Robotic Process Automation (RPA)

 What is RPA (Robotic Process Automation)?

 Robotic process automation , or RPA for its acronym in English, is a technology that allows configuring computer software or robots to emulate and execute in an integrated and autonomous (or semi-autonomous) manner the actions or steps of a human interaction with certain digital systems. , in such a way that it can execute a commercial process.

 In other words, it is programming a virtual robot to do what a person would do on their computer, this in a more expeditious, safer and uninterrupted way; activities such as data entry, processing standard transactions, or answering simple customer service questions.

 How does RPA robotic process automation work? 

RPA works by replicating the actions of a human being who interacts with applications or systems to perform different tasks, through a script that is executed by the bot under a defined set of business rules.

The operation of the types of process automation software  varies according to the tool that is being used and the type of process that is automated, however, there are some basic principles for all: programming interfaces and systems integration.

What are the benefits of implementing RPA?

 A robot does not have the needs of a worker: it does not have to rest, or go to the bathroom, or get sick. What's more, it can work 24 hours a day performing tasks in different areas of the organization, and in general the robot can significantly reduce the execution time of those tasks, also reducing the number of errors that humans can make that they used to do. the process. Thus, there are several benefits that derive from a correct implementation of RPA in your company:

Saved Man Hours:  RPA takes care of repetitive tasks saving valuable time and resources, plus they cost less than a full-time employee.

Error reduction: The fatigue or lack of knowledge that leads to human errors does not happen with bots, so the rate is reduced.

Agility and increased productivity: robots do more in less time and don't forget to consider that there is no time wasted correcting errors.

Improve response and compliance times: Automation reduces the risk of delays by introducing precision into your operations.

Making the most of employee time: automating repetitive administrative processes allows human workers to focus on complex value-added tasks for the business

What advantages and challenges are associated with RPA?

Automation has become a critical business issue in this digital age as organizations strive to boost productivity, improve user experience, and rapidly develop and launch new products and services. As the RPA technology market grows, IT leaders are increasingly interested in its ability to eliminate repetitive work, streamline operations, and reduce costs. However, as with any new technology, implementation brings advantages but also challenges. Below we indicate the most relevant in each case:

Advantage

Efficiency: RPA has been shown to increase employee productivity as they spend less time on repetitive tasks. Gartner has found that full-time employees can save up to 30% of their time with RPA. 

Accuracy – Data entry tasks are often more accurate when performed automated rather than manually. RPA tools also fully comply with organizational and industry policies.

Cost savings: by increasing the productivity of employees, the company saves money. Employees can then do higher value work in the same amount of time. 

Access to legacy technology – Organizations that are still using legacy technology often struggle to integrate these tools with other cloud-based systems. Through its user interface, RPA provides a simple entry point to exchange data with legacy systems.

Challenges

Replacement of human workers: One of the main criticisms leveled at RPA and other automation technologies is the potential elimination of data entry and other clerical roles.

Lack of intelligent features: RPA technology alone can only perform the tasks it copies from a script, so it is unable to learn and improve the script it performs. The next generation of AI and intelligent automation tools are being introduced to address this RPA blind spot.

Project complexity – Transformative RPA projects are often complex and require significant time investment to pay back; consequently, some of these projects fail before making a profit.

RPA and artificial intelligence

Robotic process automation is often mistaken for artificial intelligence (AI), but the two are distinctly different. AI combines cognitive automation, machine learning (ML), natural language processing (NLP), reasoning, hypothesis generation and analysis.

The critical difference is that RPA is process-driven, whereas AI is data-driven. RPA bots can only follow the processes defined by an end user, while AI bots use machine learning to recognize patterns in data, in particular unstructured data, and learn over time. Put differently, AI is intended to simulate human intelligence, while RPA is solely for replicating human-directed tasks. While the use of artificial intelligence and RPA tools minimize the need for human intervention, the way in which they automate processes is different. 

That said, RPA and AI also complement each other well. AI can help RPA automate tasks more fully and handle more complex use cases. RPA also enables AI insights to be actioned on more quickly instead of waiting on manual implementations.

Reference :

https://www.ibm.com/topics/rpa

https://en.wikipedia.org/wiki/Robotic_process_automation

 

Metaverse Technology - Latest Seminar Topic 2022

 Metaverse  Abstract

The Metaverse is a world of virtual or digital reality that we access through special devices such as augmented reality glasses and that allow us to interact with other users and elements of the environment, although platforms have been created that do not need these devices to allow his access to the Metaverse.

This seeks to be a kind of alternative reality, a parallel universe in which we can do the same things we do in our day to day, such as work, socialize, travel, but without moving from our room.

The Metaverse may offer us the next great evolutionary leap of the Internet or 

it might not develop as much as expected. It's still very early days, and companies like Facebook are only beginning to create the infrastructures and early concepts that lead to a future where there are devices capable of taking us there. Therefore, it is more of a concept, a blank canvas, than a reality that we can connect to today.

What is Metaverse?

The Metaverse is a virtual world , one to which we will connect using a series of devices that will make us think that we are really inside it , interacting with all its elements. It will be like actually teleporting to a whole new world through virtual reality glasses and other accessories that will allow us to interact with it.

Virtual worlds are nothing new, and there are plenty of them, especially in the video game industry. You create a character or avatar, and you enter that world to live adventures through your computer. However, the metaverse does not seek to be a fantasy world, but rather a kind of alternate reality in which we can do the same things we do today outside the home, but without leaving the room.

The term metaverse comes from a 1992 novel called 'Snow Crash' , and is a term that has settled to describe visions of three-dimensional or virtual workspaces . This metaverse, therefore, means a virtual world in which we can interact, and which has been created to resemble an external reality.

As for the precise concept of the metaverse that Facebook and other companies are betting on. The idea would be to create a parallel and completely virtual universe, which we can access with virtual reality and augmented reality devices , so that we can interact with each other within it, and from the outside with the content we have inside.

The key to this metaverse is that it can be fully immersive , or at least much more so than current virtual reality is. Yes, we will have glasses that are possibly similar to the current ones to immerse ourselves in it, but also sensors that record our physical movements so that our avatar within that metaverse does exactly the same.

Even the devices we use can interpret our facial expressions so that our avatar in the metaverse can recreate us, so that the rest of the people with whom we are interacting can understand how we feel. Come on, body language is also part of these virtual interactions.

History of Metaverse

We are not exactly clear about the origin of the metaverse, but what we can know is when people started talking about it. The first references to the metaverse appear in a novel by Neal Stephenson, Snow Crash (1992).

The novel tells the story of Hiroaki Hiro Protagonist , a pizza delivery boy in the real world, but warrior prince (samurai) in the Metaverse. Given a moment, Hiro discovers the existence of a powerful computer virus in the Metaverse, called Snow Crash , and the discovery of more about this virus will be the central axis of the plot.

What is relevant about this book is that Neal created the first written reference to a completely virtual world long before cyberspace could be spoken of. In his book Neal introduces the idea of ​​avatars (or virtual characters of real people in the tangible world).

When will the metaverse be real?

Currently, the metaverse is just a concept that is beginning to be built. The Meta company, formerly known as Facebook, has presented the idea and announces heavy investments to make it real. But it remains to be seen if other companies join in the effort to create the technologies that make it possible.

Because we still do not have the technologies that can make that concept real . We don't have virtual reality devices that actually make us move like we're inside that universe realistically. The entire infrastructure is also missing in terms of design. It is a universe that wants to be created, but it still does not have regions, streets or anything, only some virtual rooms that are being used for the first tests.

Over the next few years we will see how new devices are being launched that seek to connect us with this new virtual reality. The idea is that in the future they will be very complete and affordable, but until that is real, they may still not allow great interactions and will be quite expensive.

Therefore, we are still a long way from being able to all connect to a metaverse in which to interact. We still need to develop that virtual universe, and also develop the technology that makes it possible for us to connect to it. It is also necessary to make, where it exists, that technology affordable for all.

Augmented Reality

Augmented reality (AR) is the term used to describe the set of technologies that allow a user to visualize part of the real world through a technological device with graphic information added by it.

Artificial intelligence

Artificial Intelligence (AI) is the combination of algorithms proposed with the purpose of creating machines that have the same capabilities as the human being.

Virtual Avatar

It is a virtual representation of real people. They can be creative and fundamentally different from us, or they can try to be as similar as possible, creating an almost identical representation.

Conclusions

The Metaverse will give rise to the generation of millions of data in real time, since the technology that accompanies it offers companies enormous possibilities to sell products and services in various markets, both vertical and horizontal. This will add value to companies that use the Metaverse as a new business channel. 

Many of the challenges are unknown for an already advanced era. It is necessary to face them from innovative angles, where we understand that the already  established models are going to have changes and we will have to adjust.

Although we cannot imagine the full range of benefits or risks that will arise, it is clear that we are about to launch into a fascinating new dimension of the  human experience.

Source Reference

https://en.wikipedia.org/wiki/Metaverse

https://www.ey.com/en_in/search?q=Metaverse

Data Fabric - Seminar Topic 2022

 Data Fabric Abstract

The data fabric is an architecture that facilitates the end-to-end integration of various data work lines and cloud environments through the use of intelligent and automated systems. In the last decade, developments within hybrid cloud , artificial intelligence , the Internet of Things (IoT), and edge computing have led to the exponential growth of big data, creating even more management complexity for businesses. This has made unifying and managing data environments an increasing priority, as this growth has created significant challenges such as data silos, security risks, and overall decision-making bottlenecks. data management teamsare tackling these challenges head-on with data fabric solutions . They are leveraging them to unify their disparate data systems, integrate management, tighten security and privacy measures, and give workers, particularly business users, more access to data.

What is a Data Fabric?

The data fabric is an emerging design concept for data management that addresses the challenges of data complexity. Its goal is to provide an agile enterprise database to support a wide variety of business use cases. The notion of a data fabric is closely tied to DataOps and initiatives for data modernization and digital innovation in general.

A data fabric can be thought of as a fabric that connects data from multiple locations (edge, core, and cloud), data types, and data sources, with methods to access that data. For users consuming applications and systems alike, it abstracts away the complexities associated with underlying data storage, movement, transformation, security, and processing.

A data fabric is not a replacement for more traditional data management architectures such as data lakes, data warehouses, data concentrators, and databases. Instead, a data fabric includes those systems as active participants in a unified approach.

Data fabric architecture

Leveraging data services and APIs, data fabrics bring together data from legacy systems, data lakes , data warehouses , sql databases, and applications, providing a comprehensive view of business performance. Unlike these individual data warehouse systems, its goal is to create more fluidity in data environments, trying to counteract the problem of data gravity, that is, the idea that data becomes more difficult to move to as they grow in size. A data fabric abstracts away the technological complexities involved in moving, transforming, and integrating data, making all data available across the enterprise.

That said, this is just an example. There is no single data architecture for a data fabric, as different businesses have different needs. The diverse number of cloud providers and data infrastructure implementations ensure variation between companies. However, companies using this type of data structure exhibit similarities in their architectures that are unique to a data fabric. More specifically, they have six fundamental components, which Forrester (link external to ibm.com) describes in the "Enterprise Data Fabric Enables DataOps" report. These six layers include the following:

1. Data management layer: This is responsible for data management and data security.
   
   Data ingestion layer: This layer begins to piece together the data from the cloud, finding connections between the structured and unstructured data.
   
   Data processing: The data processing layer refines the data to ensure that only data relevant to the data extraction is displayed.
   
   Data Orchestration: This critical layer does some of the most important work for the data fabric: transforming, integrating, and cleansing data, making it usable for teams across the enterprise.
   
   Data Discovery: This layer shows new opportunities to integrate disparate data sources. For example, you might find ways to connect data in a supply chain data mart and customer relationship management data system, enabling new opportunities for product offerings to customers or ways to improve customer satisfaction.
   
   Data Access: This layer enables data consumption, ensuring the correct permissions for certain equipment to comply with government regulations. Additionally, this layer helps display relevant data through the use of dashboards and other data visualization tools

Data Fabric vs. Data Virtualization

Data virtualization is one of the technologies that enables a data fabric approach. Instead of physically moving data from various on-premises and cloud sources using the ETL (extract, transform, load) standard, a data virtualization tool connects to the different sources, integrating only the necessary metadata and creating a layer of virtual data. This allows users to tap into source data in real time.

Conclusion

Data fabrics are still in the early stages of adoption, but their data integration capabilities help businesses with data discovery, enabling them to take on a variety of use cases. While the use cases that a data fabric can handle may not be too different from other data products, it differs in the scope and scale that it can handle, as it eliminates data silos. By integrating multiple data sources, companies and their data scientists can create a comprehensive view of their customers, which has been particularly useful with banking customers. 

Source Website:

https://ibm.com/in-en/analytics/data-fabric

Internet of Things (IoT)

Internet of Things (IoT) 

The Internet of Things is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Wikipedia

History of IoT 

Some sources say that the connected device’s technology dates as far back as 1832 when the electromagnetic telegraph was first built. Of course, it was not IoT proper. But it was the first case of devices connected via a network and a true quantum leap of the time. However, we are more interested in much more recent events.

The world heard the name “Internet of Things” for the first time in 1999 when Kevin Ashton, co-founder of Auto-ID Labs, used it to describe a network which could connect physical devices to the Internet. The new name described the innovational idea of connecting the RFID (Radio-frequency identification) technology to the Internet. RFID, which allows tracking physical objects with special tags attached to them, had been around for quite some time by 1999. However, the idea of exchanging the data stored in the tags via the Internet was first aired only then.

Since the turn of the century, the Internet of Things is getting bigger with each passing year. It has penetrated most of the areas of human life. For example, retail commerce, healthcare, banking and finance, education, home management, and many more. The research by Cisco Internet Business Solutions Group found that in 2008 there were more things connected to the Internet than people.

Source : https://adoriasoft.com/blog/history-of-iot-universe/