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Data Management

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In our day-to-day life, it is important to handle lots of situations where we do need a proper arrangement and management of data. It’s always easier to access things in an arranged room than a messed one. Like this, arranged data helps us ease our accessibility and save our time. In this article we will learn about data management including data recording and data organization.


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What Does Data Management Mean?

  • Data can be defined as a set of or collection of names, figures and numbers that convey information. 

  • This information can be about anything. Data is generally made based on various observations and analysis. 

  • We can record data as well as organize data in different formats such as tables, charts, pictures, etc.


What is a Database?

  • A database can be defined as a set of data that is organized. Database is generally the collection of tables, schema and other entities. 

  • Data is basically organized to a reality model that supports processes that need  various information.


Why is Data Management Important?

  1. Data Management is Important to Minimize Errors:

  • Effective data management will always help us in minimizing potential errors and reducing the damages that is caused by bad data. 

  • The greater occurrence of various processes like drag and drop, copy-paste and linking of documents, the greater is the chance of data errors. Therefore, an effective data management strategy and data quality initiative will help in better control of the health of a business’ most valuable asset.

  1. Data Management Helps in Improving Efficiency :

  • If your data is properly managed, updated, and enhanced, the accessibility and the organizational efficiency of the data will increase exponentially. 

  • If the data is inaccurate, mismanaged then it can lead to the wastage of tremendous time and resources.

  1. Data Management Aids in Protection from Data Related Problems and Risks:

  • Security of data and proper data management is very essential as it helps in ensuring that the important data is never lost and the data is protected inside the organization.

  • Data security is an important part of data management as it protects employees and companies from various data thefts, losses and breaches.

  1. Data Management Helps in Improving the Quality of Data:

  • Better data management aids in improving data quality and data access. Therefore, better search results can be easily obtained in a company with better and faster access to the data of the organization’s, which can help in decision making.


What is Data Integration?

  • A database management system can be defined as a software application that interacts with other applications and the user and the database itself to analyze the data.

  • The main purpose of the Database Management System is to define, create, update and administer the databases.

  • It can be defined as the combination of technical and business processes that can be used to combine data from various sources into valuable and useful information. 

  • Isolation provides trusted data from various sources.

Suppose let’s take an example to illustrate how to record and how to organize data and what is their significance.


Solved Examples

For example: In a refugee camp, there were a total of 75 people of different age groups. A NGO came to sponsor food packets for them. But people in different age groups tend to take different types of food like the infants take milk while the adults take bread buns. The Management has to know the exact count of requirements for all the adults as well as the infants.

In the above case, asking each person about what they eat is impossible as it would consume a lot of time. We need to handle this situation in less time, how? This can be done by Data Management.


Here are the Steps to Manage Data:

The steps involved in data management are as follows -


Step 1: Recording the Data

The first step of data management is recording or in simple words collecting the data. Here, the table shows a total of 75 refugees, now you need to divide them into four groups of infants, kids, adults and of course old-age. Now take the count of each group.


Group

Total Number

Food Per Person

Infants (> 3 yrs)

10 infants

One milk carton

Kids

18 kids

Two bread buns and one milk carton

Adults

32 adults

Three bread buns

Old-aged

15 Old- aged

Four bread buns


Now we know the number of people who take milk and the number of people who take bread buns.


Step 2: Organization of Data

Followed by the recording, we know that the organization of data is done. Now, we need to arrange the data we have collected so that we can easily access the information from a much larger and arranged data. Above situations can be arranged in a better way. You can see one of the ways below:


Type of Food Available

Tally Marks Given Below

Total Number of People

Milk (Only for Infants)

IIIIIIIIII

10 people

Bread Buns

(For Adults & Old-aged)

IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII

47 people

Both Milk and Bread Buns

(For Kids)

IIIIIIIIIIIIIIIII

18 people


Here we used the symbol “I”  for every person making the choice and every fifth mark is used as a strike that is I = 1 and IIII equals 5. This method seems to be an effective way of representing data. Hence, data can be easily recollected whenever required.


Types of Data

Data handling methods can be performed based on the types of data. The data is generally classified into two types, such as:

  1. Qualitative Data

  2. Quantitative Data

Qualitative data can be defined as something that gives us descriptive information about something whereas quantitative data can be defined as something that gives numerical information about something. Here, the quantitative data can be further divided into two. They are discrete and continuous data. The discrete data can take only certain values for example whole numbers. The continuous data can take a value within the provided range.

FAQs on Data Management

1. What exactly is Data Management in the context of the CBSE Maths syllabus for 2025-26?

In the context of the CBSE Maths syllabus, Data Management (often called Data Handling) is the process of collecting, organising, representing, and interpreting numerical information to make it easier to understand and draw meaningful conclusions. It involves transforming raw, unorganised numbers into clear formats like tables and graphs.

2. What are the basic steps involved in managing data for a school project?

The process of handling data typically involves four fundamental steps:

  • Collection: Gathering information or observations from a source.
  • Organisation: Arranging the collected data systematically, often using a frequency distribution table and tally marks.
  • Representation: Displaying the organised data visually using graphs like bar graphs, pictographs, or pie charts.
  • Interpretation: Analysing the represented data to understand trends, make comparisons, and draw conclusions.

3. What are the common methods for representing data graphically in Maths?

In Maths, data can be represented in several visual ways to make it easy to understand. The most common methods include:

  • Pictograph: Represents data using images or symbols, where each symbol stands for a certain number of items.
  • Bar Graph: Uses rectangular bars of uniform width to show comparisons among different categories.
  • Histogram: Similar to a bar graph, but it is used to show the frequency of data within continuous intervals, so there are no gaps between the bars.
  • Pie Chart: A circular graph that shows the proportion of each category as a slice of a whole circle.

4. What are the main types of data you encounter in this chapter?

Data can generally be classified into two main types:

  • Quantitative Data: This is numerical data that can be measured or counted. Examples include the marks of students in a test, the height of players, or the number of cars passing a street.
  • Qualitative Data: This is descriptive, non-numerical data that deals with characteristics or qualities. Examples include favourite colours, types of pets, or feedback like 'good' or 'bad'.

5. Why is organising raw data in a table necessary before drawing a graph?

Organising raw data is a crucial step because unorganised data is just a jumble of numbers that is difficult to interpret. By arranging it in a frequency distribution table, we can quickly see:

  • The range of the data (highest and lowest values).
  • Which data points occur most or least frequently.
  • Patterns or trends that are not visible in the raw list.

This organisation makes the data ready for accurate graphical representation and meaningful analysis.

6. What is the most important difference between a bar graph and a histogram?

The key difference lies in the type of data they represent. A bar graph is used to compare distinct, separate categories (like favourite fruits or number of students in different classes), which is why there are gaps between the bars. In contrast, a histogram is used to represent data that is continuous and grouped into intervals or ranges (like the heights of students in the range 150-155 cm, 155-160 cm, etc.). Therefore, the bars in a histogram touch each other to show the continuous nature of the data.

7. How do you decide which type of graph is the best choice for a given set of data?

Choosing the right graph depends on what you want to show:

  • Use a pictograph for simple data to give a quick visual impression, especially for younger audiences.
  • Use a bar graph when you need to compare the values of several distinct categories against each other.
  • Use a pie chart when you want to show how different parts make up a whole, typically expressed as percentages.
  • Use a histogram when you have a large set of continuous data that can be broken down into intervals or bins.