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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 transactionsUsers 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:
Object-Oriented databaseHierarchical 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 calculationsWhen 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 DBMSSummary
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.
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In today’s business world, companies rely on third-party vendors for many different services. Such vendors may provide cloud-based software, infrastructure, and operational support daily. Third party vendors enable your company to save on costs, increase efficiency, and achieve growth. However, sharing business data with vendors also comes with its risks. According toWhat is Vendor Risk Management?
Vendor Risk Management – VRM, is the process of applying policies and procedures that govern third party access to your business data. Because vendors often need to access critical business information when providing their services, the systems they use can become a weak point for data breaches. Therefore, VRM ensures that such vulnerable points are secured from any possible risk factors. Many regulators across various industries now require a Vendor Risk Management Plan. Regulatory bodies also specify policies, programs, and due diligence when it comes to vendor management. There have been new guidelines put in place over the years with regards to how third-party vendors are managed. For example, The Payment Card Industry Data Security Standard (PCI DSS) put forward new guidelines that relate to the cloud in 2023. These guidelines cover how businesses should manage vulnerability and technical security when moving to the cloud. The EU’s GDPR guidelines also cover vendor management. Companies that outsource data processors when managing data are required to assess all technical controls during the process. And as far as security is concerned, the New York Department of Financial Services requires businesses to maintain a third-party provider for their security policy.Understanding third party Vendors
Third party vendors are primarily service providers who work together with businesses to help manage daily operations. These vendors come in many different capacities, ranging from SaaS providers to IaaS services. It’s important to understand who your vendors are, how their systems work, and the risks that are likely to occur against your business data during service provision. In most cases, vendors are IT suppliers who help your business improve performance via cloud-related services. Some of these vendors include: 1. SaaS 2. IaaS 3. PaaS Depending on the operations of your business, you may need a platform that can host your new mobile applications, websites, or other similar projects.The risks vendors pose to your systems
With each vendor you rely on to provide essential services, there comes a data security risk. Such risks can be mild, and others can be as significant as to disrupt your operations. Here are some common vendor risks you should be aware of: • Web security risks SaaS providers can expose you to web security risks such as SQL attacks and cross-site scripting. • DDoS attacks IaaS providers can fall prey to Distributed Denial of Service attacks. Such attacks lead to service disruptions, which can, in turn, leave your sensitive data vulnerable.10 Steps to a Vendor Risk Assessment Plan
An essential part of vendor risk management is to assess the risks that your company faces, after which you can act accordingly to mitigate such risks. Vendor risk assessment occurs in 10 distinct steps as follows: 1. Listing of the vendors you work with This step sounds easier than it is. Your business may be using an extensive network of vendors for many different services. Take time to focus on the essential third-party vendors and services that keep your business moving. 2. Assessment of the risks each vendor presents The next step is to assess the risks you face and identify the ones most critical to your operations. 3. A review of the information each vendor has access to Depending on the vendors you work with, each will have access to different types of information. You may wish to pay more attention to those who handle or can access Personal Identifiable Information and other sensitive data. 4. Identifying specific threats your business is exposed to List the dangers that each vendor exposes your business to. Some vendors may pose similar risks, while others may pose more extensive levels of risk. 5. Quantifying and rating each type of risk The next step is to assign each risk as a low, medium, or high risk. Ratings make it easier for you to categorize risk factors and to develop a plan of action. 6. Carrying out risk analysis Risk analysis involves multiplying the likelihood of a risk happening by the level of the threat itself. The analysis allows you to quantify the risk in dollar amounts or extent of disruption. 7. Developing a plan for risk response Once all risks are analyzed, you can determine a method for handling risks that may occur. For example, you may choose to accept, refuse, transfer, or mitigate. 8. Putting relevant controls in place Controls govern how data will be accessed, shared, and secured within your business. 9. Establishing a Service Level Agreement (SLA) An SLA specifies the controls that you put in place for vendors. SLAs ensure that third party service providers also align their risk strategy to fall in line with yours. 10. Continuous monitoring
In today’s business world, companies rely on third-party vendors for many different services. Such vendors may provide cloud-based software, infrastructure, and operational support daily. Third party vendors enable your company to save on costs, increase efficiency, and achieve growth. However, sharing business data with vendors also comes with its risks. According to The Ponemon 2023 Cost of a Data Breach Study , a data breach that occurs through a third-party source ends up costing over $13 for each compromised record. This means that data breaches arising from your vendor network are costlier and come with more extensive consequences. By implementing a vendor risk management program, you can keep your data protected and avoid costly disruptions to your operations.Vendor Risk Management – VRM, is the process of applying policies and procedures that govern third party access to your business data. Because vendors often need to access critical business information when providing their services, the systems they use can become a weak point for data breaches. Therefore, VRM ensures that such vulnerable points are secured from any possible risk factors. Many regulators across various industries now require a Vendor Risk Management Plan. Regulatory bodies also specify policies, programs, and due diligence when it comes to vendor management. There have been new guidelines put in place over the years with regards to how third-party vendors are managed. For example, The Payment Card Industry Data Security Standard (PCI DSS) put forward new guidelines that relate to the cloud in 2023. These guidelines cover how businesses should manage vulnerability and technical security when moving to the cloud. The EU’s GDPR guidelines also cover vendor management. Companies that outsource data processors when managing data are required to assess all technical controls during the process. And as far as security is concerned, the New York Department of Financial Services requires businesses to maintain a third-party provider for their security policy.Third party vendors are primarily service providers who work together with businesses to help manage daily operations. These vendors come in many different capacities, ranging from SaaS providers to IaaS services. It’s important to understand who your vendors are, how their systems work, and the risks that are likely to occur against your business data during service provision. In most cases, vendors are IT suppliers who help your business improve performance via cloud-related services. Some of these vendors include: Software-as-a-Service refers to the provision of essential programs that power your daily operations. Rather than purchasing and maintaining these programs in-house, SaaS allows you to access the platforms you need via the cloud. Most back-end work is done by the service provider, giving your employees and customers an easier time using the software available. Infrastructure-as-a-Service provides you with the equipment you need to run your business operations. By not having to deal with infrastructure purchases, you can save on costs while enjoying higher margins. For example, an IaaS provider can provide data storage, data center infrastructure, and other equipment to make your operations more efficient.Depending on the operations of your business, you may need a platform that can host your new mobile applications, websites, or other similar projects. Platform-as-a-Service Providers offer such platforms as a Launchpad (or extra capacity) for your chúng tôi each vendor you rely on to provide essential services, there comes a data security risk. Such risks can be mild, and others can be as significant as to disrupt your operations. Here are some common vendor risks you should be aware of:SaaS providers can expose you to web security risks such as SQL attacks and cross-site chúng tôi providers can fall prey to Distributed Denial of Service attacks. Such attacks lead to service disruptions, which can, in turn, leave your sensitive data chúng tôi essential part of vendor risk management is to assess the risks that your company faces, after which you can act accordingly to mitigate such risks. Vendor risk assessment occurs in 10 distinct steps as follows:This step sounds easier than it is. Your business may be using an extensive network of vendors for many different services. Take time to focus on the essential third-party vendors and services that keep your business chúng tôi next step is to assess the risks you face and identify the ones most critical to your operations.Depending on the vendors you work with, each will have access to different types of information. You may wish to pay more attention to those who handle or can access Personal Identifiable Information and other sensitive chúng tôi the dangers that each vendor exposes your business to. Some vendors may pose similar risks, while others may pose more extensive levels of chúng tôi next step is to assign each risk as a low, medium, or high risk. Ratings make it easier for you to categorize risk factors and to develop a plan of chúng tôi analysis involves multiplying the likelihood of a risk happening by the level of the threat itself. The analysis allows you to quantify the risk in dollar amounts or extent of chúng tôi all risks are analyzed, you can determine a method for handling risks that may occur. For example, you may choose to accept, refuse, transfer, or mitigate.Controls govern how data will be accessed, shared, and secured within your chúng tôi SLA specifies the controls that you put in place for vendors. SLAs ensure that third party service providers also align their risk strategy to fall in line with yours.Finally, you need a framework for continuously monitoring the vendor environment. This will ensure
What is System Integration Testing?
System Integration Testing is defined as a type of software testing carried out in an integrated hardware and software environment to verify the behavior of the complete system. It is testing conducted on a complete, integrated system to evaluate the system’s compliance with its specified requirement.
System Integration Testing (SIT) is performed to verify the interactions between the modules of a software system. It deals with the verification of the high and low-level software requirements specified in the Software Requirements Specification/Data and the Software Design Document. It also verifies a software system’s coexistence with others and tests the interface between modules of the software application. In this type of testing, modules are first tested individually and then combined to make a system. For Example, software and/or hardware components are combined and tested progressively until the entire system has been integrated.Why do System Integration Testing?
It helps to detect Defect early
Earlier feedback on the acceptability of the individual module will be available
Scheduling of Defect fixes is flexible, and it can be overlapped with development
Correct data flow
Correct control flow
Correct memory usage
Correct with software requirementsHow to do System Integration Testing
It’s a systematic technique for constructing the program structure while conducting tests to uncover errors associated with interfacing.
Correction of such errors is difficult because isolation causes is complicated by the vast expansion of the entire program. Once these errors are rectified and corrected, a new one will appear, and the process continues seamlessly in an endless loop. To avoid this situation, another approach is used, Incremental Integration. We will see more detail about an incremental approach later in the tutorial.
There are some incremental methods like the integration tests are conducted on a system based on the target processor. The methodology used is Black Box Testing. Either bottom-up or top-down integration can be used.
Test cases are defined using the high-level software requirements only.
Software integration may also be achieved largely in the host environment, with units specific to the target environment continuing to be simulated in the host. Repeating tests in the target environment for confirmation will again be necessary.
Confirmation tests at this level will identify environment-specific problems, such as errors in memory allocation and de-allocation. The practicality of conducting software integration in the host environment will depend on how much target specific functionality is there. For some embedded systems the coupling with the target environment will be very strong, making it impractical to conduct software integration in the host environment.
Large software developments will divide software integration into a number of levels. The lower levels of software integration could be based predominantly in the host environment,with later levels of software integration becoming more dependent on the target environment.
Note: If software only is being tested then it is called Software Software Integration Testing [SSIT] and if both hardware and software are being tested, then it is called Hardware Software Integration Testing [HSIT].Entry and Exit Criteria for Integration Testing
Usually while performing Integration Testing, ETVX (Entry Criteria, Task, Validation, and Exit Criteria) strategy is used.Entry Criteria:
Completion of Unit TestingInputs:
Software Requirements Data
Software Design Document
Software Verification Plan
Software Integration DocumentsActivities:
Based on the High and Low-level requirements create test cases and procedures
Combine low-level modules builds that implement a common functionality
Develop a test harness
Test the build
Once the test is passed, the build is combined with other builds and tested until the system is integrated as a whole.
Re-execute all the tests on the target processor-based platform, and obtain the resultsExit Criteria:
Successful completion of the integration of the Software module on the target Hardware
Correct performance of the software according to the requirements specifiedOutputs
Integration test reports
Software Test Cases and Procedures [SVCP].
Hardware Software Integration Testing
Hardware Software Integration Testing is a process of testing Computer Software Components (CSC) for high-level functionalities on the target hardware environment. The goal of hardware/software integration testing is to test the behavior of developed software integrated on the hardware component.
Requirement based Hardware-Software Integration Testing
The aim of requirements-based hardware/software integration testing is to make sure that the software in the target computer will satisfy the high-level requirements. Typical errors revealed by this testing method includes:
Hardware/software interfaces errors
Violations of software partitioning.
Inability to detect failures by built-in test
Incorrect response to hardware failures
Feedback loops incorrect behavior
Incorrect or improper control of memory management hardware
Data bus contention problem
Incorrect operation of mechanism to verify the compatibility and correctness of field loadable software
Hardware Software Integration deals with the verification of the high-level requirements. All tests at this level are conducted on the target hardware.
Black box testing is the primary testing methodology used at this level of testing.
Define test cases from the high-level requirements only
A test must be executed on production standard hardware (on target)
Things to consider when designing test cases for HW/SW Integration
Correct acquisition of all data by the software
Scaling and range of data as expected from hardware to software
Correct output of data from software to hardware
Data within specifications (normal range)
Data outside specifications (abnormal range)
Correct memory usage (addressing, overlaps, etc.)
Note: For interrupt testing, all interrupts will be verified independently from initial request through full servicing and onto completion. Test cases will be specifically designed in order to adequately test interrupts.Software to Software Integration Testing
It is the testing of the Computer Software Component operating within the host/target computer
Environment, while simulating the entire system [other CSC’s], and on the high-level functionality.
It focuses on the behavior of a CSC in a simulated host/target environment. The approach used for Software Integration can be an incremental approach ( top-down, a bottom-up approach or a combination of both).Incremental Approach
Incremental testing is a way of integration testing. In this type of testing method, you first test each module of the software individually and then continue testing by appending other modules to it then another and so on.
Incremental integration is the contrast to the big bang approach. The program is constructed and tested in small segments, where errors are easier to isolate and correct. Interfaces are more likely to be tested completely, and a systematic test approach may be applied.
There are two types of Incremental testing
Top down approach
Bottom Up approachTop-Down Approach
Starting with the main control module, the modules are integrated by moving downward through the control hierarchy
Sub-modules to the main control module are incorporated into the structure either in a breadth-first manner or depth-first manner.
Depth-first integration integrates all modules on a major control path of the structure as displayed in the following diagram:
The module integration process is done in the following manner:
The main control module is used as a test driver, and the stubs are substituted for all modules directly subordinate to the main control module.
The subordinate stubs are replaced one at a time with actual modules depending on the approach selected (breadth first or depth first).
Tests are executed as each module is integrated.
On completion of each set of tests, another stub is replaced with a real module on completion of each set of tests
To make sure that new errors have not been introduced Regression Testing may be performed.
The process continues from step2 until the entire program structure is built. The top-down strategy sounds relatively uncomplicated, but in practice, logistical problems arise.
The most common of these problems occur when processing at low levels in the hierarchy is required to adequately test upper levels.
Stubs replace low-level modules at the beginning of top-down testing and, therefore no significant data can flow upward in the program structure.Challenges Tester might face:
Delay many tests until stubs are replaced with actual modules.
Develop stubs that perform limited functions that simulate the actual module.
Integrate the software from the bottom of the hierarchy upward.
Note: The first approach causes us to lose some control over correspondence between specific tests and incorporation of specific modules. This may result in difficulty determining the cause of errors which tends to violate the highly constrained nature of the top-down approach.
The second approach is workable but can lead to significant overhead, as stubs become increasingly complex.Bottom-up Approach
Bottom-up integration begins construction and testing with modules at the lowest level in the program structure. In this process, the modules are integrated from the bottom to the top.
In this approach processing required for the modules subordinate to a given level is always available and the need for the stubs is eliminated.
This integration test process is performed in a series of four steps
Low-level modules are combined into clusters that perform a specific software sub-function.
A driver is written to coordinate test case input and output.
The cluster or build is tested.
Drivers are removed, and clusters are combined moving upward in the program structure.
As integration moves upward, the need for separate test drivers lessons. In fact, if the top two levels of program structure are integrated top-down, the number of drivers can be reduced substantially, and integration of clusters is greatly simplified. Integration follows the pattern illustrated below. As integration moves upward, the need for separate test drivers lessons.
Note: If the top two levels of program structure are integrated Top-down, the number of drivers can be reduced substantially, and the integration of builds is greatly simplified.Big Bang Approach
In this approach, all modules are not integrated until and unless all the modules are ready. Once they are ready, all modules are integrated and then its executed to know whether all the integrated modules are working or not.
In this approach, it is difficult to know the root cause of the failure because of integrating everything at once.
Also, there will be a high chance of occurrence of the critical bugs in the production environment.
This approach is adopted only when integration testing has to be done at once.Summary:
Integration is performed to verify the interactions between the modules of a software system. It helps to detect defect early
Integration testing can be done for Hardware-Software or Hardware-Hardware Integration
Integration testing is done by two methods
Big bang approach
While performing Integration Testing generally ETVX (Entry Criteria, Task, Validation, and Exit Criteria) strategy is used.
blog / Digital Marketing Discover the Best Ways to Leverage Influencer Marketing for Your Brand
Influencers and influencer marketing have become a significant part of marketing strategies across the world, but what is an influencer and influencer marketing, and why should you care about it? In this guide, we take you through everything you need to know about the topic.
Let’s get started by focusing on the question of what is an influencer. An influencer is an individual with the power to affect buying habits and decision-making of consumers due to their expertise and relationship with their audience. They have a large social media following and create content that generates significant engagement.The Importance of Influencers to Your Brand
Now that you know what is an influencer, let’s find out why you should consider working with an influencer for your brand.
Reach your target and undiscovered audience:
Knowing and reaching your target and potential audience is essential for successful marketing. As such, the social media presence and following of influencers help you connect with your ideal as well as the undiscovered audience.
Enhances brand awareness:
Influencers with a large and legitimate following have a high engagement rate and this helps increase your brand exposure.
Increases brand credibility and trust:
The influencers’ expertise in their domain is one of the main reasons behind their impact on their audience. Working with influencers can help you gain credibility among people, which will enable you to earn their trust.
Improved conversion rate:
Influencer promotion and review of your brand can influence purchase decisions and drive more people to your products and services.What is a Social Media Influencer?
Social media influencers are content creators with a large following and influence on social media platforms. These influencers build an established reputation by creating content on social media and showcasing their knowledge and credibility on a specific topic.What is Influencer Marketing?
Influencer marketing leverages influencers to endorse a product or service to a large audience. Its impact is profound and has become an increasingly popular marketing strategy for brands. Let’s take a look at some influencer marketing statistics collated by the Influencer Marketing 2023 report:
The number of influencer marketing-related service offerings globally grew by 26%, reaching 18,900 firms offering such services in 2023
Influencer marketing-focused platforms raised more than $800 million in funding in 2023
The influencer marketing industry was projected to grow to $16.4 billion in 2023How to Get Started with Influencer Marketing
Define your target audience:
Like any marketing strategy, defining and understanding your target market is critical.
Determine your goals and objectives:
Figure out your goals and objectives for undertaking influencer marketing. It is essential to have a clear vision of what you want to accomplish.
Find the right influencer:
what is an influencer
for your brand. Ideally, they should be trustworthy and relevant to your brand and have a significant reach and engagement rate. Make sure they are the right fit for your product or service according to your target audience.
Reach out to the influencer:
As influencers typically get many brand deals, reaching out and convincing them can be complex. Have a good pitch and plan in place. You can provide compensation such as commission and cash. It is also possible to offer them free products instead of monetary payment.
Create your marketing campaign:
You can either create a campaign for the influencer or give the influencer a creative license—with some instructions—to build content for your brand. Letting influencers create content can be a good option to get unique content that looks authentic and increases your brand credibility.
Finally, monitor the performance of the campaigns to see if your goals and objectives are met.
ALSO READ: How to Become an Influencer: A Guide to Mega Growth on Social MediaTypes of Influencers
Nano influencers like @youthsweets are new influencers who start their journey with a small number of highly engaged followers due to their expertise in niche areas. They have a following of 10,000 or fewer.
Micro-influencers like @tinasbeautytips have a considerably large following ranging from 10,000 to 100,000.
Credit: Tina Le (@tinasbeautytips) • Instagram
Macro influencers like @hyram have an audience size of 100,00 to one million.
Credit: Hyram (@hyram) Instagram
Mega influencers like @zoesugg have a super-large audience of at least one million followers. These influencers typically have a very high engagement and content visibility rate.
Credit: Zoë Sugg (@zoesugg) • InstagramHow Much do Influencers Cost?
Their rates are based on a number of factors, such as the demand for influencers in the market, the social media platform, reach, engagement, exclusivity, industry, and content. It also depends on how you pay them based on the marketing Return on Investment (ROI) by evaluating the campaign performance and impact. Some brands even offer influencers free products instead of monetary payment.How Much do Influencers Make Per Post?
According to InfluencerMarketingHub, here are some typical ‘per post’ rates charged by influencers on different social media:
Social Media Nano
$2,500+How to Find an Ideal Influencer?
Here are a few more tips on how to find an ideal influencer for your brand:
Research and list influencers who align with your goals and objectives
Check their engagement metrics
Look beyond their following/followers and focus on their content
Check the credibility and expertise of the influencer in your industry
Ensure their audience overlaps with your brand to potentially expand your customer baseLearning, the Emeritus Way
Now that you know what is an influencer and how essential it can be for your brand, it’s time to get started! Learn how to boost your engagement and sales with Emeritus’ digital marketing courses.
By Krati Joshi
Write to us at [email protected]
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.
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 managementManagement 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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