Selling your house in the financial crisis-stricken Greece is up to this day a great ordeal. When faced with such a challenge, I was baffled by the sparsity of conclusive data on land value at my birthplace city, Thessaloniki. Embarking on a personal mission and collecting and processing more than 10K online housing ads together with open data, I managed to render an insightful interactive visualization of the actual real estate values on borough and city block level that was published through the Greek media. Join me on this thought process journey to find out how to
o Gather vast online data with simple scripting
o Combine your data with open data into meaningful structures
o Create interactive data visualizations that have an actual impact @ infographeo.com
This will be an interactive session, so please feel free to bring your thoughts and questions to share during the session.
Data visualization is a powerful technology but it's a means to an end and not a goal by itself. Its main purpose is to enable more people to gain faster insights from data. One way to accelerate this time to insight is to design better, more efficient visualizations. Design guidelines remain an always popular topic for data visualization talks because most data analysis applications require users to spend a significant amount of time turning knobs to get to the output they need.
Alternatively, we suggest a design approach that focuses on meeting users' analysis needs, while minimizing their time to insight. In this IBM webinar, join IBM's data visualization specialist Frank van Ham as he illustrates the effectiveness of guided visual analytics on different types of data.
Content Provided by IBM
In the past two decades, visualization has become a language adopted not just by scientists and statisticians, but by journalists, designers, and the public in general. This process has been enabled by an increasing variety of software tools that are sophisticated, easy to use and, in many cases, free. However, knowledge of elementary principles of information presentation has not progressed at the same pace.
This webinar will provide an overview of these principles. You will learn:
-How to create charts and maps that don't mislead
-How to choose appropriate graphic forms to represent your information
-How to arrange your graphics to build compelling narratives
As data footprints in research organizations increase into the petabyte scale, so does the need to understand and visualize how that data is being used.
While data-aware scale-out NAS gives you powerful insights into your data, you can take this one step further by building custom visualizations using our programmable REST API.
Watch this webinar to learn how to:
- Understand the usage patterns of your data to best manage your storage environment
- Create interesting visualizations of your organization’s data using a programmable REST API
- Use the Qumulo QPI with common data scientist tools such as Python’s Jupyter Notebook
This talk discusses the broad design considerations necessary for effective visualizations.
Attendees will learn what’s required for a visualization to be successful, gain insight for critically evaluating visualizations they encounter, and come away with new ways to think about the visualization design process.
To be effective, a visualization must have:
This talk will define these four pillars, reveal why they must be selected in this order, and discuss the importance and impact each has on your visualization.
Data visualization requires data to be prepared before any meaningful analysis can be conducted. Finding insights, making correct observations and taking actions to drive outcomes therefore don't just depend on the way information is communicated but also on the preparation preceding the analysis.
In this webinar we discuss the key steps for data preparation to enable effective analysis and visual exploration of the data. We will show practical examples from projects we have worked on as well as share some simple data preparation ideas from our Makeover Monday challenges.
Lastly, we will show an example of how data preparation can enrich a dataset and enable further analysis.
What does the future hold?
Predictive Analytics - everyone is talking about it and many organisations claim to be doing it. But are they? And what insights do they gain to then make tactical or strategic changes? How can analysts work with decision makers by sharing results in a visually effective and meaningful way while also informing them about possible courses of action?
This webinar is presented by Andy Kriebel, Head Coach at the Data School and Eva Murray, Tableau Evangelist at Exasol. Our guest speaker on Predictive Analytics is Benedetta Tagliaferri, Consulting Analyst at The Information Lab.
The webinar will look at some examples of predictive analysis and will show data visualization examples that are actionable and can drive further questions and discussions in an organisation.
Death to Spreadsheets!
Despite the growing popularity of data visualization tools across all industries, the finance sector still relies heavily on seeing data presented in tabular form. Analysts in financial institutions often spend a large part of their day pouring over spreadsheets, extracting numbers, pivoting tables, running macros and making adjustments before creating static reports to print for management meetings.
But what happens if you have another question?
We argue that there is a better way to approach financial data and to unlock more of the collective brain power of your analysts. We will show you a number of options for visualizing financial results, highlighting trends and developing KPI dashboards that provide real insights quickly. Because there are more valuable things your staff could be doing than wrangling with spreadsheets
Whenever there is data, there is the chance to visualize it and gain valuable insights that can drive change and improvements. Governments have realized the potential that data holds for transforming our towns, cities, living spaces and communities to better address the needs of our modern society.
Governments may want to change public transport services to suit commuters who move away from city centers due to increasing living costs, or develop programs that deliver more support services to areas showing high incidences of mental illnesses, or simply monitor bike traffic to assess the necessity of additional cycle lanes and bike share programs in our capitals. Data and data visualization can help us identify the needs of our communities and can support us in addressing them effectively.
In this webinar Andy and Eva will present examples of Government using data to improve services for communities and will share how you can get involved through analyzing open data and becoming part of the wider 'dataviz' community.
TIBCO Spotfire sponsored webinar from HBR featuring data visualization expert Scott Berinato, author of Good Charts and HBR articles including “Visualizations that Really Work” and “Dataviz: Making Smarter, More Persuasive Data Visualizations”
Join Scott Berinato for a step-by-step demonstration of “whiteboarding” ideas and unlocking the right visualization options. He will provide a real-time example of how teams can take apart visualization challenges and unlock the most important information to tell the most compelling stories.
This webinar Sponsored by TIBCO Spotfire,follows Better Charts in a Couple of Hours: Sketching to Win, which focused on preparing to create data visualizations.
This second webinar in HBR’s series on data visualizations—The Right Stuff: Chart Types and Visualization Best (and Worst) Practices–-will look at different types of charts and explore which are the most compelling and persuasive in different situations.
Bar charts, line charts, and scatter plots can take you a long way, but there are other simple chart types that might be more compelling and persuasive. In this interactive webinar, Berinato will review all types of charts and share best (and worst) practices from his data visualization experience. He will also discuss charts that can mislead and will provide insights on how to spot a manipulation with data.
There’s a verse in Proverbs of the Tanakh that goes like this: As iron sharpens iron, so one person sharpens another. – Proverbs 27:17
What does this verse mean? It means that when you have a good friend, that friend will push you and make you better and stronger. If you make a mistake, they’ll point it out to you in the right way so that you don’t make it again. If you do something well, they’ll pat you on the back, but they’ll also help you figure out how to do it even better next time. And vice versa.
That’s the value of the data visualization community, and why the more voices that join, the better off we’ll all be.
There’s a big qualifier to that statement, though. In order to reap benefits from our interactions with each other, we must avoid two diametrically opposed cultural paradigms which are the antithesis of iron sharpening iron. Attend this webinar to learn more.
In 1914, New Yorker Willard Brinton wrote Graphic Methods for Presenting Facts, the first book on telling stories through data and communicating information visually. Today, the volume of data in the world is exponentially increasing, the tools to transform analysis into stories are evolving—and 100 years later, Brinton’s lessons still hold true.
In this 60-minute webinar, explore:
- Visualization basics that withstand the test of time
- The right charts for telling the right stories
- Brinton’s checklist for communicating data
Join Andy Cotgreave, Senior Technical Evangelist Manager at Tableau Software, for a 100 year flashback into the best practices that still shape effective storytelling through visual analytics.
Discover how librarians are enriching their reports and presentations to key library stakeholders with multimedia and data visualizations. Get ideas on how to give library users a platform to tell their stories about the library. Learn more about tools that can help you gain insight into and share information about your institution's research activities and performance.
Registration is required for this live webinar. It will be broadcast internationally and includes time to ask the presenters questions during the session. The webinar is a complimentary event and part of Elsevier's Library Connect program for academic, medical, corporate and government librarians.
Cannot attend on November 16? Register for the webinar and you will be notified when it can be viewed online after the event.
Data visualization must be intuitive in order for non-IT business leaders to see data patterns. Representing data in a graphical or pictorial format is easy, but constructing the data in the best and most logical way can be tricky.
In this session, Umesh will talk about how to represent data simply to make quicker and better business decisions. He will walk through several data visualization techniques through business cases and examples. By the end of the session, you will not only know different data visualization techniques, but also have an understanding of circumstances under which each technique should be used and the best way to represent particular data sets for different business cases.
Catch this follow up Q&A from the A Guide to Machine Learning Patterns and Data Visualizations presentation. Umesh answers remaining and follow up questions from the audience.Read more >
Machine learning has unlocked new possibilities that deliver significant business value. However most companies don’t have the resources to either build and maintain the supporting infrastructure or apply data science to build a smarter solution.
Join us for this webinar and hear from John Huang, engineering and data analytics lead at Handshake, as he shares how he quickly and cost effectively scaled a small engineering team to build an machine-learning powered recommendation engine that profiles users and behaviors to present relevant next steps. In this webinar you will learn how to:
-Simplify and accelerate data engineering processes including data ingest and ETL
-Incorporate machine learning into your production application without an army of data scientists
-Choose an analytics engine that will enable key analytics such as attribution, step analysis, and linear regression
-Embed visualizations into your application that drive stickiness