Friday, 24 August 2018

SSIS Interview Questions And Answers for beginner and experienced

  1. What is MSBI ?

        MSBI stands for Microsoft Business Intelligence MSBI (Microsoft Business Intelligence) is one of the ETL tool related to the database side. MSBI is composed of tools which helps in providing best solutions for Business Intelligence and Data Mining Queries.

    MSBI is divided into 3 categories:-

  • SSIS – SQL Server Integration Services – Integration tool.
  • SSAS – SQL Server Analytical Services -Analysis tool.
  • SSRS – SQL Server Reporting Services – Reporting tool

  1. SSIS– This tool is used for the integration like duping the data from one database to another like from Oracle to SQL Server or from Excel to SQL Server etc.
    This tool is also used for bulk transactions in the database like inserting lac's of records at once. We can create the integration services modules which will do the job foe us.
  2. SSAS– This tool is used to analyse the performance of the SQL server in terms of load balancing, heavy data, transaction etc. So it is more or less related to administration of the SQL Server using this tool. This is very powerful tool and through this we can analyse the data inserting in to the database like how many transactions happens in a second etc.
  3. SSRS– This tool is related to the generation of report. This is very efficient tool as it is platform independent. We can generate the report using this tool and can use in any type of applications. Now a days this is very popular in the market.

Q. What is SSIS variable?

Variables store values that a SQL Server Integration Services package and its containers, tasks, and event handlers can use at run time.

In SSIS two variables are defined
  • Global variables:- A global variable is available to all tasks across the entire job. 
  • Task level variables: - Variables created in tasks are only available within that task.

Q. What is SSIS Control flow?

SSIS control flow allows you to program graphically how the tasks will run by using the logical connectors between tasks.

There are three basic logical connectors that you can use:
  • Success 
  • Failure 
  • Complete

Q. What is precedence constraint?

In SSIS, tasks are linked by precedence constraints. A task will only execute if the condition that is set by the precedence constraint preceding the task is met.

The control flow in a SQL Server Integration Services (SSIS) package defines the workflow for that package. Not only does the control flow determine the order in which executable will run, the control flow also determines under what conditions they’re executed.

  • Success: The precedence executable must run successfully for the constrained executable to run. This is the default value. The precedence constraint is set to green when the Success option is selected. 
  • Failure: The precedence executable must fail for the constrained executable to run. The precedence constraint is set to red when the Failure option is selected. 
  • Completion: The constrained executable will run after the precedence executable runs, whether the precedence executable runs successfully or whether it fails. The precedence constraint is set to blue when the Completion option is selected.

Q. Defined the different type of containers in SSIS packages

In SSIS there are three type of Container:-


1. Sequence Container: - Sequence container defines the control flow that is subset of package control flow. Sequence containers group the package into multiple separate control flows, each containing one or more tasks and containers that run within the overall package control flow.

Advantage: -

· Disable the property of sequence container instead of on the individual tasks.

· Change the property of sequence container instead of on the individual tasks.

· Providing scope for variables that a group of related tasks and containers use.

2. For Loop container: - It’s define the repeated control flow in a package. It’s working like loop in programming languages. In each repeated loop for each loop evaluate the expression until the expression is false. Example, you need to update records 5 times, you can place the task that updates the records inside this for loop container and specifies 5 as the end of the loops by using the for loop container.


For loop Properties:-

  • InitExpression:- Optionally, provide an expression that initializes values used by the loop. 
  • EvalExpression:- Provide an expression to evaluate whether the loop should stop or continue. 
  • AssignExpression:- Optionally, provide an expression that changes a condition each time that the loop repeats. 
  • Name:- Provide a unique name for the For Loop container. This name is used as the label in the task icon. 
  • Description:- Provide a description of the For Loop container. 

3. Foreach loop container

It’s defines a repeating control flow in a package. Foreach loop implementation is similar as programming languages. In a package, looping is enabled by using a Foreach enumerator. The Foreach Loop container repeats the control flow for each member of a specified enumerator.

SSIS provides these following enumerator types:

  • ForEach File Enumerator 
  • Foreach Item Enumerator 
  • Foreach ADO Enumerator 
  • Foreach ADO.NET Schema Rowset Enumerator 
  • Foreach From Variable Enumerator 
  • Foreach NodeList Enumerator 
  • Foreach SMO Enumerator

Saturday, 5 May 2018

New 2018-19 McDonald's Interview Questions Answers

Are you one of those children who always want to work at McDonald's? Are you looking for work and you see that McDonald's can be your great opportunity? Do you have an interview with them and do not know where to start? Today is your lucky day. I want to confess some of the best kept secrets to overcome your next interview at McDonald's.

Go for it!

Before going to the interview, learn well about the company, because as it is very recognized and is very integrated into our lives it is easy for everyone to say the same things about it, so take a step further and take advantage of this advantage.

Find something that you can say that is positive, original, different ... That makes you stand out!

Well dressed and with good presence: Do not go formal , but with a good image. It is possible to end up working facing the direct public (cashier, store assistant) or indirectly (kitchen, manager).
Come early: If you arrive late, they will think that you have no interest and that you are a disorganized person, but if you arrive very soon, you will seem impatient, restless, anxious ... Ideally, you should arrive between 10 and 5 minutes early.
Pay attention to the smells! Be well groomed, do not get into a race because you are late before entering. You will throw everything away! Avoid smoking and drinking coffee before entering.

Analyze how they work at Mcdonald's: In front of the public, as a team, under pressure, in turns ... If you want to work here, be able to work according to your philosophy and work rate .

Highlight what skills you have that fit your operation.

Now, we begin! These are the most common questions in the selection process:

I want to work at Mcdonald's because it is an international company that offers me the possibility to train and be part of a multidisciplinary team. In addition, it gives me security the fact of being a great company, not only at work level, but also in quality and management of all processes.

Yes, working face to face with the public helps make the experience more rewarding, working in contact with other people offers extra human value.

It is important that you emphasize your ability to work as a team, your energy, flexibility, positive attitude ... and that you face without fear the changing situations.

Show yourself as a person that cooperates, that helps others, that you never stop ... At Mcdonald's they value that you move and that, if you have nothing to do, help others to get the job done, even if you do not have to see with your functions.

He talks about how enriching it is to work as a team, that each contribution is important to achieve common goals, that you listen to others, that you know how to negotiate and reach agreements.

What are you busy? You should analyse the importance of what you are doing at this moment and if it is not more important, take care of the food in poor condition yourself, do you have someone nearby who can take care of it? Tell him to take charge. If you can tell a manager better than better, but if not, to a partner. In any case, you will have to tell the person in charge, even if it is later.

No, unless it is absolutely essential to solve a problem.

Serving food has given me extensive experience facing the public and solving problems with customers on a daily basis. In addition, this experience will make me more willing to take care of the store when necessary.

The questions of the weaknesses formulated in another way ... "I am too demanding and that makes me add more pressure than necessary ..."

I would not have any problem. At first I may not have as much ease as in my own position, but I learn quickly and then I would perform them as if they were my own functions.

(Do not show fear, or rejection, they are not telling you what's going to happen, they just want to see your capacity for learning and adopting changes, flexibility and facing challenges)

First: Listen to what the complaint is!
Second Can I solve it? I'll do it!
Third: Can not I solve it? I bring it to the attention of my superiors.
And above all, stay calm and sure of yourself. luck!

How Prepare for face 5 most common types of interview questions

Prepare for the questions that recruiters will ask you and give an effective response.
From the interview we expect a professional conversation, focused mainly on our skills and achievements, however, sometimes the recruiter will look for 'something else' about us with questions that may not be directly related to employment.

For many candidates some interview questions do not have a logical reason, they can even be absurd or uncomfortable, so we must be prepared and anticipate to respond with intelligence.

Prepare to face the 5 most common types of interview questions:
1. Open: They are general questions that seek to flow the dialogue between the interviewer and the candidate, allow the person a broad response. With them your fluency, communication skills and coherence will be evaluated.

Example: Tell me about yourself, why were you interested in the vacancy? Why did you decide to study (insert career)? What do you like most about your work?

Tip: It is possible to prepare in advance to answer these types of questions, since they are very common. It is important to find a balance in our speech to express ourselves with ease without giving very long answers. Concentrate on the most meaningful and relevant information.

2. Fitness: Its objective is to evaluate if the candidate has the necessary knowledge to perform the job. Depending on the vacancy, the recruiter will inquire about the candidate's experience and the competencies he or she has.

Example: What were the main functions you performed in your previous job? , Tell me what knowledge and skills prepare you for the position, I see that you have advanced knowledge in (insert skill / knowledge) in what kind of activities have you applied the last 3 years?

Tip: Probably a lot of this information is contained in your Curriculum, however the recruiter will want to have a bigger picture. Using specific examples can help you clearly show why you meet the expectations of the position.

3. Behavior: When making a contract, it is not only important that the candidate can do the job. The behavioral questions seek to find out what the person's behavioral profile is, to assess whether they can successfully integrate into the work team.

Example: How do you handle stress ?, Give me an example in your work life in which you have shown integrity, Tell me about a time when you made a mistake in your work, how did you solve it?

Tip: Anticipate this type of questions by analyzing how your behavior at work is, what are your strengths and what are your areas of opportunity. Prepare yourself with clear examples of scenarios typical of the work environment such as stress, pressure, decision making, labor conflicts, etc.

4. Situational: Once the interviewer analyzes your behavior in the past you can resort to situational questions to get an idea of ​​what your future behaviors will be.

Example: How do you respond to pressure? Imagine that you have X problem at work, how would you solve it? What would you do if your boss delivers a report with erroneous figures in a work meeting?

Tip: For situational questions there is not a single correct answer, it will reveal our ability to solve problems and adapt to different situations. A good practice is to think about a similar experience that you have lived and talk about how you used your skills to face it.

5. Capciosas: It may seem absurd or incoherent questions, but depending on the recruiter, the company and the position, you may have to answer questions that seem to leave the work context. Its purpose is to move the candidate a little away from standard questions and subject him to a mental challenge that reveals a little more about his personality.

Example: If you could be an animal, what would you be? What color is there more objects in your bedroom? What would you prefer? Being the number 1 employee but hated by your colleagues or number 15 but appreciated by all?

Tip: With these questions the recruiter expects an honest and spontaneous answer, remember that there are no correct answers, since they are linked to your personality.

* Inappropriate Questions
It is common for candidates to face misplaced questions, which can be discriminatory and offensive. For example, are you pregnant? What contraceptive method do you use? What is your sexual orientation? Why are not you married? Are you religious / religious?

Friday, 23 March 2018

IBM Announced MAX - Model Asset eXchange: an App Store for Machine Learning Models

Over at the IBM Blog, Dr. Angel Diaz writes that the company has just launched the Model Asset eXchange. MAX is effectively an App Store for free Machine Learning models to help developers and data scientists easily discover, rate and deploy AI.

IBM states on the official blog--
We are excited to announce one of the first initiatives in this space — an open source enterprise Model Asset eXchange, or “MAX”. MAX is a models app store that aims to ignite a community of data scientists and AI developers, enabling them to easily discover, rate, and deploy machine learning models. MAX is a one-stop exchange for data scientists and AI developers to consume models created using their favorite machine learning engines, like TensorFlow, PyTorch, and Caffe2, and provides a standardized approach to classify, annotate, and deploy these models for prediction and inferencing, including an increasing number of models that can be deployed and customized in IBM’s recently announce AI application development platform, Watson Studio.

This message is very much echoed by Jim Zemlin, Executive Director of The Linux Foundation. “IBM’s release of Model Asset eXchange gives developers a new source for deep learning models. We look forward to seeing the innovation unlocked from the MAX community through collaboration with our forthcoming Acumos AI community.”

WhatsApp will debut on JioPhone: Tech News

WhatsApp has been continuously bringing new features to its users on both Android and iOS platforms over the past few weeks. Now WhatsApp is possibly working to bring its real-time messenger app to the emerging KaiOS. The proof of that has been found on one of the latest WhatsApp beta versions for Windows Phone, which suggests that new platforms could soon be utilising WhatsApp servers.
That new platform is expected to be KaiOS, which has recently got Facebook’s native app for the JioPhone. The JioPhone utilises KaiOS as its operating system and supports 4G VoLTE services along with support for Wi-Fi and Bluetooth. It’s not yet known whether WhatsApp could be coming with a majority of its features on the platform or be simply limited to basic messaging service. However, with Facebook already available on the JioPhone, the availability of WhatsApp on the feature phone could give a boost to the JioPhone’s sales and could find favour with more users looking to simplify their phone usage.

Microsoft Blazor 0.1.0 Released

Microsoft has recently released the first public preview of a new .NET web framework, Blazor. This new .NET web framework uses C#/Razor and HTML using the browser with WebAssembly. Blazor enables the full stack web development with the productivity of .NET but, as this is an alpha version it should not be used in production.

Microsoft states in the official blog –
“In this release, we've laid the groundwork for the Blazor component model and added other foundational features, like routing, dependency injection, and JavaScript interop. We've also been working on the tooling experience so that you get great Intelli-Sense and completions in the Razor editor. Other features that have been demonstrated previously in prototype form, like live reload, debugging, and prerendering, have not been implemented yet, but are planned for future preview updates. Even so, there is plenty in this release for folks to start kicking the tires and giving feedback on the current direction.”

What makes you happy about working on a Friday evening?

Weekends is the only reasons which makes person happy about working on a Friday evening. It is totally to discuss it because taking break from work is your right. So honestly you can discuss your points and views with your interviewer.

Sunday, 4 March 2018

Machine Learning Interview Questions Answers: Scope of Machine Learning

Many of us believe that machine learning is a very futuristic thing. However, it is increasingly present in our lives, whether when a Google computer plays an incredible game of Go, or when Gmail generates automatic responses. While all this sounds exciting, many of us continue to wonder what machine learning exactly consists of, why it is so important or why identifying a dog in a photo is not as simple as it seems. In order to analyze all this, we have met with Maya Gupta, a researcher at Google in this field.

Let's start with the simplest: what exactly is machine learning?
It is the process of machine learning that takes a set of examples, discovers the patterns behind them and uses them to make predictions about new examples.

Think, for example, about movie recommendations. Let's suppose that a billion people tell us their ten favorite movies. That would be the set of examples that the computer can use to discover which movies are common among that group of people. Next, the computer elaborates patterns to explain those examples, such as "People who like horror movies do not like romantic ones, but they do like movies in which the same actors appear". Therefore, if you tell the computer that you like The Shining of Jack Nicholson, you can deduce if you also like romantic comedy.

We understand it or almost. However, how does this translate into practice?
In practice, the patterns that the machine learns can be very complex and difficult to explain with words. Let's use Google Photos as an example, which allows you to search your photos for pictures of dogs. How does Google do it? Well, first, we use a set of examples of photos labeled "dog" (thanks to the Internet). We also use a set of photos labeled "cat", as well as photos with millions of different labels, but I will not list them all here.

Next, the computer looks for patterns of pixels and patterns of colors that help you to find out if it is a cat, a dog or anything else. First, he makes a random estimate of the patterns that might be adequate to identify dogs. Then examine an example of an image of a dog and see if its patterns fit correctly. If you check that a cat is mistakenly called a cat, make some adjustments to the patterns used. Then examine the image of a cat and refine its patterns to try to get the most accurate. This process is repeated about a billion times: it examines an example and, if the pattern is not correct, it changes it to improve the result of it.

In the end, the patterns constitute a model of machine learning, as if it were a deep neural network that can (almost) correctly identify dogs, cats, firemen and many other things.

That sounds very futuristic. What other Google products currently use machine learning?
Google is using machine learning in many new projects, such as Google Translate, which can take a picture of a signage sign or restaurant menu in a language, discover the words and language that appear in the photo, and translate them by magic and in real time to your language.

You can also send almost any voice message to Google Translate and speech recognition can be processed by machine learning. Speech recognition technology is used in other Google products, for example, to make voice queries in the Google application or to search for videos more easily on YouTube.

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Machine learning is the same as artificial intelligence?
Although in reality the meaning of these concepts can vary according to people, artificial intelligence (AI) is basically a broad term that refers to software that tries to solve problems that are simple for humans, such as describing what happens in an image. One of the most incredible things that humans do with ease is to learn from the examples. This is what machine learning programs are trying to do: teaching computers how to learn from examples.

The best thing is that when we discovered how to develop these software, we can expand this knowledge to handle data very quickly and solve really complex problems such as, for example, play as an expert to the Go, tell the way to all users so Simultaneously, optimize energy consumption nationwide and, my favorite, find the best results in the Google search engine.

So, why is Google now giving so much importance to machine learning?
Machine learning is not something new, since it goes back to the eighteenth century statistics, but it is true that lately it is booming and this is due to three reasons that I will explain below.

The first one is that we need an immense amount of examples to teach computers how to make good predictions, even about things that you and I consider easy (like finding a dog in a photo). With all the activity on the Internet, we now have a broader source of examples that computers can use. For example, there are now millions of pictures of dogs with the "dog" tag on websites around the world and in all languages.

But it is not enough to have many examples. You can not simply show a bunch of dog photos to a webcam and expect him to learn everything; the computer needs a learning program. In fact, lately the sector (and also Google) has made important advances in terms of the complexity and power that these learning programs can have.

However, our programs are still not perfect and computers are still not very intelligent, so we have to see many examples numerous times to change the digital controls and get accurate results. Although this requires enormous processing capacity, new advances in software and hardware have also made this possible.

Is there something that computers can not do today but what can they do in the future thanks to machine learning?
Until now, the voice recognition tried to detect only ten different digits when you said your credit card number by phone. Voice recognition has achieved incredible advances in the last five years with the use of machine learning, and now we can use it to search Google and every time more quickly.

I think machine learning can also help us improve our appearance. I do not know about you, but I hate to try on clothes. If I find a jeans brand that suits me, I buy five. Well, machine learning can convert examples of brands that we feel good into recommendations of other clothes that could equally well fit. This is out of Google's reach, but I hope someone is investigating it.

What will machine learning be like in ten years?
The sector is currently working to achieve faster learning from fewer examples. One way to address this (something that Google is emphasizing) is to provide our machines with more common sense, what in the sector is called "regularization".

What is common sense for a machine?
In general, it means that if an example changes only a little, the machine should not omit it. That is, a picture of a dog wearing a cowboy hat is still a dog.

We impose this kind of common sense when we get that machine learning is able to obviate small and insignificant changes, like a cowboy hat. Although this seems easy to say, if we make a mistake, it is possible that a machine does not detect important changes well. It is about reaching a balance and we are still working to achieve it.

For you, what is the most exciting thing about machine learning? What motivates you to work with him?
I grew up in Seattle, where we learned a lot about the first explorers in the Western United States, such as Lewis and Clark. Machine learning has that same spirit of exploration, since we discover things for the first time and try to trace a path towards a great future.

If you could put a slogan to Google's machine learning, what would it be?
If you do not get it first, try a billion times more.