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Data AnalyticsBest Practices When Dealing with Data Analytics

Best Practices When Dealing with Data Analytics

Maintenance of order takes a lot of energy and investment. Things tend to become naturally disorganized except someone is putting them back in order data analytics. Anytime you analyze data you want to be sure to know where you are head. Otherwise, you will likely end up with another dashboard that you end up never using.

In this article, we discuss best practices to ensure you don’t make mistakes when dealing with data analytics.

1.Ask the right questions data analytics

When analyzing marketing data, start by asking the right questions. Yes, there are good and bad questions you can ask about your data. Asking the right question helps you to better understand your funnel and your overall business. The good questions start by understanding the overall impact on your business of what you are measuring.

2.Do not keep too many charts and tables

Ben Shneiderman, a computer scientist and specialist of data visualization once said: “overview first, zoom & filter and details on demand.” This means that you don’t need to use too many chats on your dashboard when you can use just one. We are sometimes tempte to make things too complicated. But simplicity is the ultimate sophistication. One great way to simplify your dashboard is to use breakdown dimensions and control filters in your data visualization tool.

3. Have a tracking plan 

Any project in analytics should start with a tracking plan. Your tracking plan should be derived from the business questions you want to be answered. A tracking plan can be a simple sheet that lists the metrics you want to measure. Or the dimensions that help you categorize data and the sources of your data.

4. Ask the “so what” question data analytics

You need to ask the difficult questions. For instance, what is the impact of this information on my business? If you are sharing your data analytics report, be sure to include a recommendation and an action plan directly. Even the most well-built dashboard needs interpretation and context. When you pull out the data you’ve done the difficult part.You might as well go on to tell your audience what to think about it.

5.Keep your metrics simple

Metrics alone do not improve your business, only action to improve results can do this. This means anything you measure and report with the intention of improving or sustaining business outcomes should drive human behavior.There is an increasing tendency to measure and report anything and everything with the hope of demonstrating improvement or satisfactory performance. These complex dashboards create more confusion than clarity. It is true that analysts are tempted to report as much information as possible.

Conclusion

Clarity and relevance should be the goal of data analytics.Knowledge is a process of piling up facts; wisdom lies in their simplification. It helps to revisit this notion anytime a new measure is proposed. Three simple charts that tell a user the status of the things they care aboutare more valuable than detailed dashboards that look like airplane cockpit. When faced with a choice, just keep it simple.

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