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Data analysis can help predict the outcome of a situation or allow you to protect your organization against risk. As discussed in a previous blog post, analysis has many benefits including mitigating repetitive losses, lowering insurance premiums, and more.

We recognize that data analysis can be difficult, particularly for organizations with a lot of data and complex processes. In fact, an estimated 75% of organizations lack the technology or strategy to effectively use their data. That’s why we came up with this simple guide on the steps for data analysis.

Over the past few weeks we've been covering topics such as "6 Reasons Data is Key for Risk Management", "Why All Risk Managers Should Use Data Analytics", and "Data Analysis Steps for Risk Managers". Data has been deemed today's most valuable asset: the "oil of the digital era". Now, let’s delve into some types of analysis that may be particularly helpful for your organization or risk team.