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KARNATAKA class 12 commerce Informatics Practices fast track revision notes

KARNATAKA class 12 commerce Informatics Practices fast track revision notes

KARNATAKA class 12 commerce Informatics Practices fast track revision notes:- we will provide complete details ofKARNATAKA class 12 commerce Informatics Practices fast track revision notes in this article.

KARNATAKA class 12 commerce Informatics Practices fast track revision notes

KARNATAKA class 12 commerce Informatics Practices fast track revision notes

Advanced Database Technologies

KARNATAKA class 12 commerce Informatics Practices fast track revision notes:-DATA WAREHOUSE AND DATA-MINING


The term data warehouse was coined with the definition of Inmon: “A warehouse is a subjectoriented, integrated, time variant and non-volatile collection of data in support of management’s decision making process” .

Characteristics of DW

  • Subject-oriented : Means that all relevant data about a subject is gathered and stored as a single set in a useful format. Information is presented according to specific subjects or areas of interest.
  • Time-variant : Means that the data warehouse contains a history of the subject, as well as current information. It may be long-term data from five to ten years in contrast to the 30 to 60 day time..
  • Non-volatile : Means stable information, Information is consistent; Data in the database is never over-written or deleted once committed.
  • Integrated : Stored in a globally acceptable fashion with consistent naming conventions, measurements, encoding structures, and physical attributes, though underlying operational systems store the data differently;

Data Warehouse Architecture:

  • Warehouse database server: Which is almost always a relational DBMS; rarely flat files.
  • OLAP servers:- Which may either be a ROLAP or MOLAP

    • Relational OLAP (ROLAP): Extended relational DBMS that maps operations on multidimensional data to standard relational operations.
    • Multidimensional OLAP (MOLAP): Special purpose server that directly implements multidimensional data and operations.
  • Clients:-The Users or the client of Data warehouses are various Query and reporting tools, Analysis tools and Data mining tools (e.g., trend analysis, prediction)

Processors in Datawarehouse server

  • MPP

    • Massively parallel processing, a computer configuration that is able to use hundreds or thousands of CPUs simultaneously.
  • SMP

    • Symmetric multi-processing is a computer configuration where many CPUs share a common operating system, main memory and disks. They can work on different parts of a problem at the same time.

Steps involved in creating a Data warehouse

  • Data extraction
  • Data cleaning, also called data cleansing or scrubbing,
  • Data transformation
  • Convert from legacy/host format to warehouse format
  • Load
  • Sort, summarize, consolidate, compute views, check integrity, build indexes, partition
  • Refresh
  • Propagate updates from sources to the warehouse


  • Data warehouses enhance end-user access to a wide variety of data.
  • Decision support system users can obtain specified trend reports, e.g. the item with the most sales in a particular area within the last two years.
  • Data warehouses can be a significant enabler of commercial business applications.

Data Mining

  • Definition

    • Data mining, the extraction of hidden predictive information from large databases
    • The nontrivial extraction of implicit, previously unknown, and potentially useful information from data” and “the science of extracting useful information from large data sets or databases”.
  • Techniques used in Data Mining: –

    • Artificial neural networks
    • Genetic algorithms
    • Decision trees
    • Nearest neighbor method
    • Rule induction

KARNATAKA class 12 commerce Informatics Practices fast track revision notes:-Procedures, Functions and Modules

Procedure: It’s a named unit of a group of program statement that performs a well defined task. This unit can be called from the calling program.

Role of Procedure:

Increase Reusability – Using same code again and again.

Modularization – Means to divide a Big program into small modules.

Types of General Procedure:

  1. Sub – A procedure performs a task and does not return a value. Private/Public Sub Procedure-Name( parameter list) Statements End Sub
  2. Function – A procedure performs a task and returns a value. Private/Public Function Function-Name( parameter list) Statements End Function

Call byVal and Call byRef:- The call byVal method copies the values of actual parameter into the formal parameters, ie. The procedure creates its own copy of argument values and then uses them. Only a copy of a variable is passed to the called procedure and if the procedure changes the value, the changes affects only the copy and not reflected back to the original variable itself.

Code Modules:- A module is a container in VB, that contain some variables, procedures and definition.

Three types of Modules are:

  • Form Module – Stores all the procedures and declarations pertaining to single form. Form modules are stored with .FRM extension.
  • Standard Module – Store general purpose code of the application, ie code and declaration that are not specific to a form. Standard modules are stored with .BAS extension.
  • Class Module – It stores the blueprint for user created custom object. Class modules are stored with .CLS extension.

Variable Scope: – The part of a program within which a variable is accessible, is known as its scope.

Three Variable Scopes are:

  1. Private Scope/ Local Scope – Variables declared within a procedure are in local scope.
  2. Module Scope – Variables available for all the procedures within that module.
  3. Public Scope / Global Scope – Variables declared with public statement and available to the application.

Static Variables: Local and Static variable differ by their life span. Static variables retain its value even after the procedure has finished executing.

KARNATAKA class 12 commerce Informatics Practices fast track revision notes:-DATABASE FUNDAMENTALS

Database Transaction:

A transaction is a logical unit of work(LUW) that must succeed or fail in its eternity. A user views a transaction as a logical sequence of read and write operations whereas The system views a transaction as a logical sequence of read and write operations.

Transaction Handling Issues:

A transaction can be handled in either of the following two ways:

  1. Serially ie. Serial Execution of transactions.
  2. Concurrently ie.Simultaneous execution of transactions.

Transaction Properties: To ensure data integrity, the database system maintains the following properties of a transaction termed as ACID properties.

  • Atomicity.
  • Consistency.
  • Isolation.
  • Durability.

Data Communication and DBMS:

What is Client /Server computing?

A client is any process that requests to the server for specific services.A server is a process that provides requests for the clients.Both clients and server can reside in the same computer or in different computers connected by a network.

The three components of Client/Server Architecture:

  • The Client or The Front End application.
  • The Server or The Back End Application.
  • The Communication Layer or Middleware.

Network Protocol for Data Communication:

A protocol means the rules that are applicable for a network.Protocol defines the standardized formats for data packets,techniques for detecting and correcting errors and so on.

There are various protocols that work on the network. TCP/IP (Transmission Control Protocol/internet protocol) is the native protocol of Internet.

TCP/IP is called as a reliable delivery protocol. The TCP layer of TCP/IP is used to verify that whatever was sent by sending machine is received intact by the destination.

The IP layer of TCP/IP determines the route for sending packets from sending machine to the receiving machine. Also it packs the messages into small network transportable packets called datagrams. (A datagram is a collection of the data that is sent as a single message.)

Distributed Databases:

The distributed database may be defined as a database stored and running on a collection of machines that do not have shared memory, yet looks its users like a single database on single computer.

Advantages of distributed databases:

  • Sharing.
  • Availability.
  • Reliability.
  • Incremental Growth.
  • Distributed Query/Parallel Evaluation.
  • Improved Performance.

Allocation of Data in Distributed Database:

A distributed database is broken up into logical units called fragments,which may be assigned for storage at various sites.also,certain data may be stored at more than one site ie. Replication of data.

In a distributed database there are various approaches of data allocation:

  • Centralized data at one location.
  • Partitioned or fragmented data.
  • Complete replication.
  • Selective replication.

Data Fragmentation:

Distributed database supports data fragmentation.

Data fragmentation can be in any of following Ways.

  • Horizontal Fragmentation.
  • Vertical Fragmentation.
  • Mixed Fragmentation.

Data Replication:

Data replication means storing some data at more than one site.

Data can be replicated in any of the following ways:

  • No replication.
  • Partial replication.
  • Full replication.

Advantages of distributed database:

  • Organizational structure.
  • Share ability.
  • Improved availability.
  • Improved reliability.
  • Local autonomy.
  • Improved performance.
  • Incremental Growth.
  • Local autonomy.

Disadvantages of distributed database:

  • Complexity.
  • Increased Cost.
  • Increased Security requirements.
  • Lack of Standards.

KARNATAKA class 12 commerce Informatics Practices fast track revision notes

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KARNATAKA class 12 commerce Informatics Practices fast track revision notes

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