construct and use an operational risk model. It details an integrated approach to operational risk data involving three components:
1. Using the Open Group FAIR (Factor Analysis of Information Risk) risk taxonomy to create a risk data model that reflects the required data needed to assess operational risk
2. Using the DMBOK model to define a risk data capability framework to assess the quality and accuracy of risk data
3. Applying standard fault analysis approaches - Fault Tree Analysis (FTA) and Failure Mode and Effect Analysis (FMEA) - to the risk data capability framework to understand the possible causes of risk data failures within the risk model definition, operation and use
Data Is Eating The World
A data-driven organization is imperative for the future. The smartphone and the ubiquitous computing have produced an exponential data explosion. From fueling the recent success of “artificial intelligence” (AI) and the rise of “digital transformation” to its accelerated growth due to Covid-19 to new approaches to its “monetization” to how it makes businesses and consumers both anxious and animated, data dominates our deeds, debates, and dreams. If the last decade was about “software eating the world, this decade is about “data eating the world”. Organizations are now faced with the huge challenge of managing, harnessing, and leveraging all of this data. We are still at the very beginning of the data revolution, and of understanding its second, third, and fourth-order effects. Organizations that are successfully transforming their business, technology, and operations strategy to align with their data strategy are the ones that will have a sustainable competitive advantage.
An Essential Part of the Data Scientist Course.pptx
Enrolling in a data scientist course in Jaipur equips students with the skills needed to excel in the field of data science, with a strong emphasis on data visualization. Mastering this skill allows future data scientists to transform data into meaningful insights, driving better decision-making and contributing to the success of organizations. As data continues to grow in volume and complexity, the ability to visualize and interpret it effectively will remain a valuable and sought-after skill.
IIBA Data Literacy.pdf
Join IIBA® Brisbane online as they discuss the trending topic of data literacy and data driven strategic leadership.
About this event
IIBA® Brisbane will be joined by renowned speaker, Michaela Shea, Senior Manager Data Governance in RSL Queensland as she unpacks her experience in building and leading teams through organisational wide transformations.
Michaela will share knowledge on her mission to make organisations thrive and survive digital disruption by harnessing the power of data, AI and technology through cultural, technological and data-driven strategies.
https://www.linkedin.com/in/michaela-shea/
Data is love data viz best practices
Greg Nelson presented on best practices for data visualization and storytelling. He began with an introduction that outlined his background and experience in analytics, data science, and data visualization. Nelson then led the audience through an interactive exercise where they rated different data visualizations. He discussed key factors that affect how audiences consume and engage with data visualizations. Nelson outlined objectives like learning how to critically evaluate visualizations, identify misleading techniques, and understand the competencies important for visual storytelling. He emphasized that effective stories can motivate action by addressing emotions and provided tips for developing compelling data stories based on Pixar's rules of storytelling.
Selecting and Constructing Data Collection Instruments 选择和构建数据收集工具
Shanghai International Program for Development Evaluation Training Asia-Pacific Finance and Development Center; 200 Panlong Road-Shanghai, October 14, 2008
Similar to Data visualization - see things differently. Natalie Yadrentseva (20)
GIAF USA Winter 2015 - Measuring collaboration in a multiplayer game
GIAF USA Winter 2015 - Measuring collaboration in a multiplayer game
How Data Scientists Make Reliable Decisions with Data
How Data Scientists Make Reliable Decisions with Data
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wepik-insightful-perspectives-a-data-visualization-overview-20240401133024gp4...
wepik-insightful-perspectives-a-data-visualization-overview-20240401133024gp4...
wepik-insightful-perspectives-a-data-visualization-overview-20240401133024gp4...
docuri.com_-best-practices-in-data-visualizations.pdf
docuri.com_-best-practices-in-data-visualizations.pdf
Operational Risk Management Data Validation Architecture
Operational Risk Management Data Validation Architecture
An Essential Part of the Data Scientist Course.pptx
An Essential Part of the Data Scientist Course.pptx
Selecting and Constructing Data Collection Instruments 选择和构建数据收集工具
Selecting and Constructing Data Collection Instruments 选择和构建数据收集工具
Data visualization - see things differently. Natalie Yadrentseva
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- 2. We create targetprocess Agile from day 1 Smart always learning Visual innovative visual management
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- 12. Planar variables
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