The continuous investment in technology by businesses is on the rise. Different business software emerge every day to satisfy the market most appropriately. Below are the current software trends taking the business industry by storm.

1. Cloud Computing:

Cloud computing enables businesses to acquire quality services for production with little infrastructure. Companies are shifting to this technology due to the simple requirements to access efficient business services.

Software as a service, platform as a service, and infrastructure as a service are technologies from cloud computing. One requirement to getting these services is access. Business staff only need computer devices with an internet connection to utilize the resources.
What are the advantages of cloud computing?

• Secure
  Storing company data in cloud computing technology is secure and reliable. Only authorized personnel can access the data through procedures.

  The data is backed up frequently and is hard to access since it is off-site. Any attack is immediately detected and measures taken.

• Easy Access
  Accessing your business services over cloud computing reduces the necessity of diverse applications and a physical computer for operations. Almost all services necessary for a business function are accessed here.

  Physical location is never a factor here since a worker from one point of the globe can collaborate with his peers on the other side of the world.

• Backup data recovery
  Cloud storage never stores a company’s data in one location. The information is spread and encoded. An inbuilt system for recovering data is always available with protection.

2. Artificial Intelligence (AI) and Machine Learning (ML):

Businesses today use data to make meaningful insights and decisions. Since companies acquire a lot of data, it is becoming difficult to make vital decisions. Certain decisions need analyzing bulk data and making crucial decisions in a short period.

Since human labor can’t achieve this, Artificial Intelligence provides a solution to tackle the challenge. Referred to as business intelligence, AI uses machine learning algorithms to study patterns and come up with analysis to make business decisions.

3. Internet of Things (IoT):

The Internet of Things is helping companies improve customer experience. It offers automatic solutions across multiple industries for production, management, and marketing activities. Business operations are smoother and easier to handle with this technology. IoT collects and analyzes data and then communicates using physical internet-connected devices. What are the impacts of IoT on businesses?

• Lower Cost:  IOT provides data in real time through automatic processes on tasks that are used to consume resources and time. For instance, in manufacturing industries, sensors are attached to equipment to provide their output rate and maintenance information. The real-time data influences business operators to respond to tasks efficiently and quickly to avoid losses and damage.

• Smoother working conditions:   It can monitor, manage, and inform staff on business operations. The ability to automate manual tasks with minimum error influences a smooth workflow within the staff. Commercial businesses install vehicles with sensors that monitor routes, fuel consumption, and vehicle conditions.

• Business Insights:  The Internet of Things provides data to organizations that use it to understand market conditions. From this, they can react quickly to areas needing improvement or change. Using this technology enables businesses to spend little time marketing their products since they invest in advance.

• Customer Experience: Companies use IOT technology to collect client data using patterns. The information provides more on customer behavior and preferences. Producing goods and services fulfilling customer needs becomes easy for manufacturers.

4. Robotic Process Automation (RPA):

Robotic Process Automation is a technology that simplifies the creation, deployment, and software bots management. The software bots operate similarly to humans by interacting and communicating with digital systems.

Any business owner having a user account on the RPA software can create bots that learn, understand, and implement business operations according to instructions set by the business owner. The software bots use abilities like intelligence, vision, and automation to fulfill tasks assigned. 

Their character is suitable to handle bulk repetitive human tasks. Software bot’s work rate is high and accurate compared to human performance by a margin. RPA software robots operate in different modes based on abilities set and goals set by designers. They include:

• Attended RPA  – Attended RPA software bots to work alongside humans by assisting with tasks in real-time. These types of bots perform tasks depending on the user instructions set. The user triggers the bots on when, what, and how to operate through a button.

• Unattended RPA – These types of bots are in full control right after the completion of their design. They require no human intervention since users state their instructions during their development. The bots have self-control while performing assigned tasks since they have procedures to approach in different situations. RPA software bots often work in virtual devices and run in the background.

• Hybrid RPA – This type of bot software contains both unattended and attended RPA protocols. The hybrid RPA bots can execute specific tasks automatically, and in other cases, they require human involvement.

• Cognitive RPA –It is an intelligence type of RPA software bot inclusive, of artificial intelligence, machine learning, natural language processing, and computer vision. It uses knowledge-based techniques to perform complex tasks and can adapt to changes.

• API generated RPA – The application programming interface initiates this type of bot software to perform tasks. The API enables the software bots to interact and exchange data with different applications.

                                                                                       Real-life application of RPA

Multiple industries globally are adopting robotic process automation technology quicker than expected. Repeatable tasks no longer pose a threat to businesses thanks to automation abilities. Below are examples of business tasks well implemented by the RPA process.

1. Data Transfers – Relocating high volumes of data from one system to another is a difficult task when done by humans. It would need revision to identify any errors and it is time and resource-consuming.It is easy to design and instruct an RPA bot that understands the requirements to migrate the data.

2. System setup – A staff needing to access the company’s resources like devices, systems, and email does not need to get approved by any office. The process remains constant regardless of any staff because RPA bot software can automate the procedure efficiently.

3. Payroll Process – RPA bot software can generate payslips automatically while including complex factors like bonuses, expenses, and cuts. The bots can extract the necessary information required in bank transactions. The process is quick and automatic without the need for human inclusion. The process is repetitive and is suitable for high-volume staff.

4. Online Orders Processing – E-commerce companies can implement RPA bots to automate tasks like finding useful information about products to clients. The bots also find it easy for customers to track orders and improve deliveries. Handling customer service is easy when using bot software to interact and engage with customers on arising issues.

As more industries and businesses adopt ARP technologies to find their full potential, we learn the importance and diverse roles in improving business services.

5. Big Data Analytics:

What is Big Data Analytics? It is the protocol of studying high volumes of data to identify factored market insights, style, and influence. Data analytics technology gives companies a heads-up on the varying conditions witnessed in markets.

Company staff feed queries from different sources into data analytic tools to get insights and learn the business movement and performance. Big data analytics influences business operations, customer experience with preferences, and market explorations.The influence of Big Data Analytic tools on businesses depends on three conditions they meet while in operation. They include:

High Volume Data – It manages the massive data flow from sources like, social media, websites, sensors, etc. Its ability to handle this attribute depends on resources like cloud storage or distributed file systems.

Velocity – It is the speed at which the data analytics tools collect, process, and analyze large data volumes. Rapid data analytics techniques are essential for proximity and accuracy in real-time operations while applying stream processing and in-memory databases. 

Variety – The Big Data analytics process involves scanning different data types that may come in diverse forms. The data might not be well organized and structured for smooth operations. The analytic tools require a Natural Language Process and sentiment analysis technologies for clear insights. 

How do Big Data Analytics tools work?

The function handled by Big Data Analytic tools is studying the complex data structure provided and establishing meaningful insights for business operations. How do they achieve this? , these tools work in organized phases to fulfill a specific task. The phases work as follows,

Data Collection – The first step of the process is collecting data from sources we learned earlier. The data can be of any format, message, image, or video. 

Data Storage – The collected data is then organized, processed, and stored in the data warehouse. The data warehouse is a relational database purposely for analysis and querying. Professionals arrange and section the data for analytical queries. The process can be either batch processing, where high-volume data is received and analyzed over time. On the other hand, it can take the stream processing form, where smaller data sets are analyzed in real-time, accelerating the speed of analysis.

Data Cleaning and Preprocessing – The collected data is likely inconsistent, lacks missing content, has duplicates, or contains an error. Using data quality software, responsible parties clean the raw information. Data cleaning occurs by spotting and correcting mistakes to produce accurate information. The preprocessing task involves transforming the data into an utilizable format for analysis.

Data Analysis – There are various techniques analysts use to analyze the prepared data. They aim to uncover the correlations, trends, patterns, and insights that can offer valuable business concepts or solve specific problems.Techniques analysts use in this phase include:

• Machine learning algorithms
• Deep learning
• Data Mining
• Predictive modeling
• Text Mining 
• Statistical analysis
• Artificial Intelligence
• Data Visualization

Visualization and Interpretation – Insights analysts obtain from the analysis phase are released in a visible form. The different forms they use are graphs, charts, dashboards, etc. The aim of this phase is representation to stakeholders and involved parties, for better understanding.

Decision Making – From the information analysts present, organizations digest and agree on suitable decisions. The decisions are to help the company improve customer services and operations, optimize processes, develop new products, and have a competitive edge.

How is Big Data Analysis efficient in business decisions?

Choices companies make based on Big Data analysis are data-driven choices. Analysts use this technology to extract meaningful concepts from unstructured data. So, how efficient is Big Data Analysis?

We earlier learned how this technology works. We can see that the data used in this technology is the market behavior interpretation. The raw data is often complex and unclear, making it hard for companies to absorb and understand directly. Moreover, making business decisions nowadays requires solid principles based on facts that this technology applies. For Big data analysis to be efficient it applies the following:

Real-time intelligence – It is quick enough to absorb large data and process the results in time for business implementation.
Cost efficiency – Big Analytic tools do not require adding more resources for implementation which are easy to access and use.
Accuracy – It improves the unstructured data it collects to provide meaningful concepts.
Uses risk management strategies – It addresses business challenges in real-time to avoid losses and risks.

6. Cybersecurity:

Cybersecurity is an ICT term used to express the security concern on computer infrastructure. Digitally connected businesses use this technology to protect their sensitive data from unauthorized access.
Unauthorized access, referred to as cyber-attacks, is witnessed in different ways. Each style of attack aims to exploit vulnerabilities in digital systems. The different styles of cyber attacks are:

• Malware attack
• Phishing Attacks
• Database manipulation
• Fileless attacks

Implementing cybersecurity in your business ensures confidence, integrity, and efficiency in operations. To achieve the best out of cybersecurity, you must apply these aspects:

Prevention – A concept used to avoid unauthorized access to your business data.
Detection – Identifying the vulnerabilities and potential threats in your business system or network.
Response – Action you take to eliminate threats found in your systems or networks.

                                                     Importance of Cybersecurity in Your Business
Protecting Sensitive data – Businesses contain critical data that can damage operations if used against the business. Examples of sensitive information include customer details, business transactions, financial records, and proprietary intellectual property. In the wrong hands, such information can lead to financial loss or reputation damage.

Customer Trust – When you enable reliable cybersecurity measures, your business intrigues confidence in your customers, making them trust your business. Trusting their data in your systems, they always transact at ease with your business.

Financial Implications – You should be aware of the financial repercussions witnessed by cyber attacks. Costs associated with these breaches include compensation to affected parties, legal fees, regulation levies, and the charges involved when recovering affected systems.

Smooth Business Operations – Cyber attacks often damage business systems and networks, affecting their operations. Ensuring resilient measures to cyber attacks ensures smooth, continuous business operations.

Competition Edge – Without resilient cybersecurity measures, a business can spend resources and time to counterattack the threats. In such a scenario, your business does not operate to its full potential and experiences low sales and losses. Applying appropriate measures, your business can instead use these resources on more important issues.

7. Blockchain:

Blockchain is a decentralized ledger technology that records business transactions transparently. Its database stores transaction data in blocks connected through chains. The connection uses cryptographic techniques which are continuous and unalterable.

Blockchain has characteristics that make it reliable in diverse industries. These characteristics include:

• Decentralization: The ledger technology operates by multiple users to maintain it collectively.
• Immutability: Once a transaction is recorded and added to the blockchain, no entity can alter or delete the transaction.
• Transparency: Security in the blockchains is maintained through cryptographic hashing, enabling the integrity of transactions. All participants within the chain can view the transaction history.

                                                                                What are Blocks in Blockchain?

Blocks are the basic units of the blockchain. Each block contains a list of verified transactions added to a blockchain network. When adding blockchains to a network, invalidators solve complex cryptographic puzzles to validate them. Once this process is completed, the block becomes permanent. 

                                                                              Structure of a Block

Block header – This is an 80-byte field containing the data about the block. The data has a unique identifier, timestamp, and a reference of the previous block.

Transactions – They are the information about business resources transferred from one peer to another.

                                                                            Application of Blockchains

Cryptocurrencies like Bitcoin and Ethereum are common examples of blockchain implementation. They are virtual coins consisting of data that show their value and codes that show how to spend the virtual coin. The technology is not only used in financial activities but in industries such as real estate, supply management, healthcare, voting, etc.

8. Chatbots and Virtual Assistants:

A chatbox is a computer program that simulates human conversations, either verbally or written. On the other hand, virtual assistants are programs that help users with different tasks. These two technologies work together to enhance customer experience.
Chatbots handle initial queries, but if they are complex, they pass the task to a virtual assistant. They can share information, enabling seamless experience across different platforms. They provide valuable benefits to both businesses and customers across industries. These benefits include:

Fast, 24/7 customer service
Even at peak hours, customers prefer easy and fast customer service. In modern businesses, chatbots are the first interaction customers witness when engaging with organizations. These technologies provide support at any point of the day, sorting simple issues affecting customers.

Cost Efficient
When chatbots and virtual assistant technologies engage with clients, they sort out some issues that do not require human customer service. Human labor is quite expensive in handling all customer service tasks, making it cheaper when using the technologies as alternatives.

Consistent support
As we learned earlier, chatbots and virtual assistants offer 24/7 customer service. Their services are available at any point. Human customer support may not be available due to engagement, but chatbots can serve multiple customers in one scenario.

Marketing
Chatbots and virtual assistants gather insights about customer preferences, purchase behavior, etc. They can guide clients in product recommendations or even process transactions whenever customers purchase products.