The Three Basic Steps of the Analysis Process

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Analysis Process

When a business is looking to make the most of its data, there are three basic steps that must be followed. These are preparation, analysis, and reporting.

The first step is to define the problem or question that you’re trying to answer with data. This helps you focus on the most important elements of your research, and it also makes it easier to see where you might be stuck.


Preparation is the process of cleaning and transforming raw data before it can be used for business analysis. This includes reformatting and validating data, removing duplicates and errors and combining datasets for enrichment.

Data preparation is essential because businesses rely on analytics to gain a better understanding of their operations and customer needs. If your data is not clean, you can’t be sure that it will provide the insights that are needed for good business decisions.

Data preparation involves many steps, including data profiling and identifying the right analytics use cases. It also includes resolving differences between data from different source systems.


Analyzing is the process of breaking a complex topic into smaller pieces to gain a better understanding of it. This is a technique that has been used in the study of mathematics and logic for centuries, though it is only relatively recently that analysis has become a formal concept.

The first step in the analysis process is determining what data you need to analyze and how it will be collected. This will help you narrow down your objectives so that you can choose the best data sources for your project.

Depending on your objectives, you may need to gather first party data (data that you collect directly from your customers), second party data (data that you obtain from third parties), or both.

Regardless of the type of data you are collecting, you need to make sure that it is clean and free from any errors or inconsistencies. This will help you ensure that your results are accurate and relevant.


Reporting is the step that transforms raw data into digestible information for business users. It can range from a simple Excel file or data visualization tool to a formal deliverable.

This step is important in driving value as it provides an overview of the data. In addition, it offers a foundation for developing a plan of action.

Another important step of analysis is to develop recommendations. The results of analysis help answer critical questions that drive decisions (go/no go/explore further) and ultimately value.

The first step of analysis is to define the problem. Having a clear problem statement ensures that all the data and results are relevant to solving it. A properly-defined problem also makes it easier to follow the right path and avoid dead ends.


The evaluation step of the analysis process involves collecting data about program implementation and hypothesized effects. It also involves analyzing those data to produce a description of what happened and convincing explanations of why it occurred.

Several different kinds of evaluations can be used to evaluate programs, including program evaluation, process evaluation, and impact evaluation. Each kind of evaluation is designed for a specific purpose and with a specific goal in mind.

For example, program evaluation would be used to measure the effectiveness of a program that aims to make people healthier or prevent disease. It might also be used to determine whether a program helps people learn more, get a job, or stop using drugs.

A good way to evaluate a project is to start the evaluation early in the planning process, when the goals of the project are clearly defined. This way, you will be able to establish measurement criteria that are consistent and reliable. You will also be able to identify areas where new or revised data collection procedures are needed.