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In order for you to really truly understand what is happening to your business, your customers and the yummy business outcomes, you need to be able to segment the data. You need to slice! You need to dice! Repeat after me: Slice, dice, drill!! Checking datacollection quality etc. You need to drill!
The point of such dashboards is not to simplify the working environment and analysis processes since there are massive volumes of datacollected on a daily level, and companies need solutions that will bring them to the right answer at the right time.
When the data sets are large, with numerous attributes, users spend a lot of time slicing and dicing for newer insights or apply their original hypotheses to a subset of data. We rely on data and analytics to assist in all three areas.
What is the change that they want to facilitate, and what data elements can help them in deciding how to improve or facilitate that change?”. So that’s what we start with,” continues Vincent, “and then we [add] all these datacollection methodologies that will gather that information needed to make those insights.”.
" In service of analysis the job includes: Pulling data, segmentation, slicing and dicing, drilling-up, drilling-down, drilling-around, modeling, creating unique datasets, answering business questions, writing requirements for data sources and structures for Reporting Squirrels to work with IT teams to create, etc.
If you are a content site, this means the ability to slice and dice your data by author names, content type, subscribers and free-loaders, commentators and non-commentators, and so much more to bring a new layer of insights. As always, it is your turn now. Which of the above ten hidden gems will you find to be most useful?
Dimensions allow you to group your data into different buckets and they are most frequently used to slice and dice the web analytics data. We worry so much about tags and datacollection and Omniture vs. WebTrends. or doing advanced segmentation (worship this!). Truly heart warming.
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. Too many bars, inside them too many slices, odd color choices, all end up with this question: what the heck's going on here?
Measurement challenges Assessing reliability is essentially a process of datacollection and analysis. To do this, we collect multiple measurements for each unit of observation, and we determine if these measurements are closely related. In this case, the scale is not measuring the construct that interests us.
Let’s just give our customers access to the data. You’ve settled for becoming a datacollection tool rather than adding value to your product. While data exports may satisfy a portion of your customers, there will be many who simply want reports and insights that are available “out of the box.”
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