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Informatics PracticesClass 11Understanding Chapter Data

Understanding Chapter Data | Class 11 Informatics Practices Notes

By ConceptScroll Team · Published on 17 July 2026 · 4 min read

Understanding Chapter Data – this guide gives you a concise, exam-ready overview of Understanding Chapter Data from Class 11 Informatics Practices, written by ConceptScroll editors and reviewed against the latest NCERT textbook.

5.1.2 Types of Data

Data can be classified into two broad categories based on their format: structured data and unstructured data. Structured data is organized and recorded in a well-defined format, typically in rows and columns (tabular form). Each column represents an attribute or variable, and each row represents an observation. For example, a shop's inventory data listing model numbers, product names, unit prices, discounts, and quantities is structured data. Such data can be easily processed using spreadsheet software to perform calculations like total inventory or total value. Other examples include book records with attributes like title, author, price, and publication year; school fee deposits with student details and payment information; and ATM withdrawal records with account holder and transaction details. In contrast, unstructured data lacks a fixed format or structure. Examples include newspaper pages with varying layouts of text, images, and advertisements; email content with variable length and attachments; web pages combining text and multimedia; social media posts; audio and video files; and business reports. Unstructured data is more challenging to process and often requires metadata—data about data—to describe its components. For instance, metadata for an email includes subject, recipient, and attachments; for an image, metadata includes file size, type, and resolution. This chapter focuses primarily on handling structured data due to its simplicity in processing and analysis.

📊 Diagram: Table 5.1 shows structured data of kitchen items with columns ModelNo, ProductName, Unit Price, Discount(%), and Items_in_Inventory. Table 5.2 lists attributes maintained for different activities like books, fee deposits, and ATM withdrawals. An activity (Activity 5.1) asks students to observe voter identity cards to identify data fields.

🧪 Activity: Activity 5.1: Observe Voter Identity cards of family members to identify data fields and check if they are the same for all.

🔗 Connection: Understanding data types leads to the next section on how data is collected from various sources.

Frequently asked questions

1. Identify data required to be maintained to perform the following services: a) Declare exam results and print e-certificates b) Register participants in an exhibition and issue biometric ID cards c) To search for an image by a search engine d) To book an OPD appointment with a hospital in a specific department

a) Data required: Student details (name, roll number, exam scores, grades), exam results data, certificate templates, digital signatures for e-certificates. b) Data required: Participant details (name, contact info, photo), biometric data (fingerprints, iris scan), registration details, ID card templates. c) Data required: Image metadata (tags, descriptions, file names), image content data (pixels, features), user query data, indexing data. d) Data required: Patient details, hospital department

2. A school having 500 students wants to identify beneficiaries of the merit-cum means scholarship, achieving more than 75% for two consecutive years and having family income less than 5 lakh per annum. Briefly describe data processing steps to be taken by the school to prepare the list of beneficiaries.

Data processing steps: 1. Data Collection: Collect student academic records for the last two years and family income details. 2. Data Validation: Verify accuracy of marks and income data. 3. Data Filtering: Select students with more than 75% marks in both years. 4. Income Filtering: From filtered students, select those with family income less than 5 lakh per annum. 5. Compilation: Prepare the final list of beneficiaries. 6. Reporting: Generate reports or certificates for the selected students.

3. A bank ‘xyz’ wants to know about its popularity among the residents of a city ‘ABC’ on the basis of number of bank accounts each family has and the average monthly account balance of each person. Briefly describe the steps to be taken for collecting data and what results can be checked through processing of the collected data.

Steps for data collection: 1. Define data requirements: Number of bank accounts per family, average monthly balance per person. 2. Sampling: Select representative families from city ABC. 3. Data Collection: Use surveys, bank records, or interviews to gather data. 4. Data Validation: Check for accuracy and completeness. 5. Data Processing: Analyze data to find average accounts per family, average balances.

Results that can be checked:

  • Popularity of bank xyz based on number of accounts.
  • Avera
4. Identify type of data being collected/generated in the following scenarios: a) Recording a video b) Marking attendance by teacher c) Writing tweets d) Filling an application form online

a) Recording a video: Unstructured data (video files). b) Marking attendance by teacher: Structured data (attendance records). c) Writing tweets: Semi-structured data (text with hashtags, mentions). d) Filling an application form online: Structured data (form fields with defined formats).

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