Phases of Data Analysis

In all fairness, all six phases of data analysis are critical as none can exist without the other. For one to understand the problem to be solved, questions have to be asked, which is the first step. This will help me understand the challenge at hand, understand the current position and where an organization needs to be. It is a crucial step as it carries the weight of the entire process in that without it the process will lack an objective.

The next phase is to prepare accordingly regarding the questions asked. Collecting and choosing the appropriate way or tool to store the data is as important.

The collected and stored data then has to be processed accordingly. This process of data cleaning is as vital as well as it makes the vast pile of data easy to work with.

Analyzing the data to me is the parent or core part of the entire process as it is at this step I'll identify trends and relationships between data sets. This will highly influence and guide an organization to make relevant data-driven decisions.

The analyzed data needs to be shared with the relevant audience to offer guidance for decision-making. There are various tools with which the data can be made interesting through visualization. The data should tell a story of its own with the data analyst being the choreographer.

Once shared, it is now upon the organization or the relevant audience to act accordingly and make a decision to combat the challenge identified in the first phase.

It is my opinion then that the most important step is data analysis. This is because the first three phases all lead to this and the other two are entirely tied to this phase. It is the phase in which data is acted upon to identify trends that play a key role in data-driven decision-making.