Digital Marketing

Digital marketing is another form of online marketing. Digital marketing is marketing products in a digital way. It means to promote any product or brand using of websites, mobile devices, social media, search engines, and other similar mediums. Digital marketing became popular with the advent of the internet in the 1990s. Using the internet to get more traffic and get the best potential customers.

Digital marketing involves some of the same principles as traditional marketing and is often considered a new way for companies to approach consumers and understand their behavior. Companies often combine traditional and digital marketing techniques in their strategies.

Digital Marketing Mediums

Digital marketing mediums have evolved and continue to do so. The following are the most common mediums that companies can use to boost their marketing efforts. Most of the companies use multiple mediums to improve digital marketing.

1. Website Marketing

A website is the centerpiece of all digital marketing activities. It is a very powerful channel on its own, but it’s also the medium needed to execute a variety of online marketing campaigns. A website should represent a brand, product, and service in a clear and memorable way. It should be fast, mobile-friendly, and easy to use.

2. Pay-Per-Click (PPC) Advertising

Pay-per-click (PPC) advertising enables marketers to reach Internet users on a number of digital platforms through paid ads. Marketers can set up PPC campaigns on Google, Bing, LinkedIn, Twitter, Pinterest, or Meta (formerly Facebook) and show their ads to people searching for terms related to the products or services.

PPC campaigns can segment users based on their demographic characteristics (such as by age or gender), or even target their particular interests or location. The most popular PPC platforms are Google Ads and Meta Ads.

3. Content Marketing

The goal of content marketing is to reach potential customers through the use of content. Content is usually published on a website and then promoted through social media, email marketing, search engine optimization, or even PPC campaigns. The tools of content marketing include blogs, eBooks, online courses, infographics, podcasts, and webinars.

4. Email Marketing

Email marketing is still one of the most effective digital marketing mediums. Many people confuse email marketing with spam email messages, but that’s not what email marketing is all about. This type of marketing allows companies to get in touch with potential customers and anyone interested in their brands.

5. Social Media Marketing

The primary goal of a social media marketing campaign is brand awareness and establishing social trust. As you go deeper into social media marketing, you can use it to get leads or even as a direct sales channel. Promoted posts and tweets are two examples of social media marketing.

6. Affiliate Marketing

Affiliate marketing is one of the oldest forms of marketing, and the internet has brought new life to this old standby. With affiliate marketing, influencers promote other people’s products and get a commission every time a sale is made or a lead is introduced. Many well-known companies like Amazon have affiliate programs that pay out millions of dollars per month to websites that sell their products.

7. Video Marketing

YouTube is one of the most popular search engines in the world. A lot of users are turning to YouTube before making a buying decision, to learn something, read a review, or just to relax.

There are several video marketing platforms, including Facebook Videos, Instagram, and even TikTok to use to run a video marketing campaign. Companies find the most success with video by integrating it with SEO, content marketing, and broader social media marketing campaigns.

8. SMS Marketing

Companies and nonprofit organizations also use SMS or text messages to send information about their latest promotions or give opportunities to willing customers. Political candidates running for office also use SMS message campaigns to spread positive information about their own platforms. As technology has advanced, many text-to-give campaigns also allow customers to directly pay or give via a simple text message.

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Cyber Security

Cyber security are techniques generally set forth in published materials that attempt to safeguard the cyber environment of a user or organization. It manages the set of techniques used to save the integrity of networks, programs and data from unauthorized access. It refers to the body of technologies, processes, and it may also be referred to as information technology security. 

The security, which is designed to maintain the confidentiality, integrity and availability of data, is a subset of cyber security.

The field is of growing importance due to increasing reliance on computer systems, including smart phones, televisions and the various tiny devices that constitute the Internet of Things.  

WHY DO WE NEED CYBER SECURITY ?

The range of operations of cyber security involves protecting information and systems from major cyber threats. These threats take many forms. As a result, keeping pace with cyber security strategy and operations can be a challenge, particularly in government and enterprise networks where, in their most innovative form, cyber threats often take aim at secret, political and military assets of a nation, or its people. 

Some of the common threats are :

1. Cyber terrorism 

It is the innovative use of information technology by terrorist groups to further their political agenda. It took the form of attacks on networks, computer systems and telecommunication infrastructures.

2. Cyber warfare 

It involves nation-states using information technology to go through something another nations networks to cause damage. In the U.S. and many other people live in a society, cyber warfare has been acknowledged as the fifth domain of warfare. Cyber warfare attacks are primarily executed by hackers who are well-trained in use of benefit the quality of details computer networks, and operate under the favorable and support of nation-states. Rather than closing a targets key networks, a cyber-warfare attack may forced to put into a situation into networks to compromise valuable data, degrade communications, impair such infrastructural services as transportation and medical services, or interrupt commerce.

3. Cyber espionage 

It is the practice of using information technology to obtain secret information without

permission from its owners or holders. It is the most often used to gain strategic, economic, military advantage, and is conducted using cracking techniques and malware.

What Cyber Security Can Prevent

The use of cyber security can help prevent cyber-attacks, data breaches and identity theft and can aid in risk management. When an organization has a strong sense of network security and an effective incident response plan, it is better able to prevent and serious of these attacks. For example, end user protection defends information and guards against loss or theft while also scanning computers for malicious code.

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5th Generation Mobile Network (5G )

 5G is the 5th generation mobile network. It is a new global wireless standard after 1G, 2G, 3G, and 4G networks. 5G enables a new kind of network that is designed to connect virtually everyone and everything together including machines, objects, and devices.

5G wireless technology is meant to deliver higher multi-Gbps peak data speeds, ultra low latency, more reliability, massive network capacity, increased availability, and a more uniform user experience to more users. Higher performance and improved efficiency empower new user experiences and connects new industries. 5G is implemented by several companies within the mobile ecosystem.

5G is based on OFDM (Orthogonal frequency-division multiplexing), a method of modulating a digital signal across several different channels to reduce interference. 5G uses 5G NR air interface alongside OFDM principles. 5G also uses wider bandwidth technologies such as sub-6 GHz and mmWave.

 

Like 4G LTE, 5G OFDM operates based on the same mobile networking principles. However, the new 5G NR air interface can further enhance OFDM to deliver a much higher degree of flexibility and scalability. This could provide more 5G access to more people and things for a variety of different use cases.

5G will bring wider bandwidths by expanding the usage of spectrum resources, from sub-3 GHz used in 4G to 100 GHz and beyond. 5G can operate in both lower bands (e.g., sub-6 GHz) as well as mmWave (e.g., 24 GHz and up), which will bring extreme capacity, multi-Gbps throughput, and low latency.

 

5G is designed to not only deliver faster, better mobile broadband services compared to 4G LTE, but can also expand into new service areas such as mission-critical communications and connecting the massive IoT. This is enabled by many new 5G NR air interface design techniques, such as a new self-contained TDD subframe design.

How is 5G better than 4G?

There are several reasons that 5G will be better than 4G, 

1. 5G is a unified platform that is more capable than 4G

While 4G LTE focused on delivering much faster mobile broadband services than 3G, 5G is designed to be a unified, more capable platform that not only elevates mobile broadband experiences, but also supports new services such as mission-critical communications and the massive IoT. 5G can also natively support all spectrum types (licensed, shared, unlicensed) and bands (low, mid, high), a wide range of deployment models (from traditional macro-cells to hotspots), and new ways to interconnect (such as device-to-device and multi-hop mesh). 

2. 5G uses spectrum better than 4G

5G is also designed to get the most out of every bit of spectrum across a wide array of available spectrum regulatory paradigms and bands—from low bands below 1 GHz, to mid bands from 1 GHz to 6 GHz, to high bands known as millimeter wave (mmWave). 

3. 5G is faster than 4G

5G can be significantly faster than 4G, delivering up to 20 Gigabits-per-second (Gbps) peak data rates and 100+ Mbps average data rates.

4. 5G has more capacity than 4G

5G is designed to support a 100x increase in traffic capacity and network efficiency.

5. 5G has lower latency than 4G

5G has significantly lower latency to deliver more instantaneous, real-time access: a 10x decrease in end-to-end latency down to 1ms.

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Virtual Reality

Virtual Reality (VR) is a technology that creates a simulated, immersive environment that users can interact with using specialized devices such as head-mounted displays (HMDs), motion sensors, and handheld controllers. Virtual Reality (VR) technology aims to create a fully immersive experience that feels like you're actually inside a virtual world.

One example of how Virtual Reality (VR) technology can be used is in gaming. With Virtual Reality (VR) headsets and controllers, players can enter a fully immersive gaming environment where they can interact with virtual objects and characters in a more natural and intuitive way. For example, in a Virtual Reality (VR) game like Beat Saber, players use handheld controllers to slash through musical beats as they fly towards them, creating an immersive, interactive experience that feels like you're inside the game.

Virtual Reality (VR) technology is also used in other industries, such as healthcare and education. In healthcare, Virtual Reality (VR) technology can be used to simulate medical procedures and surgeries, allowing medical professionals to practice and refine their skills in a safe, controlled environment. In education, Virtual Reality (VR) technology can be used to create immersive, interactive educational experiences that supplement traditional classroom instruction, allowing students to explore historical or scientific concepts in a more engaging and memorable way.

Overall, Virtual Reality (VR) technology has the potential to revolutionize a wide range of industries and applications, from entertainment and gaming to education and healthcare, by creating fully immersive, interactive experiences that allow users to engage with virtual worlds in new and exciting ways.

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Blockchain

A Blockchain is just another type of database for recording transactions. The transaction is copied to all of the computers in a participating network. A blockchain is thus sometimes referred to as a 'distributed ledger'. Data in a blockchain is stored in fixed structures called 'blocks'. 

Blockchain Block Structure

The important parts of a block are: 

Header - which includes metadata, such as a unique block reference number, the time the block was created and a link back to the previous block 

Content (Body) - usually a validated list of digital assets and instruction statements, such as transactions made, their amounts, and the addresses of the parties to those transactions.

Given the latest block, it is possible to access all previous blocks linked together in the chain, so a blockchain database retains the complete history of all assets and instructions executed since the very first one - making its data verifiable and independently auditable. As the number of participants grows, it becomes harder for malicious actors to overcome the verification activities of the majority. Therefore the network becomes increasingly robust and secure. Indeed, blockchain solutions are being discussed as a potential means of protecting data from nuclear power stations, flood-defense mechanisms, and other critical infrastructure.

Blockchain Architecture

Type of Blockchain

1. Public Blockchain

2. Private Blockchain

Difference between Public and Private Blockchain

Like many other types of databases, blockchains can be public or private. 

Private Blockchains, on the other hand, are networks where the participants are known "a priori" and have permission to update the ledger. Participants may come from the same organization or from different organizations within an industry sector where the relationships between them are governed by informal arrangements, formal contracts, or confidentiality agreements. 

The Bitcoin network is public because anyone can read or write data from or to the ledger if they are running the appropriate Bitcoin software. 

In the absence of trust, public blockchains typically require additional mechanisms to arbitrate disputes among participants and protect the integrity of the data. This involves added complexity because there is no central authority to arbitrate in a decentralized network. 

In the Bitcoin blockchain, for example, new transactions can only be added to the blockchain after a participant on the network solves a complex mathematical problem, known as a 'proof-of-work'. This process is called 'mining'. The effort miners have to expend on finding a solution to this mathematical problem acts as a sign that the transactions are valid, even though the miners may not know one another. 

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Internet of Things (IoT)

Internet of Things (IoT) refers to a collection of managed and platform services across edge and cloud that connect, monitor and control billions of IoT assets. It also includes security and operating systems for devices and equipment, along with data and analytics that help businesses to build, deploy and manage IoT applications. When discussing the Internet of Things, we consider how these services work together across three components:

1. Things

The physical objects or things, such as industrial equipment, devices or sensors, that connect to the cloud persistently or intermittently.

2. Insights

Information collected by the things, which is analyzed and turned into actionable knowledge either by people or AI.

3. Actions

The way people respond to those insights and connect them to their business, as well as the systems and tools they use.

Advantages of Internet of Things(IoT)

Internet of Things (IOT) facilitates several advantages in our daily lives. Some of its advantages are given below,

Minimize human effort

As IoT devices interact and communicate with each other, they can automate the tasks helping to improve the quality of a business’s services and reducing the need for human intervention.

Save time 

By reducing the human effort, it saves a lot of our time. Saving time is one of the primary advantages of using the IoT platform.

Enhanced data collection

Information is easily accessible, even if we are far away from our actual location, and it is updated frequently in real-time. Hence these devices can access information from anywhere at any time on any device.

Improved security

If we have an interconnected system, it can assist in the smarter control of homes and cities through mobile phones. It enhances security and offers personal protection.

Efficient resource utilization

We can increase resource utilization and monitor natural resources by knowing the functionality and how each device works.

Reduced use of other electronic equipment

Electric devices are directly connected and can communicate with a controller computer, such as a mobile phone, resulting in efficient electricity use. Hence, there will be no unnecessary use of electrical equipment.

Use in traffic systems

Asset tracking, delivery, surveillance, traffic or transportation tracking, inventory control, individual order tracking, and customer management can be more cost-effective with the right tracking system using IoT technology.

Useful for safety concerns

IOT is helpful for safety because it senses any potential danger and warns users. For example, GM OnStar is an integrated device that identifies a car crash or accident on the road. It immediately makes a call if an accident or crash is found.

Useful in the healthcare industry

Patient care can be performed more effectively in real-time without needing a doctor’s visit. It gives them the ability to make choices as well as provide evidence-based care.

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Quantum Computing

Quantum Computing is a new technology trend that holds great promise for solving complex problems that are difficult or impossible for classical computers to solve. Quantum computers operate on the principles of quantum mechanics, which allows them to perform calculations using quantum bits or qubits, rather than classical bits.

One example of how Quantum Computing can be used is in the field of drug discovery. Drug discovery is a complex process that involves identifying potential drug candidates and then testing their efficacy and safety. With Quantum Computing, researchers can perform highly complex calculations and simulations that would be too difficult or time-consuming for classical computers, allowing them to more quickly and accurately identify promising drug candidates.

Another example of how Quantum Computing can be used is in the field of cryptography. Quantum computers can perform calculations that can break many of the encryption methods used to protect sensitive information, such as credit card numbers and passwords. However, Quantum Computing can also be used to develop new forms of encryption that are resistant to quantum attacks, which will be crucial in the future as Quantum Computing becomes more powerful.

Overall, Quantum Computing is an emerging technology trend that has the potential to revolutionize a wide range of fields and industries, from drug discovery and cryptography to finance and logistics. As Quantum Computing technology continues to evolve, it will be exciting to see the new applications and innovations that emerge.

There are several types of Quantum Computing currently being researched and developed. Here are some of the most common types:

Quantum Annealing: This type of Quantum Computing is designed for optimization problems, such as finding the shortest path between multiple points. Quantum annealing uses a process of gradual cooling to settle on the optimal solution.

Quantum Circuit-based Computing: This type of Quantum Computing uses quantum circuits to perform calculations. It is similar to classical computing, but with qubits instead of classical bits. Quantum circuit-based computing is being developed for a variety of applications, including cryptography, simulation, and machine learning.

Topological Quantum Computing: This type of Quantum Computing is based on the manipulation of non-local properties of particles, such as their topology. It is a relatively new and untested approach to Quantum Computing, but has the potential to be highly robust against errors.

Quantum Simulation: This type of Quantum Computing is designed to simulate complex systems that are difficult or impossible to simulate using classical computers. Quantum simulation has applications in fields such as chemistry, materials science, and condensed matter physics.

Quantum Communication: This type of Quantum Computing involves using quantum states to transmit and process information. Quantum communication has the potential to be highly secure, as it is difficult to intercept or copy quantum states without disturbing them.

Overall, Quantum Computing is an exciting and rapidly evolving field with many different approaches and applications. As research and development continue, it is likely that new types of Quantum Computing will emerge.

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Robotic Process Automation (RPA)

RPA is the use of software to automate business processes such as interpreting applications, processing transactions, dealing with data, and even replying to emails. RPA automates repetitive tasks that people used to do. 

RPA can be used to automate repetitive tasks both in the back office and front office that require human intervention. Some common RPA examples are automation of data entry, data extraction and invoice processing. 

Robotic Process Automation (RPA) applications

1- Data updates

Most departments including HR, customer service and marketing routinely need to update customer/personnel data which is constantly changing. Setting up bots for auto updating relevant data from forms or email can ensure that departments can access fresh and correct data.

2- Data validation

Most data validation controls can be embedded in databases. However, there’s data validation tasks such as cross checking data against publicly available data, for which RPA automation is more suitable than other tools.

3- Extracting data from PDFs, scanned documents and other formats

Screen scraping, OCR (Optical Character Recognition) and basic pattern recognition technologies enable data extraction from almost any format, reducing the need for keying in data. Feel free to review a data driven list of machine learning powered solutions. These can be easily integrated to RPA solutions to extract data and process documents.

4- Periodic report preparation and dissemination

Every business requires regular reports to inform managers and ensure teams are aware of their progress. Preparing such reports and sending them over every week or month is not labor intensive but it distracts employees.  RPA can help to automate periodic reporting. RPA solutions can easily auto-generate reports, analyze their contents and based on the contents, email them to relevant stakeholders.

For example, a telecom operator report showing areas with connectivity issues has different recipients based on its severity. CTO should be copied in reports with critical issues and head of network should be copied in reports with major issues. RPA bots can analyze reports to modify recipients according to provided criteria.

5- Data migration and entry

Legacy systems still perform critical functions at companies. For example, legacy billing systems need to interface with other systems and such systems may not have the capability to pull relevant data from APIs. In such cases, employees manually migrate data using formats like CSV. RPA can prevent such manual labor and potential clerical errors it brings.

Furthermore such systems that keep data up to date enable improved analysis and decision making. We are living in a day when even marketing has 5000 applications to choose from. RPA can help integrate applications and allow for more holistic analyses.

6- Generating mass emails

Mass emails relying on data from multiple systems are painful to produce manually. Especially if you are sending them frequently, consider automating the process.

7- Creating and delivering invoices

This is a case of data replication. Same sales data needs to exist in both CRM and accounting systems. Instead of manual data replication, bots can update accounting records, prepare and deliver invoices from the right email accounts.

8- Updating CRM

Updating interactions to CRM is time consuming and unproductive yet necessary. Because Salesforce acts needs to act as the source of truth regarding customer interactions. There is an emerging class of solutions that allow companies to integrate their email, call and other communication data to CRM. If you can not find a good solution for the CRM system you are using, you could write a simple bot to update your CRM records with customer contact data.

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Machine Learning (ML)

Machine Learning (ML) is an important component of the growing field of data science. Through the use of statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects. These insights subsequently drive decision making within applications and businesses, ideally impacting key growth metrics. As big data continues to expand and grow, the market demand for data scientists will increase, requiring them to assist in the identification of the most relevant business questions and subsequently the data to answer them.

Machine Learning (ML) applications

Below are just a few examples of machine learning you might encounter every day,

Speech Recognition 

It is also known as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, and it is a capability which uses natural language processing (NLP) to process human speech into a written format. Many mobile devices incorporate speech recognition into their systems to conduct voice search—e.g. Siri—or provide more accessibility around texting.

Customer Service  

Online chatbots are replacing human agents along the customer journey. They answer frequently asked questions (FAQs) around topics, like shipping, or provide personalized advice, cross-selling products or suggesting sizes for users, changing the way we think about customer engagement across websites and social media platforms. Examples include messaging bots on e-commerce sites with virtual agents, messaging apps, such as Slack and Facebook Messenger, and tasks usually done by virtual assistants and voice assistants.

Computer Vision 

This AI technology enables computers and systems to derive meaningful information from digital images, videos and other visual inputs, and based on those inputs, it can take action. This ability to provide recommendations distinguishes it from image recognition tasks. Powered by convolutional neural networks, computer vision has applications within photo tagging in social media, radiology imaging in healthcare, and self-driving cars within the automotive industry. 

Recommendation Engines 

Using past consumption behavior data, AI algorithms can help to discover data trends that can be used to develop more effective cross-selling strategies. This is used to make relevant add-on recommendations to customers during the checkout process for online retailers.

Automated stock trading 

Designed to optimize stock portfolios, AI-driven high-frequency trading platforms make thousands or even millions of trades per day without human intervention.

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Artificial Intelligence (AI)

Artificial Intelligence (AI) is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.

Artificial Intelligence (AI) applications

There are numerous, real-world applications of AI systems today. Below are some of the most common examples:

Speech Recognition: 

It is also known as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, and it is a capability which uses natural language processing (NLP) to process human speech into a written format. Many mobile devices incorporate speech recognition into their systems to conduct voice search—e.g. Siri—or provide more accessibility around texting. 

Customer Service:  

Online chatbots are replacing human agents along the customer journey. They answer frequently asked questions (FAQs) around topics, like shipping, or provide personalized advice, cross-selling products or suggesting sizes for users, changing the way we think about customer engagement across websites and social media platforms. Examples include messaging bots on e-commerce sites with virtual agents, messaging apps, such as Slack and Facebook Messenger, and tasks usually done by virtual assistants and voice assistants.

Computer Vision: 

This AI technology enables computers and systems to derive meaningful information from digital images, videos and other visual inputs, and based on those inputs, it can take action. This ability to provide recommendations distinguishes it from image recognition tasks. Powered by convolutional neural networks, computer vision has applications within photo tagging in social media, radiology imaging in healthcare, and self-driving cars within the automotive industry. 

Recommendation Engines: 

Using past consumption behavior data, AI algorithms can help to discover data trends that can be used to develop more effective cross-selling strategies. This is used to make relevant add-on recommendations to customers during the checkout process for online retailers.

Automated stock trading: Designed to optimize stock portfolios, AI-driven high-frequency trading platforms make thousands or even millions of trades per day without human intervention.

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