![]() Explain processes being followed to make the data easier to access and analyze, and encourage this to become an ongoing enterprise process.Communicate the value of good quality data to the decision-making process, and reinforce the need to regularly assess the data and sources.Reinforce the mission of the company and how all decisions lead back to that mission.The need for, and awareness of, good actionable data should be communicated and reinforced at all levels of the organization. You also need to establish and maintain a solid foundation for data practices in your company. In other words, you might need to ensure your analysis covers a range of elements that could affect the data and the resulting decisions. A data-informed decision, however, might consider “likes,” as well as other factors such as time of day, perhaps graphics used, etc. As an example of a data-driven decision, let’s say you’re determining what your next blog post will be about based only on how many likes a post of yours received on LinkedIn this week. Are your decisions 100% data-driven, or are they data-informed? How you use your data can affect the outcomes you see. Once you’ve assessed the quality of your data, you need to look at how it affects your decision-making process. How comprehensive is the data? Is there enough for actionable analysis? Is the dataset complete, and does it cover what you need?Ħ. How relevant is the data? Is it timely and applicable?ĥ. Is the data consistent, or is it haphazard and unstructured?Ĥ. How valid is the data? Were there strict parameters?ģ. How exact is your data? What is the degree of error?Ģ. You can ask yourself the following questions to begin assessing the quality of your data:ġ. There are numerous factors to consider, such as the number of inputs, the nature of the data being collected and how the data is to be used. If you and your team do have access to your company’s data, what you now need to do is assess the quality of that data.
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