With the wealth of information available to make organizational decisions, companies need trained professionals to sort through existing data. By organizing data, business analysts can use the right information for answering management questions, drawing conclusions to the data, and making informed decisions to predict future business outcomes.
Simply put…businesses need better data analysis to make better business decisions.
Key steps are involved in data analysis to help ensure your business obtains value from your data and avoid the risk of error.
Step 1: Set Goals and Asking the Right Question
Goal Setting is the first step in the data modeling procedure. It’s vital that understandable and measurable goals are established before any data analysis begins. To start this process, it is important to ask the right question. Data analysis is only as good as the goal you set and the question you ask. You must define a goal and then, ask a question so it is quantifiable and created to be measurable, clear, and concise. Often, this starts with the company determining KPIs or key performance indicators, which is as individual as the company that creates them.
For example, start with a clearly defined problem: “Our logistics costs have increased 20% in the last question”. Then, formulate a question to answer the problem like “Can the organization reduce logistics costs without compromising delivery times?”
Step 2: Decide what to measure and how to do it
For determining what to measure, you need to focus on what you want to solve, making sure to include any stakeholders in the decision. “How to measure” involves you determining your time-frame for the project, the data you will use (or collect) for the measurement, and deciding what factors should be included in the measurement. It is important that you choose the criteria you’ll use to analyze the data; this will help you determine the data you will need to collect and analyze later.
Step 3: Data Gathering
With a well-defined goal for data analysis based on your defined question, now it’s time to collect your data. First, decide what information can be used from available sources. Then, if you need to collect data, establish who you will collect from, what data you need, where you should collect the data, when to collect the data, and how you plan to do the data collection.
Step 4: Analysis of the Data
By this step, you should have a data-set to use for analysis. First, make sure you scrub your data, checking for duplicate, incomplete, or redundant information. Then, begin your data analysis by manipulating your information in multiple ways. Excel is a great tool for this process.
Step 5: Interpret Results
Now, it is time to interpret the information. As you move through the analysis process, make sure the data is answering your original question, helping you draw accurate conclusions, and determining if there are limitations to your data analysis.
Step 6: Predictive Analysis
A portion of your analysis may include Predictive Analysis, which uses statistical techniques and predictive modeling to analyze current and historical data. This step in the data analysis process can help you make predictions about future actions for your company.
Step 7: Action
Once you are satisfied with your data analysis, the next step is to use the results of your data to decide your next best course of action.
Conclusion
With organized steps in the data analysis process, your organization’s decisions can be backed by focused information. With practice, your data analysis allows for better, informed decision-making to help your company run more effectively.
Learn more about Data Analytics through DCTC’s Marketing program: Clicking here.
