One of the attractive things about big data is the sheer variety of data sets that you can analyze and visualize. The potential for discovering useful data is almost endless, but so is the possibility of wasting time analyzing data that ultimately proves to be useless. There is no single defining line that divides good data from bad; ultimately, where that line is drawn will depend on your company’s practices and resources. However, almost all businesses can improve the quality of their data by following a few general pointers.
The most important way to improve your data quality is to focus on the needs of your business. Data analysis can answer questions and inform decisions; knowing what the most important questions and decisions are is key to identifying both useful data and useless data. Although it is always important to keep your mind open to new possibilities regarding your company’s priorities, it is even more important to begin your data analysis process with a clear picture of those priorities as they exist now.
Once you’ve actually begun mining and monitoring data, you need to sort the relevant from the irrelevant. One strategy that works exceedingly well for this is keeping an eye out for data sets that change significantly. Some sets of data are more likely to change dramatically than others, and even some of the more stochastic data sets may be irrelevant to your company’s performance. Data analysis strategies should prioritize significant changes that have a significant impact on your business.
Data analysis is at its best when it shows you the relationships between the sources of the data. Understanding the cause-and-effect relationships between your company’s policies and your company’s performance is the heart and soul of business intelligence. In order to provide the high-quality data you need to develop your business intelligence strategy, your data analysis process should focus on the relationships that are most important to your company.
High data quality is important to business intelligence. Having a high quality concentration of relevant data is essential to effective data visualization and a thorough understanding of your company’s performance. Following these tips can help ensure that your data mining and data analysis focus on high-quality data that is truly meaningful to your company’s performance.
Data Clairvoyance is dedicated to putting data science effectively to work for your company. Feel free to contact us and ask about how we can improve your business intelligence strategy.