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# Data Analysis|Definition & Meaning

## Definition

The **process** of cleansing, **converting,** and **modeling data** in order to find **relevant information** for **effective decisions** is known as **data analysis. Extracting** usable **insights** from data and **making decisions** based on that **analysis** is the **goal** of **data analysis.**

Every time we **weigh** the results of the **past** and the **potential outcomes** of the present when **faced** with a choice, we are **engaging** in a basic form of data analysis. It’s the method of **evaluating** possible **outcomes** and settling on a course of action.

## Visual Representation of Data Analysis

**Imagine** that you are **interested** in making a **cake** all by yourself. **Butter,** sugar, **milk,** and **cream** were some of the ingredients that went into the **making** of the cake that you baked. You used **10 percent butter, fifty percent** sugar, **thirty** percent milk, and ten **percent** cream in your **recipe.** The following pie **chart offers** a graphical **illustration** of the whole breakdown of the ingredient **distribution.**

**Imagine** that you want to whip up a **delicious ice** **cream shake** all by **yourself. Sugar,** milk, and **ice cream** were some of the **components** that went into making the **ice cream shake.** You used ten percent sugar, sixty **percent milk,** and thirty percent ice cream in the **recipe.** The **breakdown** of the **ingredient distribution** is **depicted graphically** in the **following** pie chart that you can see below this **paragraph.**

The **following** figure represents a **histogram** with **five** bars, each of **which** has the **height specified** for **different buildings** shown in the figure. The **beginning** of the **first** bar can be found at the **coordinates** [0, 1], the **beginning** of the **second** bar can be found at the **coordinates** [1, 2], and so on.

## What Steps Are Involved in Data Analysis?

The **definition** of data **analysis** is merely the first step in the process. We’ll now **examine** its **execution.** Collecting the all information, **processing** it, **studying** your data, and using it to **uncover patterns** and other **insights** are all parts of the data **analysis** process, often known as the data **analysis** phases. The steps involved in **data analysis** are as **follows:**

- Ask yourself why you’re
**conducting**this study, what kind of**information**you want to**employ,**and what data you intend to**evaluate**later on. - The next step is to
**gather information**from your various**sources**using the**needs**you’ve**already**defined as guides. Studies such as case studies,**polls, interviews, questionnaires,**onsite**observations,**and focus groups are also useful. The gathered**information**must be properly**arranged**before. - It’s time to tidy up the data you’ve
**collected**because not all of it will be**valuable.**In this step,**you’ll**clean up your data by**removing**blank lines, duplicates, and**simple mistakes.**The**information**must be**thoroughly cleaned**before it can be sent for**analysis.** - The next step, after
**obtaining**the results you sought, is to**analyze**them and**develop**viable next**steps**in light of what you’ve**learned.** - Data
**visualization**means**“showing**your**information graphically**so people can read it” You can**utilize**a variety of tools,**including charts, graphs, maps,**and**bulleted**lists.**Visualization**helps users**compare datasets**and see**relationships.**

## What Are the Many Forms of Data Analysis?

There are now four **main methods** of **data analysis** that are **widely** used in the **fields** of **science** and **business.** The following are:

- In order to
**answer**this**question**“Why did this**happen?”**is found in the**diagnostic**analysis. Experts use method analysis to find**patterns**in data by using what they’ve learned from**statistical**methods. In a perfect world, analysts would find**similar patterns**from the past and use the**solutions**they found to solve the**problems**they are facing now. - The answer to the
**question**“What is most**likely**to**happen?”**is given by**predictive**analysis. Analysts can guess what will**happen**in the future by looking for**patterns**in both**old data**and**current events.**Although there is no such**thought**as a**100%**accurate**prediction,**the chances are**better**if indeed the analysts have a large amount of**detailed data**as well as the**discipline**to look into it**thoroughly.** - When you
**combine**the**insights**from the other**types**of data**analysis,**you get**prescriptive**analysis. Sometimes**,**a problem can’t be solved with just one type of analysis. Instead, it**needs**more than one type of insight. - The question “
**What****happened?”**can be answered by**statistical**analysis. This analysis looks at how dashboards are used to collect,**analyze,**model, interpret, and show data.

## Methods for Analyzing Data

Some **professionals** don’t **distinguish** between **“data analysis methods”** and **“data analysis techniques.”** To make things even more **confusing,** people **sometimes** add the **“data analysis** **types**” that we’ve already talked about. Here, we want to make a clear **distinction** between the **different** kinds of **information analysis** and how they are used. Words, **symbols, visual representations,** and observations are all used in the **qualitative** data approach to obtain data. This approach does not make use of any **statistics.**

**Methods** such as **Content Analysis,** which **examines** both verbal and **behavioral** data, are among the most widely used qualitative research approaches. **Narrative Analysis** is a method for **processing information** obtained from sources such as **interviews, diaries,** and **surveys.**

Methods of **statistical data analysis** involve the **collection** and **transformation** of raw data into **numerical** data. For example, the mean, often known as the **average,** is a **statistical measure** that is **calculated** by dividing the total of a series of data by the total **number** of numbers in the set.

During the process, the **number** of persons in a sample is determined by selecting and **analyzing** a representative subset of the entire population. The obtained **results** are thought to be** typical** of the whole body, which allows us to hypothesize about the **dataset** or **demography**.

**Artificial intelligence** is currently on the rise and has already proven to be an invaluable tool in data analysis. **Techniques** of analysis similar to these include:

**Deep neural networks**and**artificial neural network****Machine learning**

## What Role Does Data Analysis Play in Research?

**Sorting** through data is a **significant** portion of a researcher’s job. That is what the word **“research”** really means. And even the most **dedicated researcher** can find it hard to keep up with the **constant flood** of information that comes with the **Information** Age. Therefore, **data analysis** is crucial in **transforming** such data into a more **precise** and useful form, **facilitating** the work of **researchers.**

Researchers can use a wide **range** of **diverse** tools, **including descriptive** **analysis, inferential** analysis, as well as **quantitative** analysis, thanks to data **analysis.**

**In the end,** data analysis** gives** academics better** information and** better** ways** to study and analyze this** information.**

## Example of Data Analysis

**Construct** a **pie chart** to **graphically** present the **twenty percent** of one **hundred.**

### Solution

We **have** to find the **20 percent** of **100. **So,

**20 percent of 100 = (20 /100 ) x 100**

** 20 percent of 100 = (0.2 ) x 100**

**20 percent of 100 = 20**

Thus, 20 **percent** of **100** is **20.**

The **blue region** of the pie chart **represents 20 percent** of 100 **while** the remaining **80 percent** is **represented** in the **yellow region.**

*All images/mathematical drawings were created with GeoGebra.*