Meaning Of Gaming

What is Data Analytics?

Data Analytics is the process of examining raw data to uncover patterns, draw meaningful insights and support better decision making. It helps individuals and businesses understand past performance, monitor current trends and predict future outcomes.. Features of Data Analytics are

• Insight Generation: Helps identify trends, patterns and anomalies in data to make informed decisions.
• Predictive Capabilities: Uses historical and current data to forecast future outcomes and opportunities.
• Data Management: Involves building systems and tools to efficiently handle, process and analyze large volumes of data.

Process of data analytics

Data analytics is used in many fields like banking, farming, shopping, government and more. It helps in many ways:

• Helps in Decision Making: It gives clear facts and patterns from data which help people make smarter choices.
• Helps in Problem Solving: It points out what's going wrong and why making it easier to fix problems.
• Helps Identify Opportunities: It shows trends and new chances for growth that might not be obvious.
• Improved Efficiency: It helps reduce waste, saves time and makes work smoother by finding better ways to do things.

some important points

1. Data Collection : Data collection is the first step where raw information is gathered from different places like websites, apps, surveys or machines. Sometimes data comes from many sources and needs to be joined together. Other times only a small useful part of the data is selected.

2. Data Cleansing : Once the data is collected it usually contains mistakes like wrong entries, missing values or repeated rows. In this step the data is cleaned to fix those problems and remove anything that isn’t needed. Clean data makes the results more accurate and trustworthy.

3. Data Analysis and Data Interpretation: After cleaning the data is studied using tools like Excel, Python, R or SQL. Analysts look for patterns, trends or useful information that can help solve problems or answer questions. The goal here is to understand what the data is telling us.

4. Data Visualization: Data visualization is the process of creating visual representation of data using the plots, charts and graphs which helps to analyze the patterns, trends and get the valuable insights of the data. By comparing the datasets and analyzing it data analysts find the useful data from the raw data.

Methods of Data Analytics

There are two types of methods in data analytics which are mentioned below:

1. Qualitative Data Analytics

Qualitative data analysis doesn’t use statistics and derives data from the words, pictures and symbols. Some common qualitative methods are:

• Narrative Analytics is used for working with data acquired from diaries, interviews and so on.
• Content Analytics is used for Analytics of verbal data and behaviour.
• Grounded theory is used to explain some given event by studying.

2. Quantitative Data Analysis

Quantitative data Analytics is used to collect data and then process it into the numerical data. Some of the quantitative methods are mentioned below:

• Hypothesis testing assesses the given hypothesis of the data set.
• Sample size determination is the method of taking a small sample from a large group of people and then analysing it.
• Average or mean of a subject is dividing the sum total numbers in the list by the number of items present in that list.