[MUSIC] There are four aspects to our framework. Outcomes, decisions and actions, insights, and discovery. Beyond the emptied mind and walk our way backwards to define the problem and analysis to redact. And each of the four aspects we takes steps to ensure time to value from data analytics. During the discovery phase you need to define the problem, develop a hypothesis and collect and explore data. During insights, you perform the data analysis. Next comes actions where you link insights to actionable recommendations and an execution plan. Finally, you review the outcomes that have transformed the business or business unit or the industry. We start from business outcomes to define the problem we are trying to solve. We often look at the questions that need to be answered or the key issues that need to be addressed. The metrics that need to be factored. This allows us to not only define the problem but also state our hypothesis on how we are going to impact the outcomes. Once we determine the outcomes to be achieved, we look at the decisions that the executives need to make, or the actions that employees need to take. This allows us to identify the critical dependent variables, decisions or actions, or the output required to make the right decisions and actions. Based on the complexity of the problem and the time available we look at different techniques that can be used to generate those insights. This typically starts with first understanding what has happened so far, what the organization has done, and how they can do it in the future, in order for us to help influence key decisions and actions. Once we have the techniques that will generate the insights, we can look for the right data that is available. The data could be internal or external to the organization. It can also be structured or unstructured. Most offered the data available, the time available to obtain the data but influence the techniques that we could potentially use for insight generation. Well, this is an iterative process. It is always better to start from the outcomes and the hypothesis as opposed to the available data to generate the best value from data and analytics. So let's recap the data analytics framework. During the discovery phase you define the problem, develop a hypothesis, and collect and explore data. During insights you perform the data analysis. Actions is where you link insights to actionable recommendations and then execution plan. Finally you review the outcomes of long term objectives and solutions. This framework allows us to move through data analysis in an organized way and provide us with the process to follow as we work with clients to solve a problems. In the next video, I'm going to talk about the types of analysis you can perform and show you the tools that you can use within the data analytics framework. [MUSIC]