How does data analytics function?

How Data Analytics Works — Step by Step

Here's how it generally works:

✅ 1. Data Collection

What occurs: Collect data from different sources such as websites, databases, sensors, customer interactions, or social media.

Tools: APIs, SQL, Google Analytics, CRM systems, spreadsheets.

Example: Collecting sales data from an online store.

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✅ 2. Data Cleaning (Data Preparation)

What it does: Eliminate errors, complete missing values, and normalize formats. Incomplete or dirty data may result in erroneous conclusions.

Tools: Excel, Python (Pandas), R, Power Query.

Example: Resolving inconsistent date formats or eliminating duplicates within a dataset.

What it does: Understand the feel of the data—summary stats, trends, and correlations.

✅ 4. Data Analysis & Modeling

What is done: Use statistical methods or algorithms to discover patterns, make predictions, or determine relationships.

Types:

Descriptive analytics: What occurred?

Diagnostic analytics: Why did it occur?

Predictive analytics: What will probably occur?

Prescriptive analytics: What must we do?

Tools: Python (Scikit-learn), R, Excel, SPSS, SAS.

Example: Predicting future sales with regression using past data.

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✅ 5. Data Visualization

What happens: Display the insights in graphs, charts, and dashboards to ensure they are intuitive to consume.

Example: Building a dashboard to illustrate monthly revenue trends.

✅ 6. Interpretation & Decision-Making

What happens: Convert insights into executable business strategies.

Product pricing

Customer segmentation

Marketing optimization

Operational improvement

Example: Identifying that an advertising campaign is more successful with email targeting and suggesting a change of strategy

Summary:

Data analytics operates by gathering, cleaning, exploring, analyzing, visualizing, and interpreting data to enable intelligent decisions.

It takes raw figures and turns them into actionable knowledge.

Would you prefer a visual infographic or flowchart of this process?

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