5 Foundational Aspects of Data Automation

Data automation is a process by which the data within an organization is consolidated, cleansed, and distributed.

Data automation can be applied to different areas of any business. These are often IT Services, IT Services Outsourcing Services, Finance Services, HR Services, and many more.

Such services allow companies to automate tasks that typically require human intervention with the help of technology. Sometimes companies outsource their data jobs to third-party vendors or in-house individuals who specialize in data management.

It's important that before any company embarks on a journey to acquire these services, they know what type of data they need and how it's going to be used for this process. 

Having already explored the characteristics of modern data architecture, it only makes sense that we now dive into the critical aspects of data automation, which goes hand-in-hand with data integration and implementing a successful enterprise data management strategy.

The fact is, businesses are generating and storing an ever-increasing amount of data. On one hand, those huge data stores represent priceless insights that can drive growth. On the other hand, managing all that data often poses so many challenges that businesses end up struggling to access it quickly or consistently enough to actually use it. The technical challenges of handling data are the biggest roadblock to unlocking Business Intelligence (BI).

With data coming in so many different formats from so many sources, achieving efficient, accessible, and cost-effective analytics is no small feat. Data automation plays a big role in the process, as it helps simplify organization, sanitation, access, and reporting in multiple ways. So, let’s explore five critical aspects of understanding and using data automation correctly.

#1 Getting to Know ETL Operations

• To understand data automation, you first have to know the three main components that make up a data automation tool. These are often summarized as “ETL,” which stands for Extract, Transform, and Load.
• Extraction is the process of taking data from one or multiple sources.
• Transformation is the process of modifying data to fit a standard structure, which might require operations like replacing state names with state abbreviations or converting all data into CSV format.
• Load is the process of moving data from one system to another system.

These key elements make data automation possible by collecting your data, standardizing it, and then shipping it off to the system(s) where you need to have access to it.

#2 Developing a Data Automation Strategy

Failing to create a data automation strategy will cost your company in terms of wasted time and resources. Allowing teams to try to move forward without a strategy to guide them will surely lead them to straying away from the original plans and missing key steps, deadlines, and milestones.

As part of the development of your data automation strategy, you must identify the business areas that stand to benefit the most from automation; sort your data based on its importance and format; prioritize the processes that you plan to automate; and outline the required transformations that must take place for data automation to be effective.

#3 Defining Data Access and Ownership

Defining data access and ownership is yet another crucial aspect of data automation. In practice, there is often not a single team responsible for all data. Instead, separate groups will likely own a set of elements within your ETL process. How you divide ownership will depend on your existing teams and their responsibilities.

One of the most common approaches is centralized data access and operation, where the entire ETL process and any data automation associated with it is owned by the central IT department and likely managed by multiple teams within the department. Another option is hybrid data access and operation, where the extract and transform procedures are each owned by a department and the loading process is part of the central IT department.

Lastly, you might take the approach of completely decentralized data access and operation. In this instance, each department will be in charge of its own set of ETL processes. This is the most complex choice and you need to make sure that each department’s processes don’t contradict that of another department. In other words, investing in company-wide data standardization will prove crucial with this approach.

#4 Measuring Internal Business Results

Three of the biggest benefits a company can expect when implementing data automation is reduced processing time, improved ability to scale, and better performance. Alongside these benefits, you’ll likely experience improved cost efficiency and a myriad of other side advantages that come along with more efficient internal processes. The key is to not only set goals but put someone in charge of monitoring and measuring your progress towards them.

If one goal is to reduce processing time, that means that manual intervention should be minimized and monitored. You should also be tracking metrics like data reliability, resource utilization, and time savings. If another goal is to improve the performance of your data environment, you should be tracking the need for manual task updates, the time it takes to execute jobs, and similar data points.

#5 Ensuring End-User Results

Internal business metrics, like improved performance within your data environment, is no small accomplishment, but the impact of data automation really shines when you’re able to show measurable improvement for your end-users. Data automation can support every team in your company, from customer support to accounting, and improved access to relevant data should directly improve these teams’ ability to satisfy clients.

Aside from tracking how your data automation strategy improves the customer experience, you should also keep in touch with business users to see how it is directly improving their workflows. For instance, data automation reduces human input, thereby improving data quality by reducing human error and manual integrations. This can save teams countless hours spent entering, altering, and updating information within systems, allowing them to focus on what really matters: Growing the business.

Take The Next Step

Aezion has helped countless companies plan a data automation strategy that makes the most of existing tools, talent, and goals. Contact us today to discuss how we can help your organization get on the path to efficiency and performance through a data automation solution.

Preparing Your Business for AI Bot Development and Deployment

Introduction

Artificial intelligence (AI) and AI bot development are no longer the sole preserve of large corporations and scientists. AI bots are becoming available for businesses of all sizes.

AI is a technology that will transform businesses. To date, we have only seen the tip of the AI iceberg. And, no one is 100% certain of what lies beneath the surface. So, how can you prepare your business for this revolution that is coming soon? How can you prepare for a revolution that will bring changes that no one can predict with any certainty? The answer is; you must begin making cautious and measured preparations now.

Learn About What AI has to Offer Your Business

The first thing you should do to prepare for AI is to get key staff in your business thinking about the technology. AI is an emerging technology. So, avoid any preconceptions that may have about the AI bots and AI bot development. Don’t fall into the trap of thinking that AI bots are only chatbots. Look further afield at what AI may be able to do for your business in the future. Look at how your competitors are implementing AI. Look at how AI is being implemented in businesses outside of your own niche market. Research where AI bots are likely to go next and how to prepare your business for AI Bot development. Here are a few of the business processes that AI bots are already automating:

• Intruder detection
• Answering users’ technical questions
• Automating production management
• Internal compliance monitoring
• Anticipating customer purchases
• Monitoring social media
• Financial trading
• Automated call distribution

Understand Your Business Needs

It is important that businesses don’t begin to use AI technology for the sake of having AI. Businesses should use AI bots and define AI Bot development projects to meet a defined business need.

A support desk that provides award-winning support services, for example, may not need AI bots. In this case, using chatbots to answer support calls might be a backward step for the business.

If a support desk is overrun with calls, though, Chatbots might improve the service. They could reduce waiting times and reduce the number of customer complaints.

The starting point for preparing for AI bots is to understand your business needs. Don’t look for the business processes that AI could fit. Identify the business processes that AI Bots could improve.

Set Realistic Expectations for AI Bot Development Projects

AI is not the solution to everything. Customer service bots are great for very busy call centers. But, if you only receive a few calls a day, AI would not be necessary. AI bots are also useful for data mining. But, if your data set is small, a human would be able to complete the job as fast, because there would be no setup time involved.

Instead of trying to revolutionize your business overnight, start with something small. Start by looking at automating a small task that is currently time-consuming or very expensive to complete and defining an AI Bot development project to achieve that objective. Implementing AI will be a steep learning curve for all businesses. It is better that you learn by first implementing AI to complete a minor task. Then, you can start thinking about AI for mission-critical tasks.

Don’t Forget the Staff

Using AI bots is likely to have a big impact on your staff. It will bring new challenges and staff will need retraining. Staff will also have concerns about job security when you begin to use AI bots. So, it will be important to address the needs of the staff as a part of your AI strategy.

Provide employees with training so that they can work with AI bots. Think ahead about how employees might need to move into new roles. AI is likely to change the roles that people fill rather than replace the need for people. If you want artificial intelligence to deliver results, you will need to train your employees on how to work with and manage AI bots.

Start Preparing Your IT Infrastructure Now

One of the major potentials of AI for businesses is that it can use data from many different sources. This might be combining internal customer data with market research data, for example. Combining data from different systems can be a challenge. Especially if those systems cannot already communicate with each other.

AI bots will be able to perform more than one or two functions in a business. In the future, AI will work across all business systems. The use of AI will impact all areas of a business. Transitioning to AI will be easier if all your systems sit on a common platform. The easier it is for systems to share data, the easier it will be to sit AI bots over the top of all those systems. This is something that businesses can build into their IT strategies now.

Conclusion

AI is something that will need to revisit on a regular basis. You will need to track the progress of your own implementations of AI bots. And, you will need to keep abreast of new developments in AI. AI is with us today, but it’s got a long to go. So, the best way to begin using AI in business is to introduce it in small steps — perhaps starting with a few carefully defined AI Bot development projects. The first step is to start preparing for now.

Robotic Process Automation and Its Applications

Introduction

Many large enterprises are using robotic process automation (RPA) to reduce costs and improve efficiency. By implementing RPA, businesses can automate repetitive and mundane tasks. RPA could represent the first step towards true intelligent automation. But what is RPA, and what are its applications in business?

What Is Robotic Process Automation?

RPA is a term that can be applied to any computer program that automatically performs a repetitive function. In its simplest form, RPA is the automatic out-of-office message that your email software sends. More sophisticated RPA bots can log into an application, perform tasks, and log out again. RPA is not a part of an organization’s IT infrastructure. RPA sits on top of the infrastructure and automates tasks that humans would otherwise perform.

There are three main types of RPA bots. There are programmable bots that interact with other systems. There are intelligent RPA bots that can make decisions based on unstructured data. And, there are self-learning bots, such as chatbots.

Robotic Process Automation is a software technology that automates the execution of tasks, typically those that are repetitive and mundane.

Robotic Process Automation (RPA) is an emerging trend in business process automation. It is a type of computer programming that uses software to control the execution of routine tasks. RPA automates these routine tasks by mimicking human actions, such as clicking or filling out forms on a screen.

Examples of RPA Applications

RPA is suitable for use on tasks that are repetitive, well-documented, and well-defined. If the task is rule-based, and it does not alter often, then it is a task that could be completed by RPA. Robotic process automation can automate a wide variety of tasks in many different industries. Here are a few of the practical applications of RPA.

Web site scraping

RPA can be used to gather information from web pages. Examples of this include extracting and summarizing data from stock trading websites. Once the data has been collected and summarized, it can then be passed to humans for further analysis.

Automated email processing

Many organizations receive lots of emails asking the same questions. RPA can take care of some of these emails and respond with standard replies. The emails that the RPA bot cannot answer can then be forwarded to the appropriate personnel for answering.

Data Cleansing

Data cleansing is a good example of where RPA can be used to complete time-consuming tasks. If there are clear rules as to what constitutes bad data, RPA can filter out that bad data much more efficiently than humans.

Data Entry

One of the most far-reaching applications of RPA is that of data entry. An RPA bot can read original forms using optical character recognition (OCR) and then “key” the data into an application. This would be faster than a human could key the data, and it would be more accurate.

The Benefits of Robotic Process Automation

The benefits of RPA to businesses are many. RPA removes the human error factor from many tasks. The effectiveness of RPA can be limited by the accuracy of technologies, though. Technologies such as optical character recognition and speech recognition software. Even so, RPA bots can work 24/7 without breaks, and they never get bored. Bots also only need training once, and they will never quit their job.

RPA technology brings more than only cost savings. It also improves the customer experience through faster processing of data and faster resolution of queries. For employees, it brings that removal of the boring, repetitive tasks, so that they can spend more time on the important aspects of a role. RPA will change the nature of some jobs, so the HR aspects of those changes must be planned for as well. Overall, though, RPA will change the nature of employment for the better, rather than put people out of work.

Why Businesses Need to Consider Robotic Process Automation

RPA is a technology of today, not of the future. RPA bots are being used in accounting, finance, HR, and marketing now. American Express Global Business Travel uses RPA to automate the canceling of airline tickets and the issuing of refunds. At Walmart, RPA bots answer employees’ questions. In the future, some elements of almost every business process could be automated by RPA.

Robotic Process Automation won’t replace the need for humans. But it will remove the need for humans to perform programmable repetitive tasks. Businesses that do not embrace RPA will find themselves falling behind their competition. They will find that their customer service functions are slower and less efficient. And, they will become less competitive because of the additional costs of employing humans to perform tasks that are better performed by boots, and by not innovating by freeing up humans to do things that bots cannot. Eventually, businesses that do not use RPA will also find it difficult to employ people to perform repetitive tasks. Like their customers, their employees will have all moved to the companies that are using Robotic Process Automation to make life better for customers and employees.

30 Days Minimum Viable Product Wisdom

When anyone sets out to design and market a new product or system of any kind, their first inclination is likely to be to make the first release of that product or system the most functionally rich and complete that it can be. There is, however, a growing acceptance that releasing a minimum viable product (MVP) to early adopters is a far more efficient way to develop a new product or system and one that will ultimately lead to a much better deliverable.

What is a Minimum Viable Product?

The concept of a minimum viable product, which has been popularized by Silicon Valley entrepreneurs Steve Blank, and Eric Ries, is a design and development process in which a new product, such as an app, is developed and initially released with only sufficient functionality to satisfy the needs of the early adopters. Further features and functionality are only added to the product after consideration has been given to the feedback that has been received from those early adopters.

A minimum viable product is a product that has sufficient value to make people want to use it and that has been sufficiently developed so that early adopters can see the future of the product. The aim of MVP is to provide a feedback loop that can be used to guide the future direction of product development.

The advantages of the MVP

Developing a product using the MVP model has distinct advantages over the traditional, all-in-one-go, approach. Here are the main reasons why an MVP produces better apps.

Removes uncertainty

A system spec can only be, at best, a guess of what users will do with an app, how they will interact with it and what functionality they will need from the app. An MVP takes much of the guesswork out of product development and allows time for the feedback of users to drive the development of the product.

Eliminates wasted time

If you attempt to develop a fully completed app-based only on system spec, it is virtually guaranteed that you will develop functionality that users don’t use or functionality that doesn’t quite meet their expectations. It is far more cost-effective, therefore, to develop an app that has all the basic minimum functionality and then lets the user feedback be what dictates the future development of the product.

Applies the 80/20 principle to the development process

The Pareto (80/20) principle is never truer than it is in software development. 80% of the most important requirements of an app are likely to be cared for by just 20% of the functionality. The MVP focuses early development time on getting the essential 20% right so that 80% of essential user needs will be met with the first release.

Improves development focus

The MVP development model allows developers to focus on the development of core functionality first, followed by the development of additional functionality. This is a much more efficient way of developing a product than attempting to develop many aspects of functionality simultaneously. It allows the focussed use of resources on fewer aspects of the app, which ensures that each element of an app is completed to the highest specification.

It allows a product to evolve

Evolution has created some of the most complex and efficient systems on the earth, so why not let a product evolve too? What begins as an MVP can evolve naturally, through end-user feedback, and refinement via subsequent development iterations.

The Wisdom of the Aezion Inc. 30 Days MVP Development Model

The 30 Day MVP model does not doggedly insist that any product can be delivered as an MVP in 30 days. Instead, it recognizes, and leverages, the realization that the 30-day constraint (when applied with carefully crafted and optimized facilitation, design, planning, development, and usability testing techniques) can sharpen focus and improve project and custom software development process efficiency.

These efficiencies accrue as a result of the following:

Greater focus: A 30 days development constraint can further sharpen the focus by forcing prioritization and squeezing out all but the essential aspects of the app idea.

More efficient project structure: In contrast to conventional agile MVP processes, the Aezion Inc. approach defines and validates the entire multi-sprint MVP deliverable at the outset during week 1. This process eliminates the uncertainty often associated with open-ended agile processes and provides the dev team with a highly actionable solution definition that can be implemented sequentially by one team or in parallel by multiple sub-teams to meet the desired timeline.

We concede that our 30-Day MVP Model is unusual and is not suited to everyone and every software project; but if our approach resonates with you or whets your appetite, please schedule an appointment to discuss your app requirements.

The Benefits of a Content Management System

A content management system (CMS) is software that enables end-users to create and manage content on a website. They are designed to make content management easy for non-technical users. One of the key features of a good content management system is that no coding is needed to create or modify content. CMS handles all the basic coding, so users can concentrate on what visitors to the website will see, rather than what goes on behind the scenes.

A content management system consists of two main elements. First, there is a content management application (CMA). The CMA is the part of the application that allows users to add content and manage it. The second element is a content delivery application (CDA). This is the backend application that formats the content and makes it available to visitors to the site.

The Benefits of a Content Management System

The main benefit of a content management system is that it allows non-technical people to publish content. This dramatically cuts the cost of maintaining a website. You may still employ the services of a web developer to design and set up a site. But, with a CMS system, you will be able to publish and modify content yourself.

The second major advantage of a CMS is that it allows collaboration. Multiple users within an organization can create and publish content. The user interface of a CMS is usually browser-based so any number of users can access the system from anywhere.

Examples of Content Management Systems

One of the most popular content management systems is WordPress, but there are hundreds of other CMS platforms. WordPress is an open-source CMS tool that is used by large businesses, small businesses, and individuals. It is estimated that WordPress is the CMS behind more than 30% of the world’s websites. Some of the other popular platforms include Drupal, Joomla, and Magento.

Important Things to Consider CMS Platform

While WordPress is popular, it is not the only option. Before you choose a content management system, you should look at what your overall goals are.  You will need to think in detail about the functionality that you will need. This will help you choose a CMS platform that is right for your business rather than simply opting for the best-known CMS. Here are some things to consider when choosing a CMS platform.

Ease of Use

Ease of use is the main thing to look for in a CMS platform. However, some CMS systems cross the line between ease of use and lack of functionality. Make sure that the CMS platform use is intuitive and easy to use. But, remember to make sure that it has sufficient functionality to meet your needs.

Availability and Cost of Add-ins

You can usually add functionality to CMS platforms with modules, which are often called plugins. These are usually made available by third parties. They may, or may not, be free. When you are researching CMS, investigate the availability and the cost of plugins. If the CMS platform you choose only has limited out-of-the-box functionality, then you will be relying on plugins to customize your content management solution to your own needs. Plugins expand functionality, but they can lead to maintenance issues. Because they are written by third parties, they may not always be compatible with your version of the CMS platform.

Look and Feel Flexibility

It is important that your website looks different from all the rest. This can be difficult with some of CMS platforms. If there are only a limited number of themes or templates, and a few customization options, it will be difficult to make your website uniquely your own.

Responsive Design

More half of internet traffic now comes from mobile devices. So, responsive mobile design is essential in a CMS platform. Make sure that the CMS platform you select supports responsive web design. That will ensure that your web pages will render properly across different types of devices.

Speed

Speed is an important consideration in several areas. The first aspect of speed relates to ease of use. How easy will it be to install the software, configure the website, and publish content. The second aspect is the speed that the site will operate. The speed at which web pages are rendered is vital. If a website is slow to load or refresh, visitors will become frustrated and move on to another website.

Integration

The ability to integrate a CMS platform with third-party applications can also be very important. You may want to integrate your website with an e-commerce solution, a CRM package, or an automated marketing system. Investigate the availability of Application Programming Interfaces (APIs) and find out what support there is for integration. Even if you don’t want to integrate your CMS with third-party applications now, you may want to in the future.

Scalability

Another factor to consider is how scalable the CMS platform is. Will it handle large spikes in traffic? Can you add resources to cope with increasing traffic? If you plan on having more than one website, does the CMS application offer multi-site support?

Security and Support

You should also check what security features come with the software, and what extra third-party security applications you may have to use. All websites are targets for hackers, but some platforms have much better security features than others. The support services that are available for CMS platforms vary as well. High-end open source applications like WordPress are typically built with sophisticated security mechanisms but do not provide support service for CMS installation and maintenance so you may have to use a third-party support service.

To choose the right CMS platform for your business, you will need to assess both your current and future requirements. There are plenty of CMS options, but making the right decision at the outset will save you a lot of time in the future. Content can be migrated from one platform to another, but it can be very time consuming to do so.

It is advisable to seek advice from a company that specializes in digital marketing. If you can, it is also useful to test drive the software before you commit to using it. The decision you make now on a CMS platform could have a major impact on your organization in the future.

Docker Container-based Custom Application Management - what business leaders should know

Docker Containers have become an essential element in modern, high-performance IT operations practices — particularly in the cloud computing era. This article defines what containers are and why they are important to your business, whether you are responsible for just managing a single server or running IT operations at scale.

Docker Containers Background

IT operations are responsible for managing and maintaining an efficient and reliable computing infrastructure that supports the range of computing tasks performed by a business. These tasks are facilitated through enterprise resource planning applications that support Human Resources, Finance, Customer Relationship Management, Project Management, Operations Management and Workflow, Logistics, Reporting and Analytics, and more. While these applications differ in function all share a common dependence on efficient, reliable, and responsive computing resources. These resources include an operating system, processor, RAM, storage and networking elements. Historically, these individual elements were organized and managed as physical server units, then virtual machines with the advent of virtualization technology.

Virtual Machines improved overall computing resources and IT operations efficiency through increased sharing of physical hosts and host files and libraries. This reduction in physical servers and increased utilization of host files and libraries led to a reduction in Capital and Operations Expenditure, and improvements in Developer and Customer Experience. 

Containers extend the efficiency trajectory of Virtual machines by allowing apps to run in a dramatically simplified and light-weight environment compared to physical servers and virtual machines. Containers disassociate dedicated application dependencies from shareable OS elements. These shareable elements are abstracted and packaged as single-instance, shareable resources that further improve resource utilization. 

Containers and Docker

Containers were introduced as an extension of the Linux Operating System in 2001. They are an evolution and formalization of namespace isolation and resource governance techniques used in pre-Linux Operating Systems such as Solaris Zones, Unix chroot and BSD Jails. The Docker Container specification presented a common packaging model, test and deployment model that dramatically simplified containerization and application deployment on Linux hosts. The specification was realized as Docker images that contained shared host and VM files and libraries. This evolution led to further improvement in computing resource utilization — maximizing resource sharing by eliminating VM-related overhead — and significant improvement in IT operations and application management. The result is further improvement in Capital Expenditure, Operations Expenditure, and Customer Experience. 

The benefits of Docker Containers were introduced to Windows hosting environments with Windows Server 2016. To support this initiative, Microsoft established a partnership with Docker to extend the Docker API and toolset to support containers operating on Windows Server hosts. The Microsoft extensions permit the same Docker client to manage both Linux and Windows Server containers — extending Docker utility for Windows Server while preserving the DevOps efficiencies and user experience made possible by Docker. This initiative by Microsoft created a true win-win scenario for all parties.

Why Docker Containers are Important

Docker Containers are important for small and large IT operations. To understand this, let’s review the DevOps benefits of Docker-based containers:

1. Application performance improvements. This is enabled through the sharing a single Operating System kernel across multiple containers. The result is more efficient and granular application packaging, which in fast container startup and because the startup package is smaller and OS components are excluded from the container startup process. 
2. Faster Provisioning. Containers are dramatically faster to provide because they are significantly lighter-weight to build and define versus Virtual Machine images, and they are provisioned via software on pre-provisioned infrastructure. 
3. Efficient Resource Utilization. Containers are also more efficient at resource utilization than Virtual Machines with siloed OSs and OS-based resources.
4. Simple, high availability. This is because the containers can run on the different underlying hardware. If one host goes down, traffic can be re-routed from the Edge to live application containers running elsewhere.
5. Smooth scaling. Containers enable smooth scaling without downtime or architectural changes. Scaling is difficult with VM-centric hosting which requires rebooting, and often rearchitecting, to resize.
6. Configuration consistency. Every container can be exactly the same. The hosting platform is a large, resource sharing matrix. Containers are provisioned automatically on identical infrastructure managed via consistent, automated tools that minimizes server sync issues.

These are direct benefits if you are responsible for managing a large IT operation. You and your DevOps team can experience them in your day to day operations. However, these benefits also apply if you are responsible for administering a single server or even a single website. This is because best of breed hosting providers such as Azure or AWS (a) have platform economics that produces lower costs for comparable, small-to-large scale server deployments, and (b) have largely adopted containers — so by utilizing one of them you indirectly experience these benefits.

The Internet of Things It Cover All Business Web Services

The Source IoT, It will describe the market around the Internet of Things (IoT), the technology used to build these kinds of devices, how they communicate, how they store data, web services, cloud computing contributes to the growth of the internet of things from the mere definition to reality. ... Web service uses XML for data representation and data transportation between layers. Divided into four modules, we will learn by doing. We will start with simple examples and integrate the techniques we learn into a class project in which we design and build an actual out system.

Internet of  Things Graph, a service that connects different devices and cloud services, such as linking humidity sensors to sprinklers to weather data services to create agricultural applications, Industrial apps through a visual drag-and-drop interface.

 Internet of Things Site Wise to monitor operations across facilities, quickly compute common industry performance metrics, build applications that analyze industrial web data to prevent costly equipment issues, and reduce gaps in production with standard data.

The idea of IoT is interconnectivity. Not only people will be able to communicate with IoT products, but IoT products will be able to communicate with each other. People will be supervisors of their IoT products and households via web applications with smartphones or tablets.

                               

The solution used principally remote victimization cloud systems and cloud computing during this analysis and development. Its product will communicate with one another. The merchandise is managed by cloud technology and users don't would like the native controller. We tend to design a product (things) for house connectable to the net solely with the house local area network router, which has each average social unit applications. It is likely to increase the number of people working from home with access to multiple devices in the office and on the factory floor; many more tasks will be able to be completed remotely. Remote workers are often more efficient and more cost-effective. So, the IoT could have a beneficial effect on most businesses a bottom line of The Internet of Things Means for Businesses.