Remove Metrics Remove Slice and Dice Remove Visualization
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Know Your Data Ingredients

Juice Analytics

This is an often overlooked step on the rush to visualize data. In an effort to lay a strong foundation for your visualizations, here are three steps to understand and evaluate your data fields before you throw it into the Cuisinart that is your visualization tool. (1) 1) Separate your metrics from your dimensions.

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12 Marketing Reports Examples You Can Use For Annual, Monthly, Weekly And Daily Reporting Practice

datapine

While your keyboard is burning and your fingers try to keep up with your brain and comprehend all the data you’re writing about, using an interactive online data visualization tool to set specific time parameters or goals you’ve been tracking can bring a lot of saved time and, consequently, a lot of saved money. Structure your metrics.

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Super-charged pivot tables in Amazon QuickSight

AWS Big Data

Additionally, with Amazon QuickSight Q , end-users can simply ask questions in natural language to get machine learning (ML)-powered visual responses to their questions. This involved migrating complex tables and pivot tables, helping them slice and dice large datasets and deliver pixel-perfect views of their data to their stakeholders.

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Move Beyond Excel, PowerPoint And Static Business Reporting with Powerful Interactive Dashboards

datapine

Visualizing the data and interacting on a single screen is no longer a luxury but a business necessity. They enable you to easily visualize your data, filter on-demand, and slice and dice your data to dig deeper. Maps are important data visualizations and at datapine, we love utilizing them in our dashboards.

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13 power tips for Microsoft Power BI

CIO Business Intelligence

Power BI is Microsoft’s interactive data visualization and analytics tool for business intelligence (BI). With Power BI, you can pull data from almost any data source and create dashboards that track the metrics you care about the most. Power BI’s rich reports or dashboards can be embedded into reporting portals you already use.

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Data Storytelling: What's Easy and What's Hard

Juice Analytics

Gathering a collection of visualizations and calling it a data story is easy (and inaccurate). Making it meaningful is so much harder. Making data-driven narrative that influences people.hard. Schedule a demo.

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5 tips for excelling at self-service analytics

CIO Business Intelligence

Having that roadmap from the start helps to trim down and focus on the actual metrics to create. Have a data governance plan as well to validate and keep the metrics clean. As soon as one metric is not accurate it is hard to get the buy-in again, so routinely confirming accuracy on all analytics is extremely important.”

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