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There are three elements to our "big data" efforts, or unhyped normal data efforts: Data Collection, Data Reporting, and DataAnalysis. Data presentation! After all you spent so much time on collection, reporting and analysis. Your data presentation is your brand. #2.
Produce built-in visualization magic. Ravaging data. Leverage Custom Alerts – Let Data Kick Your Butt Into Action. #3. Use Table View Options (Comparison, Pivots, In-line Filters) – Faster Initial Insights. #4. In-Page Analytics – Re-imagine Traveling Through Data. #5. Ravage all the features.
The gap between a bad and good datavisualization is small. The gap between a good and great datavisualization is a vast chasm! We’ll start by looking at the two sets of humans who are at the root of the conflict of obsessions and then learn to assess how effective any datavisualization is in an entirely new way.
work (collection, processing, reporting, analysis), processes, org structure, governance models, last-mile gaps , metrics ladders of awesomeness , and… so… much… more. I’ve intended to create a simple visual that absorbs the scale, complexity and many moving parts. That’s because we have to talk about tools (so many!),
Custom reports allow you to package up entire datasets for deeper analysis. Many custom reports are wrong because we mess up the fundamental data model in analytics. Social Media Performance Analysis. Business Outcomes Analysis. Campaign Cost Analysis. Key Metrics: Map Overlay Visualization.
Like a vast majority on planet Earth, I love datavisualizations. There is something magical about taking an incredible amount of complexity and presenting it as simply as we possibly can with the goal of letting the cogently presented insight drive action. Datavisualized is data understood.
Let’s buy more hamster wheels, hire more hamsters and train them to spin faster ! At the end of each day, the data was collected and used to train a deep convolutional neural network (CNN), to learn to predict the outcome of each grasping motion. And every day it will get smarter as it’ll have access to the latest (and more) data.
Ten years, and the 944,357 words, are proof that I love purposeful data, collecting it, pouring smart strategies into analyzing it, and using the insights identified to transform organizations. Don't fragment data, don't forget higher order bits. The end result in all these cases is that data efforts come to naught.
If you are in a company this is easier to get done as you have access to people and at least some data (even if the site is not tagged). For help with identifying opportunities and how to do business analysis please see this post: The Beginner's Guide to Advanced Web DataAnalysis. That takes a few days of pain.
I believe deeply in the value of making data accessible. In service of that belief, there are few things that bring me as much joy as visualizingdata (smart segmentation comes close). The result then is both a mind and heart connection that drives action with a sense of urgency. 5: What-if Analysis Models.
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