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A typical organization is divided into operational, middle, and upper level. The information requirements for users at each level differ. Towards that end, there are number of information systems that support each level in an organization.

This tutorial will explore the different types of information systems, the organizational level that uses them and the characteristics of the particular information system.

In this tutorial, you will learn the different Classification of Information.

Pyramid Diagram of Organizational levels and information requirements

Understanding the various levels of an organization is essential to understand the information required by the users who operate at their respective levels.

The following diagram illustrates the various levels of a typical organization.

Pyramid Diagram

Operational management level

The operational level is concerned with performing day to day business transactions of the organization.

Examples of users at this level of management include cashiers at a point of sale, bank tellers, nurses in a hospital, customer care staff, etc.

Users at this level use make structured decisions. This means that they have defined rules that guides them while making decisions.

For example, if a store sells items on credit and they have a credit policy that has some set limit on the borrowing. All the sales person needs to decide whether to give credit to a customer or not is based on the current credit information from the system.

Tactical Management Level

Tactical users make semi-structured decisions. The decisions are partly based on set guidelines and judgmental calls. As an example, a tactical manager can check the credit limit and payments history of a customer and decide to make an exception to raise the credit limit for a particular customer. The decision is partly structured in the sense that the tactical manager has to use existing information to identify a payments history that benefits the organization and an allowed increase percentage.

Strategic Management Level

This is the most senior level in an organization. The users at this level make unstructured decisions. Senior level managers are concerned with the long-term planning of the organization. They use information from tactical managers and external data to guide them when making unstructured decisions.

Transaction Processing System (TPS)

Transaction processing systems are used to record day to day business transactions of the organization. They are used by users at the operational management level. The main objective of a transaction processing system is to answer routine questions such as;

How printers were sold today?

How much inventory do we have at hand?

What is the outstanding due for John Doe?

By recording the day to day business transactions, TPS system provides answers to the above questions in a timely manner.

The decisions made by operational managers are routine and highly structured.

The information produced from the transaction processing system is very detailed.

Examples of transaction processing systems include;

Point of Sale Systems – records daily sales

Payroll systems – processing employees salary, loans management, etc.

Stock Control systems – keeping track of inventory levels

Airline booking systems – flights booking management

Management Information System (MIS)

Management Information Systems (MIS) are used by tactical managers to monitor the organization’s current performance status. The output from a transaction processing system is used as input to a management information system.

The MIS system analyzes the input with routine algorithms i.e. aggregate, compare and summarizes the results to produced reports that tactical managers use to monitor, control and predict future performance.

For example, input from a point of sale system can be used to analyze trends of products that are performing well and those that are not performing well. This information can be used to make future inventory orders i.e. increasing orders for well-performing products and reduce the orders of products that are not performing well.

Examples of management information systems include;

Sales management systems – they get input from the point of sale system

Budgeting systems – gives an overview of how much money is spent within the organization for the short and long terms.

Human resource management system – overall welfare of the employees, staff turnover, etc.

Tactical managers are responsible for the semi-structured decision. MIS systems provide the information needed to make the structured decision and based on the experience of the tactical managers, they make judgement calls i.e. predict how much of goods or inventory should be ordered for the second quarter based on the sales of the first quarter.

Decision Support System (DSS)

Decision support systems are used by senior management to make non-routine decisions. Decision support systems use input from internal systems (transaction processing systems and management information systems) and external systems.

The main objective of decision support systems is to provide solutions to problems that are unique and change frequently. Decision support systems answer questions such as;

What would be the impact of employees’ performance if we double the production lot at the factory?

What would happen to our sales if a new competitor entered the market?

Decision support systems use sophisticated mathematical models, and statistical techniques (probability, predictive modeling, etc.) to provide solutions, and they are very interactive.

Examples of decision support systems include;

Financial planning systems – it enables managers to evaluate alternative ways of achieving goals. The objective is to find the optimal way of achieving the goal. For example, the net profit for a business is calculated using the formula Total Sales less (Cost of Goods + Expenses). A financial planning system will enable senior executives to ask what if questions and adjust the values for total sales, the cost of goods, etc. to see the effect of the decision and on the net profit and find the most optimal way.

Bank loan management systems – it is used to verify the credit of the loan applicant and predict the likelihood of the loan being recovered.

Artificial intelligence techniques in business

Artificial intelligence systems mimic human expertise to identify patterns in large data sets. Companies such as Amazon, Facebook, and Google, etc. use artificial intelligence techniques to identify data that is most relevant to you.

Let’s use Facebook as an example, Facebook usually makes very accurate predictions of people that you might know or went with to school. They use the data that you provide to them, the data that your friends provide and based on this information make predictions of people that you might know.

Amazon uses artificial intelligence techniques too to suggest products that you should buy also based on what you are currently getting.

Google also uses artificial intelligence to give you the most relevant search results based on your interactions with Google and your location.

These techniques have greatly contributed in making these companies very successful because they are able to provide value to their customers.

Online Analytical Processing (OLAP)

Online analytical processing (OLAP) is used to query and analyze multi-dimensional data and produce information that can be viewed in different ways using multiple dimensions.

Let’s say a company sells laptops, desktops, and Mobile device. They have four (4) branches A, B, C and D. OLAP can be used to view the total sales of each product in all regions and compare the actual sales with the projected sales.

Each piece of information such as product, number of sales, sales value represents a different dimension

The main objective of OLAP systems is to provide answers to ad hoc queries within the shortest possible time regardless of the size of the datasets being used.

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What Is Dbms (Database Management System)? Application, Types & Example

What is DBMS?

Database Management System (DBMS) is software for storing and retrieving users’ data while considering appropriate security measures. It consists of a group of programs that manipulate the database. The DBMS accepts the request for data from an application and instructs the operating system to provide the specific data. In large systems, a DBMS helps users and other third-party software store and retrieve data.

DBMS allows users to create their own databases as per their requirements. The term “DBMS” includes the user of the database and other application programs. It provides an interface between the data and the software application. 

In this Database Management System tutorial, you will learn DBMS concepts like-

Example of a DBMS

Let us see a simple example of a university database. This database is maintaining information concerning students, courses, and grades in a university environment. The database is organized as five files:

The STUDENT file stores the data of each student

The COURSE file stores contain data on each course.

The SECTION stores information about sections in a particular course.

The GRADE file stores the grades which students receive in the various sections

The TUTOR file contains information about each professor.

To define DBMS:

We need to specify the structure of the records of each file by defining the different types of data elements to be stored in each record.

We can also use a coding scheme to represent the values of a data item.

Basically, your Database will have 5 tables with a foreign key defined amongst the various tables.

History of DBMS

1960 – Charles Bachman designed the first DBMS system

1970 – Codd introduced IBM’S Information Management System (IMS)

1976- Peter Chen coined and defined the Entity-relationship model, also known as the ER model

1980 – Relational Model becomes a widely accepted database component

1985- Object-oriented DBMS develops.

1990s- Incorporation of object-orientation in relational DBMS.

1991- Microsoft ships MS access, a personal DBMS, and that displaces all other personal DBMS products.

1995: First Internet database applications

1997: XML applied to database processing. Many vendors begin to integrate XML into DBMS products.

Characteristics of DBMS

Here are the characteristics and properties of a Database Management System:

Provides security and removes redundancy

Self-describing nature of a database system

Insulation between programs and data abstraction

Support of multiple views of the data

Sharing of data and multiuser transaction processing

Database Management Software allows entities and relations among them to form tables.

It follows the ACID concept ( Atomicity, Consistency, Isolation, and Durability).

DBMS supports a multi-user environment that allows users to access and manipulate data in parallel.

DBMS vs. Flat File

DBMS Flat File Management System

Multi-user access It does not support multi-user access

Design to fulfill the need of small and large businesses It is only limited to smaller DBMS systems.

Remove redundancy and Integrity. Redundancy and Integrity issues

Expensive. But in the long term Total Cost of Ownership is cheap It’s cheaper

Easy to implement complicated transactions No support for complicated transactions

Users of DBMS

Here, are the important landmarks from the history of DBMS:

Following are the various category of users of DBMS

Component Name Task

Application Programmers The Application programmers write programs in various programming languages to interact with databases.

Database Administrators Database Admin is responsible for managing the entire DBMS system. He/She is called Database admin or DBA.

End-Users The end users are the people who interact with the database management system. They conduct various operations on databases like retrieving, updating, deleting, etc.

Popular DBMS Software

Here is the list of some popular DBMS systems:

Application of DBMS

Below are the popular database system applications:

Sector Use of DBMS

Banking For customer information, account activities, payments, deposits, loans, etc.

Airlines For reservations and schedule information.

Universities For student information, course registrations, colleges, and grades.

Telecommunication It helps to keep call records, monthly bills, maintain balances, etc.

Finance For storing information about stock, sales, and purchases of financial instruments like stocks and bonds.

Sales Use for storing customer, product & sales information.

Manufacturing It is used to manage the supply chain and track the production of items. Inventories status in warehouses.

HR Management For information about employees, salaries, payroll, deduction, generation of paychecks, etc.

Types of DBMS

Types of DBMS

The main Four Types of Database Management Systems are:

Hierarchical database

Network database

Relational database

Object-Oriented database

Hierarchical DBMS

In a Hierarchical database, model data is organized in a tree-like structure. Data is Stored Hierarchically (top-down or bottom-up) format. Data is represented using a parent-child relationship. In Hierarchical DBMS, parents may have many children, but children have only one parent.

Network Model

The network database model allows each child to have multiple parents. It helps you to address the need to model more complex relationships like the orders/parts many-to-many relationship. In this model, entities are organized in a graph which can be accessed through several paths.

Relational Model

Relational DBMS is the most widely used DBMS model because it is one of the easiest. This model is based on normalizing data in the rows and columns of the tables. Relational model stored in fixed structures and manipulated using SQL.

Object-Oriented Model

Advantages of DBMS

DBMS offers a variety of techniques to store & retrieve data

DBMS serves as an efficient handler to balance the needs of multiple applications using the same data

Uniform administration procedures for data

Application programmers are never exposed to details of data representation and storage.

A DBMS uses various powerful functions to store and retrieve data efficiently.

Offers Data Integrity and Security

The DBMS implies integrity constraints to get a high level of protection against prohibited access to data.

A DBMS schedules concurrent access to the data in such a manner that only one user can access the same data at a time

Reduced Application Development Time

The cost of Hardware and Software of a DBMS is quite high, which increases the budget of your organization.

Most database management systems are often complex, so training users to use the DBMS is required.

In some organizations, all data is integrated into a single database that can be damaged because of electric failure or corruption in the storage media.

DBMS can’t perform sophisticated calculations

When not to use a DBMS system?

Although DBMS system is useful, it is still not suited for the specific task mentioned below:

Not recommended when you do not have the budget or the expertise to operate a DBMS. In such cases, Excel/CSV/Flat Files could do just fine.

For Web 2.0 applications, it’s better to use NoSQL DBMS


DBMS definition: A database is a collection of related data which represents some aspect of the real world

The full form of DBMS is Database Management System. DBMS stands for Database Management System. It is software for storing and retrieving users’ data by considering appropriate security measures.

DBMS Provides security and removes redundancy

Some Characteristics of DBMS are Security, Self-describing nature, Insulation between programs and data abstraction, Support of multiple views of the data, etc.

End-Users, Application Programmers, and Database Administrators are the type of users who access a DBMS

DBMS is widely used in Banking, Airlines, Telecommunication, Finance, and other industries

The four main DBMS types are 1) Hierarchical, 2) Network, 3) Relational, 4) Object-Oriented DBMS.

DBMS serves as an efficient handler to balance the needs of multiple applications using the same data

The cost of Hardware and Software of a DBMS is quite high, which increases the budget of your organization.

Different Types Of Economic Utility

Definition of Economic Utility

Economic Utility is the total satisfaction a consumer derives from consuming a product. In other words, it is the satisfying power of any good or commodity. For example, Mr. Vivek can go to his workplace by cycling or by car. He prefers cycling as he derives greater utility (both health-wise and cost-saving) from it.

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In the above example, the utility is not measured in numbers. When numbers come in to measure utility, we mostly use them to compare products.

Therefore economic utility is totally psychology. The utility of a given product may be different for every person based on the demands of the person.

A consumer/buyer usually purchases a particular product when he will derive some benefit/benefit by using the product. He believes that the use or consumption of the purchased goodwill fulfills his want. Utility depends on consumer demand. A consumer’s demand/want will be fulfilled on the basis of the amount of utility fulfilled by the product.

Types of Economic Utility

An economic utility can be broadly divided into four main types:





We will now discuss each form of utility in detail:-

1. Form

A utility is created by changing its form. Form utility is the value that the customer sees in the finished product. Every company tries to increase its form utility as the finished product is more useful to the consumer than the raw materials used to make it.

Companies always try to understand and analyze the target market segment. This will help the company to figure out what kind of product they should make.

For example

A company may use wood to make finished products like cabinets which will add significant value for the customers and thus increase the form utility.

Wood logs converted to furniture.

Wood pulp is used to make finished products like paper which add significant value to the customer in everyday life.

2. Place

The physical location for the availability of the product increases the attractiveness of the good to the consumers. So the place utility has more to do with the physical location of the product’s availability and the distribution channels.

For examples

If goods are sold in stores close to the buyer’s home or office, it will be convenient and efficient for the buyer.

Goods in store increase the utility of place.

3. Time

The availability of products and services when the customer needs them. The customer wants a good or service depending on the season and the weather conditions.

For examples

During the rainy seasons, umbrellas are very important, and their demand also increases. During the winter, the demand for warm clothes increases. Time utility increases when the product is easily available when the customer needs it.

Companies are increasing the time utility even more with e-commerce’s coming up with one-day or same-day delivery services. In this way, time utility increases as the customer gets a product when he needs it the most.

4. Possession

If a product is useful for multiple purposes, the possession utility of the product increases. Like when we buy a product for one use but use it for multiple purposes.

For example

we can use a vase for keeping flowers, as an item for decoration, or to keep cutleries.

Vase is used to keep cutleries or flowers.

Can we measure Economic Utility?

Consumers buy a product for different kinds of reasons. The price a buyer is ready to pay is the worth of the product. No buyer will be ready to pay more than the derived utility from the product.

For example

If I buy a television for ₹ 25,000, I derive a utility equivalent to the value of ₹ 25,000. Similarly, if I buy furniture for ₹ 5,000, I will derive utility equivalent to the amount I pay.

But many economists have not agreed with the above statement by Prof Marshall because the utility is different for different people, and it is completely personal and psychological.

A brand of a television set might fulfill my demand, but the same brand X might not satisfy the need of another person.


Therefore economic utility is the total satisfaction or usefulness a consumer derives by consuming the good. In other words, economic utility is how the consumer perceives a given product to fulfill its demand. As discussed, there are four different types of utility: Form, Place, Time, and Possession.

Form utility is the value a consumer sees in the final product. Place utility makes a good or service more easily available to the target customers. Time utility provides easy availability of a good or service when customers need or want it. And lastly, possession utility describes the benefits available to the customers from owning the product.

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This has been a guide to Economic Utility. Here we have discussed types of Economic Utility and their example to understand this topic in a better manner. You may also take a look at some of the useful articles here:

5 Different Types Of Raster

Introduction to Raster Data

Raster Data is the type of geospatial data that is used to geocode maps and fill in the information related to surface features. It can be a pixel, matrix or even collection of cell forming a picture in general term. The Satellite imagery and the layers are classified into Raster Data. Unlike Vector Data, this form of data represents the interior part of the feature. Vector Data forms the boundary of any geo feature, and Raster Data fills the feature with specific pixelation. Raster Data are more into storing temperature, elevation, depth and soil pH value related data. The colour contrast varies from. Location to location and also depends on various geographical features covering the area. Two types of Raster data are Discrete Raster Data and Continuous Raster Data.

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How does Raster Data Work?

As given in the above definition, each cell or the matrix act as a data container. They can be called the variables that store colour-specific information depending on the classification and nature of the geographic feature. In the Raster form of data, the map area is divided into several cells and a matrix. The area is equally distributed with the help of Rows and Columns. Each cell of the row and the column has some unique attributes that define the value.

Most of the raster data pixels are in a square or rectangular format, but other shapes like triangular or hexagonal are also possible. The whole imagery or datasheet contains all these uniquely filled cells and forms the Raster data. Raster spatial data structures are two-dimensional arrays; this means that the area that each cell grid represents can both be used to define map resolution and the number of cell grids to describe the spatial distribution. Single-pixel or a cell in the layer can only have one attribute being mapped to it. To handle more than one attribute, more data layers need to be created. These layers can be visualized as stacked, one on top of the other.

While working on any project, GIS Analysts and Technicians load the Raster data models from the serving source and then work on the geocoding and referencing part. Based on the Raster data’s reference, they further create the vector map objects that consist of point, line, and polygon. The data is stored in various file formats like Images (.IMG, .JPG, and . PNG file extensions), ESRI uses bit maps (.BMP, .BPW) and many more customized formats.

The Raster Data is the imagery form of the surface area where each pixel in the data describes the surface area.Camera Sensors are used to capture the features with the help of electromagnetic waves generated through the sensors. The data collected from these sensors are the measurements that are reflected using electromagnetic waves.

There are primarily two types of sensors, Active Sensors and Passive Sensors.Passive Sensorsin the satellite sensors that detect only the data emitted from the landscape or reflected from any other light source. Active Sensors emits their signal, and the sensors in the satellite measures what is reflected. SONAR and RADAR are perfect examples of this type of sensor.

Passive Sensor Active Sensor

Types of Raster Data

Raster Data is further classified into various types; they are:

Satellite Imagery

Digital Elevation Model(DEM)

Digital Orthophotos

Binary Scanned Files

Graphic Files

Let us study the above-mentioned types in details:

1. Satellite Imagery

The imagery is remotely sensed and collected data in the raster format. The image value in the pixel represents the light or energy that is emitted and reflected from the earth back to the satellite sensors, which collects the data. Various types of land use and hydrography features can be classified during image processing. The imagery generated through this method can be either in RGB format or in traditional black & white format.

 2. Digital Elevation Model (DEM)

DEM of Snow covered mountains

3. Digital Orthophotos

Digital Orthophoto is a type of aerial imagery or satellite imagery that is extracted using remote sensing techniques. It is said to the corrected and processed imagery where the camera tilts and terrain relief is removed. This imagery form is geometrically correct and used for the digitization of 2D models. The collection of these Orthophotos form a large sheet of imagery, also known as Google Earth imagery is the perfect example of this orthophoto.

4. Binary Scanned Files

Binary Images Showing the presence in black, grey and white

5. Graphic Files

In this format, the Maps, Photographs and Images can be stored as digital graphic files. The popular graphic files that we come across in our daily life are GIF (Graphic Interchange Format), TIFF (Tagged Image File Format), JPEG (Joint Photographic Experts Group) and PNG (Portable Network Graphics)

Advantages of Raster Data

Raster Datais the simplest form of data structures, and hence they are easy to use and understand by the Geographic Information Systems Workforce.

This data form can be used to do various spatial analysis.

The model maintains uniformity when it comes to size and shape due to matrix and multi-array like structure.

Comparatively to its vector counterpart, the technology is far cheaper and affordable.

This makes the data livelier and presentable due to the involvement of colour codes, and hence when pairing with vector models, it gives proper relatable information.


With the help of Raster data form, spatial data becomes valuable. Most of the organization that is into GIS domain refer to external raster data forms. Raster data is simple yet heavy to handle due to toa large amount of imagery related files. Unlike earlier days, RDMS and Systems have become robust to handle these large and heavy data models. Both the data types are crucial in the world of GIS, but Raster data is the most preferred one.

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Different Types Of Sql Functions

SQL, or Structured Query Language, is a programming language used for managing and manipulating relational databases. One of the most powerful features of SQL is the ability to use functions to perform various operations on the data in a database. In this article, we’ll discuss the different categories of SQL functions and provide code examples to help illustrate their use.

Aggregate Functions

Aggregate functions are used to perform calculations on a set of values and return a single result. Some of the most commonly used aggregate functions in SQL include −

COUNT() – Returns the number of rows in a table or the number of non-NULL values in a column

SUM() – Returns the sum of all non-NULL values in a column

AVG() – Returns the average of all non-NULL values in a column

MIN() – Returns the minimum value in a column

MAX() – Returns the maximum value in a column

Here’s an example of using the COUNT() function to find the number of rows in a table called “orders” −









And here’s an example of using the SUM() function to find the total cost of all orders in the table −









Scalar Functions

Scalar functions are used to perform calculations on a single value and return a single result. Some examples of scalar functions in SQL include −

LENGTH() – Returns the number of characters in a string

UPPER() – Converts a string to uppercase

LOWER() – Converts a string to lowercase

CONCAT() – Concatenates two or more strings together

ROUND() – Rounds a number to a specified number of decimal places

Here’s an example of using the UPPER() function to display the names of all customers in uppercase −









And here’s an example of using the ROUND() function to round the total cost of an order to two decimal places −











Date and Time Functions

SQL also provides a number of functions for working with date and time values. Some examples of date and time functions in SQL include −

NOW() – Returns the current date and time

CURRENT_DATE() – Returns the current date

CURRENT_TIME() – Returns the current time

YEAR() – Returns the year of a date

MONTH() – Returns the month of a date

DAY() – Returns the day of a date

Here’s an example of using the NOW() function to find the current date and time −






And here’s an example of using the MONTH() function to find the month of an order’s date −









String Functions

SQL also provides a number of string manipulation function. Some examples of string functions in SQL include −

LTRIM() – Removes the leading whitespace of the string

RTRIM() – Removes the trailing whitespace of the string

TRIM() – Removes both leading and trailing whitespace of the string

SUBSTRING() – Extracts a specific portion of a string

REPLACE() – Replaces all occurrences of a specified string with another string

Conditional Functions

SQL also provides a number of functions that perform different actions based on certain conditions. Some examples of conditional functions in SQL include −

CASE – evaluates a list of conditions and returns a result for the first condition that is met

IF – return a specified value if the condition is met, otherwise return another specified value

COALESCE – return the first non-null expression among multiple expressions.

Here’s an example of using the CASE function to assign a label to each order based on the total cost −











"price range"




Here’s an example of using the IF function to check the availability of stock of a product








Here’s an example of using the COALESCE function to display the primary phone number and the secondary phone number of a customer −











"Phone Number"




Logical Functions

SQL provides a set of logical functions that return a Boolean value, which can be either true or false. Some examples of logical functions in SQL include −

AND – Returns true if both the conditions are true

OR – Returns true if at least one of the conditions is true

NOT – Negates a boolean value

Here’s an example of using the AND function to find all customers who live in a specific city and have an account balance greater than a certain amount −









Conversion Functions

SQL provides a number of functions that can be used to convert data from one type to another. Some examples of conversion functions in SQL include −

CAST() – Converts a value from one data type to another

CONVERT() – Converts a value from one data type to another (This function is specific for some database vendors like SQL Server)

TO_DATE() – Converts a string to a date value

TO_TIME() – Converts a string to a time value

TO_TIMESTAMP() – Converts a string to a timestamp value

Here’s an example of using the CAST() function to convert a float value to an int −









"Integer Price"




Here’s an example of using the TO_DATE() function to convert a string to a date value −









"Formatted Order Date"




Window Functions

SQL provides a set of functions that can be used to perform calculations across a set of rows that are related to the current row. These functions are known as window functions. Some examples of window functions in SQL include −

RANK() – Assigns a unique rank to each row within a result set, based on the values in one or more columns

DENSE_RANK() – Assigns a unique rank to each row within a result set, based on the values in one or more columns, but does not leave gaps in the ranking sequence when there are ties

ROW_NUMBER() – Assigns a unique number to each row within a result set, based on the order specified in the ORDER BY clause of the function

Here’s an example of using the RANK() function to find the rank of each customer based on their account balance −





















Here’s an example of using the ROW_NUMBER() function to find the row number of each customer in the table −














"Row Number"




These are just a few examples of the many functions that SQL provides for working with and manipulating data in a relational database. Each category of functions serves its own unique purpose, and understanding when and how to use them can help to make working with SQL and relational databases more efficient and effective.


SQL functions are an incredibly powerful tool for working with and manipulating data in a relational database. In this article, we’ve discussed the different categories of SQL functions, including aggregate functions, scalar functions, date and time functions, string functions, and conditional functions, and provided examples of how they can be used. Understanding and being proficient in the use of these functions is an essential part of working with SQL and relational databases.

Types Of Seam With Fullness

The additional fabric used to cover the drape’s width and occasionally its height is known as “fullness.” A drape with more fullness has a richer appearance. It offers additional light and sound absorption as well as an increase in the depth of field that may be seen. How much fullness to add to a drape depends on its usage, style, and price range. If seams need to be “hidden” within the pleat, there is another thing to think about. The meaning of “fullness” is that it helps achieve proper fit and comfort and is done to create variation. Fullness is released by pleats, tucks, and gathers; darts are used to create flat patterns; and fullness gives clothing more adornment.

Types of Seam with Fullness

Following are the major terminologies used as types


Pleats are folds in clothing made at equal intervals on the yoke, sleeves, and waistband of skirts to release fullness. Pleats are made at the top and smoothly flow down the bottom of the fabric. A final pleat’s size is three times as large as the material needed to create it. They usually range in size from 2.5 to 5 cm. They can be employed as a style detail and cause eye movement.

Depending on the fabric chosen, a pleat has a different effect. The depth of the pleat is determined by the fabric’s weight and the desired look. Knife, Box, Inverted, Accordion, Sun Ray, Pinch, and Kick pleats are a few examples of the various pleat styles.

Ruffles and Frills

A ruffle is a fabric strip that has been trimmed or handled in a way that creates fullness. These are employed in order to embellish clothing. They can occasionally be used to lengthen the hems of skirts and dresses.

To create flare and add ornamentation, frills can be gathered or pleated and cut on a straight, bias, or circular axis. It is crucial to leave enough fullness for gathering, but how much should be left depends on the fabric type. They can be used to trim the neckline, wrists, and hem of a garment either individually or in tiers. Ruffles and frills are best made from light-weight, sheer fabrics.


A dart is a triangular fold that is crucial when manufacturing clothes. It contours a flat piece of cloth to fit the natural curves of the body’s bust, armholes, neckline, and waist. They are primarily used in clothing for women. They are essential when designing clothing and cannot be disregarded. In the process of making darts, the stitching should begin at the broad edge and travel toward the tip. Normally, darts are made before a garment is sewn. It aids in improving the fit of the clothing. Single-pointed darts and double-pointed darts are the two different varieties of darts.


A tuck is a fold in the cloth that is sewn down to give the garment more fullness. They should have an even width and aid in shaping a garment. Depending on whether the garment is used for ornamental or functional purposes, tucks can be done on either the right or wrong side of the garment. They produce a decorative accent that gives clothing more fullness. They appear more alluring when wearing exquisite and delicate fabrics. They ought to be separated equally. The various tuck styles include the pin, cross, piped, and shell tucks.


Gathers are used to distribute fullness evenly in a specific area. Depending on the desired impact, the material requirement can be adjusted to be twice as wide. Cotton that is stiff has a crisp look, whereas silk or any man-made fibre has a graceful one. Elastic, a machine, or a hand can be used to gather material. Using the sewing technique of “gathering,” a fabric strip can be made shorter so that it can be joined to a shorter piece. It is frequently used to manage fullness in clothes, such as when a full sleeve is attached to a shirt’s armscye or cuff or when a skirt is fastened to a body.


A godet is an additional piece of cloth sewn onto a garment, typically a dress or skirt, in the shape of a circular sector. When a godet is added, the item of clothing in question flares, adding width and volume. A godet gives a piece of clothing added range of motion for the wearer.


According to current fashion trends, flares can be added to skirts, sleeves, trouser legs, and other garments. To add diversity, you can change the degree of flare. For instance, an A-line skirt has the least amount of flare at the hem, while a circle skirt has the most. Bell sleeves have a modest flair, whereas circular sleeves have the most flare.

Shirring Gores

To create a fitted bodice or hip and a flared-out hem, gores can be added to a skirt, kameez, or top. The type and availability of the fabric, the grain, and the desired level of fullness for the hemline all affect how many gores are inserted. It can be anywhere from 4 and 12; either 6 in the front and 6 in the rear, or 2 in the front and 2 in the back. In order for gored skirts or dresses to drape properly, the grain line is crucial. In order to achieve a decent, uniformly distributed flare and an appropriate slant on the seams, the centre of the gore should be on the straight grain.


To sum up, fullness makes a cloth look appealing and helps it accommodate the body’s natural curves. The contour is shaped by darts. Any area of the garment can be made fuller by pleating, gathering, or tucking. The type of material determines the choice of fullness.

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