Top 20 AWS (Amazon Web Services ) Interview Questions and Answers

Ques: 1. What is Data warehouse in AWS?

Answer: 

Data ware house is a central repository for data that can come from one or more sources. Organization typically use data warehouse to compile reports and search the database using highly complex queries. Data warehouse also typically updated on a batch schedule multiple times per day or per hour compared to an OLTP (Online Transaction Processing) relational database that can be updated thousands of times per second.

 

AWS Outposts Interview Questions and Answers

AWS Cloud Interview Questions and Answers

 

Ques: 2. What is NAT Instance and NAT Gateway?

Answer:

NAT instance: A network address translation (NAT) instance is an Amazon Linux machine Image (AMI) that is designed to accept traffic from instances within a private subnet, translate the source IP address to the Public IP address of the NAT instance and forward the traffic to IWG.

NAT Gateway: A NAT gateway is an Amazon managed resources that is designed to operate just like a NAT instance, but it is simpler to manage and highly available within an availability Zone. To allow instance within a private subnet to access internet resources through the IGW via a NAT gateway.

  

AWS AppSync Interview Questions and Answers

AWS Cloud9 Interview Questions and Answers

  

Ques: 3. What type of performance can you expect from Elastic Block Storage? How do you back it up and enhance the performance?

Answer: 

Performance of an elastic block storage varies i.e. it can go above the SLA performance level and after that drop below it. SLA provides an average disk I/O rate which can at times frustrate performance experts who yearn for reliable and consistent disk throughput on a server. Virtual AWS instances do not behave this way. One can backup EBS volumes through a graphical user interface like elasticfox or use the snapshot facility through an API call. Also, the performance can be improved by using Linux software raid and striping across four volumes.

 

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Ques: 4. How will you access the data on EBS in AWS?

Answer: 

Elastic block storage as the name indicates provides persistent, highly available and high-performance block level storage that can be attached to a running EC2 instance. The storage can formatted and mounted as a file system or the raw storage can be accessed directly.

  

AWS Cloud Practitioner Essentials Questions and Answers

AWS EC2 Interview Questions and Answers

  

Ques: 5. Is it possible to vertically scale on an Amazon Instance?  If yes, how?

Answer: 

Following are the steps to scale an Amazon Instance vertically –

1. Spin up a larger Amazon instance than the existing one. 
2. Pause the existing instance to remove the root ebs volume from the server  and discard. 
3. Stop the live running instance and detach its root volume. 
4. Make a note of the unique device ID and attach that root volume to the new server. 
5. Start the instance again.

 

AWS Lambda Interview Questions and Answers

AWS Cloud Security Interview Questions and Answers

  

Ques: 6. What is the total number of buckets that can be created in AWS by default?

Answer: 

100 buckets can be created in each of the AWS accounts. If additional buckets are required, increase the bucket limit by submitting a service limit increase.

 

AWS Simple Storage Service (S3) Interview Questions and Answers

AWS Fargate Interview Questions and Answers

 

Ques: 7. How will you configure an instance with the application and its dependencies, and make it ready to serve traffic?

Answer: 

You can achieve this with the use of life cycle hooks. They are powerful as they let you pause the creation or termination of an instance so that you can sneak peak in and perform custom actions like configuring the instance, downloading the required files, and any other steps that are required to make the instance ready. Every auto scaling group can have multiple life cycle hooks.

 

AWS SageMaker Interview Questions and Answers

AWS DynamoDB Interview Questions and Answers

  

Ques: 8. What are some of the key best practices for security in Amazon EC2?

Answer:

• Create individual IAM (Identity and Access Management) users to control access to your AWS recourses. 
• Creating separate IAM user provides separate credentials for every user making it possible to assign different permissions to each user based on the access requirements. 
• Secure the AWS Root account and its access keys. 
• Harden EC2 instances by disabling unnecessary services and applications by installing only necessary software and tools on EC2 instances. 
• Grant least privileges by opening permissions that are required to perform a specific task and not more than that. Additional permissions can be granted as required. 
• Define and review the security group rules on a regular basis. 
• Have a well-defined strong password policy for all the users. 
• Deploy anti-virus software on the AWS network to protect it from Trojans, Viruses, etc.

 

AWS Cloudwatch interview Questions and Answers

AWS Elastic Block Store (EBS) Interview Questions and Answers

 

Ques: 9. What are the important features of a classic load balancer in EC2?

Answer: 

·         The high availability feature ensures that the traffic is distributed among EC2 instances in single or multiple availability zones. This ensures high scale of availability for incoming traffic.

·         Classic load balancer can decide whether to route the traffic or not based on the results of health check.

·         You can implement secure load balancing within a network  by creating security groups in a VPC.

·         Classic load balancer supports sticky sessions which ensure that the traffic from a user is always routed to the same instance for a seamless experience.

 

AWS Amplify Interview Questions and Answers

AWS Secrets Manager Interview Questions and Answers

 

Ques: 10. What happens when you reboot an EC2 instance?

Answer: 

Rebooting an instance is just like rebooting a PC. You do not return to image’s original state; however, the contents of the hard disk are same as before the reboot.

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Ques: 11. What Are the main features of Amazon Cloud Front?

Answer: 

Amazon Cloud Front is a web service that speeds up delivery of your static and dynamic web content, such as .html, .css, .js, and image files, to your users. CloudFront delivers your content through a universal network of data centres called edge locations

AWS Solution Architect Interview Questions and Answers

AWS Glue Interview Questions and Answers

Ques: 12. Explain storage for Amazon Ec2 Instance?

Answer: 

An instance store is a provisional storing type located on disks that are physically attached to a host machine. … This article will present you to the AWS instance store storage type, compare it to AWS Elastic Block Storage (AWS EBS), and show you how to backup data stored on instance stores to AWS EBS

Amazon SQS is a message queue service used by scattered requests to exchange messages through a polling model, and can be used to decouple sending and receiving components

AWS Cloud Interview Questions and Answers

AWS VPC Interview Questions and Answers         

Ques: 13. What is AWS Certificate Manager?

Answer: 

AWS Certificate Manager is an administration that lets you effortlessly arrangement, oversee, and send open and private Secure Sockets Layer/Transport Layer Security (SSL/TLS) endorsements for use with AWS administrations and your inward associated assets. SSL/TLS declarations are utilized to anchor arrange interchanges and set up the character of sites over the Internet and additionally assets on private systems. AWS Certificate Manager expels the tedious manual procedure of obtaining, transferring, and reestablishing SSL/TLS endorsements.

AWS DevOps Cloud Interview Questions and Answers

AWS Aurora Interview Questions and Answers

Ques: 14. What is the AWS Key Management Service?

Answer: 

AWS Key Management Service (AWS KMS) is an overseen benefit that makes it simple for you to make and control the encryption keys used to scramble your information. AWS KMS is additionally coordinated with AWS CloudTrail to give encryption key use logs to help meet your inspecting, administrative and consistence needs.

AWS Database Interview Questions and Answers

AWS ActiveMQ Interview Questions and Answers

Ques: 15. What is Amazon EMR?

Answer: 

Amazon Elastic MapReduce (EMR) is one such administration that gives completely oversaw facilitated Hadoop system over Amazon Elastic Compute Cloud (EC2).

AWS CloudFormation Interview Questions and Answers

AWS GuardDuty Questions and Answers

Ques: 16. What is Amazon Kinesis Firehose?

Answer: 

Amazon Kinesis Data Firehose is the least demanding approach to dependably stack gushing information into information stores and examination devices. … It is a completely overseen benefit that consequently scales to coordinate the throughput of your information and requires no continuous organization.

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AWS Lake Formation Interview Questions and Answers

Ques: 17. What Is Amazon CloudSearch and its highlights?

Answer: 

Amazon CloudSearch is a versatile cloud-based hunt benefit that frames some portion of Amazon Web Services (AWS). CloudSearch is normally used to incorporate tweaked seek abilities into different applications. As indicated by Amazon, engineers can set a pursuit application up and send it completely in under 60 minutes.

AWS Data Pipeline Interview Questions and Answers

Amazon CloudSearch Interview Questions and Answers 

Ques: 18. What is the Difference between the Service Role and SAML Federated Role?

Answer: 

Service Role are meant for usage of AWS Services and based upon the policies attached to it, it will have the scope to do its task. Example : In case of automation we can create a service role and attached to it.

Federated Roles are meant for User Access and getting access to AWS as per designed role. Example: We can have a federated role created for our office employee and corresponding to that a Group will be created in the AD and user will be added to it.

AWS Transit Gateway Interview Questions and Answers

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Ques: 19. Distinguish between Scalability and Flexibility?

Answer: 

Cloud computing offers industries flexibility and scalability when it comes to computing needs:

Flexibility. Cloud computing agrees your workers to be more flexible – both in and out of the workplace. Workers can access files using web-enabled devices such as smartphones, laptops and notebooks. In this way, cloud computing empowers the use of mobile technology.

One of the key assistances of using cloud computing is its scalability. Cloud computing allows your business to easily expensive or downscale your IT requests as and when required. For example, most cloud service workers will allow you to increase your existing resources to accommodate increased business needs or changes. This will allow you to support your commercial growth without exclusive changes to your present IT systems.

Amazon EMR Interview Questions and Answers

Amazon OpenSearch Interview Questions and Answers

Ques: 20 What is SES, SQS and SNS?

Answer: 

SES (Simple Email Service): SES is SMTP server provided by Amazon which is designed to send bulk mails to customers in a quick and cost-effective manner.SES does not allows to configure mail server.

SQS (Simple Queue Service): SQS is a fast, reliable and scalable, fully managed message queuing service. Amazon SQS makes it simple and cost Effective. It’s temporary repository for messages to waiting for processing and acts as a buffer between the component producer and the consumer.

SNS (Simple Notification Service): SNS is a web service that coordinates and manages the delivery or sending of messages to recipients.

 

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Top 20 Data Science Interview Questions and Answers

 

Ques: 1. What is the difference between Data Science and Data Analytics?

Answer: 

Data Scientists need to slice data to extract valuable insights that a data analyst can apply to real-world business scenarios. The main difference between the two is that the data scientists have more technical knowledge then business analyst. Moreover, they don’t need an understanding of the business required for data visualization.

 

Ques: 2. What is the method to collect and analyse data to use social media to predict the weather condition?

Answer: 

You can collect social media data using Facebook, twitter, Instagram's API's. For example, for the tweeter, we can construct a feature from each tweet like tweeted date, retweets, list of followers, etc. Then you can use a multivariate time series model to predict the weather condition.

 

Ques: 3. What is the Cross-Validation?

Answer: 

It is a model validation technique for evaluating how the outcomes of a statistical analysis will generalize to an independent data set. It is mainly used in backgrounds where the objective is forecast, and one wants to estimate how accurately a model will accomplish in practice. The goal of cross-validation is to term a data set to test the model in the training phase (i.e., validation data set) to limit problems like overfitting and gain insight on how the model will generalize to an independent data set.

 

Ques: 4. What are the Steps in Making a “Decision Tree”?

Answer: 

The steps to make a “Decision Tree” are as follows:

1. Take the entire data set as input.
2. Look for a split that maximizes the separation of the classes. A split is any test that divides the data into two sets.
3. Apply the split to the input data (divide step).
4. Re-apply steps 1 to 2 to the divided data.
5. Stop when you meet some stopping criteria.This step is called pruning. 
6. Clean up the tree if you went too far doing splits.

 

Ques: 5. Can you explain Star Schema?

Answer: 

It is a traditional database schema with a central table. Satellite tables map IDs to physical names or descriptions and can be connected to the central fact table using the ID fields; these tables are known as lookup tables and are principally useful in real-time applications, as they save a lot of memory. Sometimes star schemas involve several layers of summarization to recover information faster.

 

Ques: 6. What are the various steps for a Data analytics project?

Answer: 

The following are important steps involved in an analytics project:

1. Understand the Business problem. 
2. Explore the data and study it carefully. 
3. Prepare the data for modelling by finding missing values and transforming variables. 
4. Start running the model and analyse the Big data result. 
5. Validate the model with new data set. 
6. Implement the model and track the result to analyze the performance of the model for a specific period.

Ques: 7. Why Data Cleansing is essential and which method you use to maintain clean data? Explain.

Answer: 

Dirty data often leads to the incorrect inside, which can damage the prospect of any organization. For example, if you want to run a targeted marketing campaign. However, our data incorrectly tell you that a specific product will be in-demand with your target audience; the campaign will fail.

 

Ques: 8. What is reinforcement learning?

Answer: 

Reinforcement Learning is a learning mechanism about how to map situations to actions. The end result should help you to increase the binary reward signal. In this method, a learner is not told which action to take but instead must discover which action offers a maximum reward. As this method based on the reward/penalty mechanism.

 

Ques: 9. While working on a data set, how can you select important variables? Explain.

Answer: 

Following methods of variable selection you can use:

• Remove the correlated variables before selecting important variables
• Use linear regression and select variables which depend on that p values.
• Use Backward, Forward Selection, and Stepwise Selection
• Use Xgboost, Random Forest, and plot variable importance chart.
• Measure information gain for the given set of features and select top n features accordingly.

 

Ques: 10. What cross-validation technique would you use on a time series dataset?

Answer: 

Instead of using k-fold cross-validation, you should be aware to the fact that a time series is not randomly distributed data - It is inherently ordered by chronological order.

In case of time series data, you should use techniques like forward chaining – Where you will be model on past data then look at forward-facing data.

fold 1: training[1], test[2]

fold 1: training[1 2], test[3]

fold 1: training[1 2 3], test[4]

fold 1: training[1 2 3 4], test[5]

 

Ques: 11. What is deep learning?

Answer: 

Deep learning is subfield of machine learning inspired by structure and function of brain called artificial neural network. We have a lot of numbers of algorithms under machine learning like Linear regression, SVM, Neural network etc and deep learning is just an extension of Neural networks. In neural nets we consider small number of hidden layers but when it comes to deep learning algorithms we consider a huge number of hidden layers to better understand the input output relationship.

 

Ques: 12. What is the difference between machine learning and deep learning?

Answer: 

Machine learning:

Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Machine learning can be categorized in following three categories.

• Supervised machine learning,
• Unsupervised machine learning,
• Reinforcement learning

Deep learning:

Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks.

 

Ques: 13. What is selection bias?

Answer: 

Selection bias is the bias introduced by the selection of individuals, groups or data for analysis in such a way that proper randomization is not achieved, thereby ensuring that the sample obtained is not representative of the population intended to be analysed. It is sometimes referred to as the selection effect. The phrase “selection bias” most often refers to the distortion of a statistical analysis, resulting from the method of collecting samples. If the selection bias is not considered, then some conclusions of the study may not be accurate.

 

Ques: 14. What is TF/IDF vectorization?

Answer: 

TF–IDF is short for term frequency–inverse document frequency, is a numerical statistic that is intended to reflect how important a word is to a document in a collection or corpus. It is often used as a weighting factor in information retrieval and text mining. The TF-IDF value increases proportionally to the number of times a word appears in the document, but is offset by the frequency of the word in the corpus, which helps to adjust for the fact that some words appear more frequently in general.

 

Ques: 15. What is the difference between Regression and classification ML techniques?

Answer: 

Both Regression and classification machine learning techniques come under Supervised machine learning algorithms. In Supervised machine learning algorithm, we must train the model using labelled dataset, while training we must explicitly provide the correct labels and algorithm tries to learn the pattern from input to output. If our labels are discreate values then it will a classification problem, e.g A,B etc. but if our labels are continuous values then it will be a regression problem, e.g 1.23, 1.333 etc.

 

Ques: 16. What is p-value?

Answer: 

When you perform a hypothesis test in statistics, a p-value can help you determine the strength of your results. p-value is a number between 0 and 1. Based on the value it will denote the strength of the results. The claim which is on trial is called Null Hypothesis.

Low p-value (≤ 0.05) indicates strength against the null hypothesis which means we can reject the null Hypothesis. High p-value (≥ 0.05) indicates strength for the null hypothesis which means we can accept the null Hypothesis p-value of 0.05 indicates the Hypothesis could go either way. To put it in another way,

High P values: your data are likely with a true null.
Low P values: your data are unlikely with a true null.

Ques: 17. What are the differences between overfitting and underfitting?

Answer: 

In order to make reliable predictions on general untrained data in machine learning and statistics, it is required to fit a (machine learning) model to a set of training data. Overfitting and underfitting are two of the most common modelling errors that occur while doing so.

Following are the differences between overfitting and underfitting:

Definition - A statistical model suffering from overfitting describes some random error or noise in place of the underlying relationship. When underfitting occurs, a statistical model or machine learning algorithm fails in capturing the underlying trend of the data.

Occurrence – When a statistical model or machine learning algorithm is excessively complex, it can result in overfitting. Example of a complex model is one having too many parameters when compared to the total number of observations. Underfitting occurs when trying to fit a linear model to non-linear data.

Poor Predictive Performance – Although both overfitting and underfitting yield poor predictive performance, the way in which each one of them does so is different. While the overfitted model overreacts to minor fluctuations in the training data, the underfit model under-reacts to even bigger fluctuations.

 

Ques: 18. Could you explain the role of data cleaning in data analysis?

Answer: 

Data cleaning can be a daunting task since with the increase in the number of data sources, the time required for cleaning the data increases at an exponential rate.

This is due to the vast volume of data generated by additional sources. Also, data cleaning can solely take up to 80% of the total time required for carrying out a data analysis task.

Nevertheless, there are several reasons for using data cleaning in data analysis. Two of the most important ones are:

• Cleaning data from different sources helps in transforming the data into a format that is easy to work with. 
• Data cleaning increases the accuracy of a machine learning model.

 

Ques: 19. Can you explain Recommender Systems along with an application?

Answer: 

Recommender Systems is a subclass of information filtering systems, meant for predicting the preferences or ratings awarded by a user to some product.

An application of a recommender system is the product recommendations section in Amazon. This section contains items based on the user’s search history and past orders.

 

Ques: 20. What is exploding gradients?

Answer: 

“Exploding gradients are a problem where large error gradients accumulate and result in very large updates to neural network model weights during training.” At an extreme, the values of weights can become so large as to overflow and result in NaN values.

This has the effect of your model being unstable and unable to learn from your training data.

Gradient: Gradient is the direction and magnitude calculated during training of a neural network that is used to update the network weights in the right direction and by the right amount.

 

Top 20 Robotic Process Automation(RPA) Interview Questions and Answers

Ques: 1. What is Blue Prism’s Robotic Automation?

Answer: 

Robotic Automation infers process Automation’s where computer software drives present enterprise application software in a similar way that a user does. Automation is a gadget that operates other application software through the present application UI.

 

Ques: 2. What are benefits of Robotic Process Automation?

Answer: 

Benefits of RPA are:

• Faster: As bots are dealing with the execution here, a greater measure of work can be done in a relatively much shorter period. A faster delivery coupled with accuracy. 
• Consistency: It is a safe, non-invasive technology that doesn’t interfere with the inherent systems and provides impeccable consistency in performing the activities across the board, each time. 
• Cost Effective: It has been projected that using robotics cuts operational costs, Robots can operate 24*7 and take no leave, when compared to humans. 
• Increased Customer Satisfaction: Providing better quality of work with optimum accuracy and improved customer/client interaction leads to increased customer and client satisfaction. 
• Accuracy & Quality: RPA offers better services to processes that have a high probability of human error, thereby increasing accuracy. Robots are reliable, consistent and do not whine when expected to work tirelessly. 
• Improved Analytics: Having access to error free, perfect data from various sources would improve the quality of analytics in the process.

 

Ques: 3. What is the difference between thin client and thick client?

Answer:

Thin client: It is any application that we cannot get the quality properties while spying using any RPA tools.

e.g.  Any virtual environment

Thick client: It is any application that we get pretty handful of attribute features using RPA tools

e.g. calculator, Internet explorer.

 

Ques: 4. What are the important Phases of RPA Life Cycle?

Answer:

Phases of RPA Life Cycle:

• Analysis: The first phase in RPA begins with analysis. Business team and RPA Architect work together to understand a business process for RPA development. 
• Bot Development: RPA developer (Team) starts working on the requirement in their environment possibly a distinct development environment. 
• Testing: Some companies conduct Testing by Separate Testing Team, while some have a dedicated testing team which performs a dedicated QA like normal SDLC flow. Best Practice is to have a dedicated testing team which performs QA of developed bot. 
• Deployment and Maintenance: After the Development and Testing phases, a bot is ready for distribution and enters maintenance phase.

 

Ques: 5. What are Limitations of Robotic Process Automation?

Answer: 

Limitations of RPA are:

• RPA surely improves company efficiency by powering repetitive human effort, but there are limitations to the types of work that it can be applied to – especially ones that require judgment. 
• Enterprises need to be aware of various inputs coming from multiple sources. 
• It cannot read any data that is non-electronic with unstructured inputs. 
• RPA is not a cognitive computing solution. It cannot learn from experience and therefore has a ‘shelf life’. 
• Implementing RPA to a broken and incompetent process will not fix it. RPA is not a Business Process Management solution and does not bring an end-to-end process view.

 

Ques: 6. How is RPA going to impact the BPO offshore market?

Answer: 

All the large BPO providers have made bold statements about what RPA will do for their businesses. For instance, some declare that it will automate 50% of the FTEs performing the processes today. These are the companies that have stated targets and business plans to increase their revenues and are trying to move up the value chain. 

This is where we see a real gap in the market, which we are addressing by starting to offer services around Robotic BPO (R-BPO). If you have a process that is well-suited for automation, we can provide that as a service and handle the exceptions.

 

Ques: 7. What are the various categories of RPA tools?

Answer: 

All RPA tools can be categorized by the functionality they provide in these 3 dimensions:

1. Programming options: RPA bots need to be programmed and there are a few ways to program bots which involve trade-offs between complexity of bots and programming time. 
2. Cognitive capabilities: Programmed bots need to have cognitive capabilities to determine their actions based on inputs they gather from other systems. RPA tools provide a range of cognitive capabilities. 
3. Usage: Bots serve specific functions. Though most RPA tools can be used to build bots that serve all these functions, some tools are more optimized for attended or unattended automation. While unattended automation is batch-like background processes, in attended automation users, for example customer service reps, invoke bots like invoking macros.

 

Ques: 8. What’s the future of RPA?

Answer: 

There are some problems of RPA for which the leading solution providers are working to fix. All these solutions focus on the 2 most expensive portions of RPA deployment:

1. Design & development and
2. Maintenance.

There solutions are:

1. No code RPA: Enabling companies rely on cheaper resources and reduce RPA development time. 
2. Self-learning RPA: Automating process modelling using system logs and videos of users working on the process. 
3. Cognitive RPA: Enriching RPA with advanced functionality such as image processing and Natural Language Processing.

 

Ques: 9. What are reusable RPA plugins/bots?

Answer: 

Reusable RPA plugins/bots are programs that can be added to your RPA tool to take care of specific tasks like data extraction from invoices, manipulating dates in different databases, transcribing speech etc. Therefore, they reduce development efforts, error rates and implementation time.

 

RPA is a flexible automation platform. Therefore, rolling out RPA solutions require significant programming and customization. In this way, RPA is analogous to programming languages and platforms which are also flexible automation tools. Functions are critical in software development as they enable code reusability, reducing development time and errors. RPA is no different, reusability reduces RPA development times and programming errors.

 

Ques: 10. What are the common pitfalls need to be avoided in RPA implementation?

Answer: 

We have seen 3 types of pitfalls in RPA implementations:

1. Organizational pitfalls: Lack of commitment either from management or the team itself can delay any project and RPA projects are no exception.
2. Process pitfalls: Choosing an overly complex or insignificant process will lead to limited impact. For example, implementing RPA to an area like expense auditing where specialized solutions exist, can lead to significant effort without satisfying results.
3. Technical pitfalls: Choosing a difficult-to-use RPA tool can slow down development efforts.

 

Ques: 11. How the Robotic Process Automation is reliable and secure, and why RPA is significant?

Answer: 

For every business venture, the eventual goal in mind is to gain a bit more than has been invested in the first place as a capital. For that matter, RPA is a proven technology that reduces human labor by replacing it with robots that not tend to spawn prone error-ridden operational processes.

By propelling and encouraging parallel operations that range from fundamental front end and back end processes to the advanced cloud-based environments, RPA expedites the performance of the heaping workloads well before the deadline.

 

Ques: 12. Name the systems that can be robotically integrated with Blue Prism?

Answer: 

The notable distinctive feature of Blue Prism is its ability to incorporate diverse sources of technologies into its software systems. The integrated technologies in turn synchronized with Blue Prism software infrastructure, thus becoming robust and secure.

Rather than setting up individual adaptors for every single application in the software, Blue Prism comes packed with technologies and programmed with tools like Java, Windows, Green Screen, and Mainframe.

These settings are additionally allied with even more resolute tools so that they could be linked with Blue Prism. Without impacting the already existing systems, Blue Prism adapts with quite an adaptability the newly designed, built, and tested applications.

 

Ques: 13. What are the important stages of RPA lifecycle?

Answer: 

The various important stages of RPA lifecycle:

1). Analysis: To develop a potential RPA business process, RPA architects and business management team collaborate to analyse and identify the business process.

2). Bot Development: At this phase, an agent that simulate the human activity is induced so that the robotic process could develop.

3). Testing: The developed bot is tested with the specially designed QA that certifies the successful architecture of the product.

4). Deployment and Maintenance: Once an RPA product is done, it is launched to be deployed to the user-end and maintained with carefully developed additional tool systems.

 

Ques: 14. How Robotic Automation is different from macros and screen scratching?

Answer: 

Unlike the generation-old applications like screen scratching and macros, any given application that is used by human can also be used by robots. RPA is equipped with handling complex applications like web frameworks, mainframes, web service apps, and can work efficiently with Application Programming Interface (API) hosting services.

These applications are read by the robot, either through existing APIs where they are prolonging, through the operating systems before applications appear. In this case, the modern robots reads an application screen in context and in the same way a user does. As part of the robot training, it is shown how to read the display of the application much like a user.

 

Ques: 15. What are the framework types used in Automation Anywhere?

Answer: 

The following frameworks are used in Automation Anywhere:

1. Data-driven automation framework.
2. Keyword Driven Automation Framework.
3. Modular automation framework.
4. Hybrid Automation Framework.

 

Ques: 16. What is the role of the RPA developer?

Answer: 

Process Designer is responsible for understanding the current process. He / she ensures that the people working on the RPA project are synchronized. It also monitors the changes that occur after the implementation of the feedback during the development or test phase, keeping project specifications intact.

 

Ques:17. Does RPA store data?

Answer: 

The RPA stores data Although all are known as RPA, each of them is selected according to the processes or tasks that the organization wants the robots to handle. There are ‘probots’, which process data, ‘knowbots’ to collect and store data, and ‘chatbots’ that act as virtual agents to respond to customer queries in real time.

 

Ques: 18. What can the RPA not do?

Answer: 

Of robotic processes, also known as RPA, is a rapid and important change that is invading many industries. … RPA can help your company employees set up computer software or a robot to capture and interpret existing applications to help manufacture, transfigure, and analyse data.

 

Ques:19. What are the various features of RPA?

Answer: 

The important features of RPA are:

1). User-Friendly: RPA selection starts inside business tasks rather inside IT divisions. RPA ventures require less IT aptitudes and less speculation. In the long run, the robotization is brought down at a generous rate.

2). Rick Free: RPA (Robotic Process automation) is low complexity and risk-free from other Tools. RPA access to end users’ systems Through a controlled user interface, hence Increasing the Important of underlying systems programming.

3). Code Free: RPA (Robotic Process automation) doesn’t require programming skills. anyone can Learn RPA With Simple Effect Because Its run’s without coding, with any subject expertise, can be trained to automate RPA tools instantly. RPA tool Designed with charts and flowcharts.

 

Ques: 20. Is Blue Prism’s Robotic Automation Platform secure and auditable?

Answer: 

Security and auditability are consolidated into the Blue Prism robotic automation platform at various levels. The runtime environment is totally separate to the process editing environment.

Approvals to design, create, edit and run processes and business objects are specific to each authorized user. A full audit trail of changes to any process is kept, and comparisons of the before and after effect of changes are provided.

The log created at run-time for each process provides a detailed, time-stamped history of every action and decision taken within an automated process. Our clients tend to find that running a process with Blue Prism gives them a lot more control than a manual process, and from a compliance point of view assures that processes are run consistently, in line with the process definition.