Six Steps of Data Analysis Process

GREATER NOIDA, India - March 4, 2025 - PRLog -- Steps for the Data Analysis Process:

Step 1: Define the Question

In the first phase of the process, the data analysis is assigned a problem/business job. The analyst must grasp the task and the stakeholder's expectations for the solution.

Step 2. Data Collection

The second phase is to prepare or collect data. This process entails collecting and storing data for future analysis. The analyst must collect data from numerous sources in accordance with the assignment assigned.

– First-party data refers to data obtained by an individual using their own resources.
– Data acquired and sold is referred to as second-party data.

Step 3: Cleaning the data

This implies cleaning, or'scrubbing' it, which is critical for ensuring that you're working with high-quality data. Important data cleansing tasks include:

– Eliminating severe errors, duplication, and outliers — all of which are unavoidable issues when combining data from many sources.
– Eliminating unnecessary data points — extracting useless observations that have no influence on the intended analysis.

Step 4: Analyzing the data

Finally, you have cleared your data. Now comes the fun part: analyzing it! The type of data analysis you perform is primarily determined by your goals. But there are numerous techniques accessible.

Step 5. Data Visualization

The fifth phase is visualizing the data. Nothing is more captivating than a visualization. The altered data must now be represented visually. The reason for creating data visualizations is that there may be people, primarily stakeholders, who are not technical. Visualizations are created to simplify the interpretation of complex data.

Step 6. Presenting the Data

Presenting data is putting raw information into a format that is easily understandable and meaningful to many stakeholders. This technique includes creating visual representations, such as charts, graphs, and tables, to effectively communicate patterns, trends, and insights derived from data analysis.

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Conclusion:

In this article, we reviewed the key processes in the data analytics process. These essential processes can be modified, rearranged, and reused as needed, but they serve as the foundation for all data analysts' work.

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