Blockchain

What is Hashing?

Hashing is simply passing some data through a formula that produces a result, called a hash. That hash is usually a string of characters and the hashes generated by a formula are always the same length, regardless of how much data you feed into it. For example, the MD5 formula always produces 32 character-long hashes. Regardless of whether you feed in the entire text of MOBY DICK or just the letter C, you’ll always get 32 characters back.

Hashing is One-Way

Hashing works in one direction only – for a given piece of data, you’ll always get the same hash BUT you can’t turn a hash back into its original data. If you need to go in two directions, you need encrypting, rather than hashing.

With encrypting you pass some data through an encryption formula and get a result that looks something like a hash, but with the biggest difference being that you can take the encrypted result, run it through a decryption formula and get your original data back.

Remember, hashing is different – you can’t get your original data back simply by running a formula on your hash (a bit about how to hack these, though, in a moment).

To salt a hash, simply append a known value to the string before you hash it. For example, if before it’s stored in a database every password is salted with the string ‘dog’, it will likely not be found in online databases. So, password salted with dog (i.e. passworddog) and then run through the md5 calculator becomes 854007583be4c246efc2ee58bf3060e6.

Reference:

 https://www.edureka.co/blog/interview-questions/blockchain-interview-questions/

https://dataspace.com/big-data-applications/what-does-it-mean-to-hash-data/

System Analyst - 1

 

RAID

RAID stands for Redundant Array of Inexpensive Disks. That means that RAID is a way of logically putting multiple disks together into a single array. 

RAID 0 (Striping)

RAID 0 is taking any number of disks and merging them into one large volume. This will greatly increase speeds, as you're reading and writing from multiple disks at a time.

RAID 1 (Mirroring)

A pair of identical disks identically mirror/copy the data equally across the drives in the array. The point of RAID 1 is primarily for redundancy. If you completely lose a drive, you can still stay up and running off the additional drive.

RAID 5/6 (Striping + Distributed Parity)

-RAID 5 requires the use of at least 3 drives (RAID 6 requires at least 4 drives). 

-It takes the idea of RAID 0, and strips data across multiple drives to increase performance. But, it also adds the aspect of redundancy by distributing parity information across the disks. 

-With RAID 5 you can lose one disk, and with RAID 6 you can lose two disks, and still maintain your operations and data.

-RAID 5 and RAID 6 are often good options for standard web servers, file servers, and other general purpose systems where most of the transactions are reads, and get you a good value for your money. This is because you only need to purchase one additional drive for RAID 5 (or two additional drives for RAID 6) to add speed and redundancy.

-RAID 5 or RAID 6 is not the best choice for a heavy write environment, such as a database server, as it will likely hurt your overall performance. 

RAID 10 (Mirroring + Striping)

RAID 10 requires at least 4 drives and is a combination of RAID 1 (mirroring) and RAID 0 (striping). This will get you both increased speed and redundancy. This is often the recommended RAID level if you're looking for speed, but still need redundancy. In a four-drive configuration, two mirrored drives hold half of the striped data and another two mirror the other half of the data. This means you can lose any single drive, and then possibly even a 2nd drive, without losing any data. Just like RAID 1, you'll only have the capacity of half the drives, but you will see improved read and write performance. You will also have the fast rebuild time of RAID 1.

R

R is a programming language and software environment for statistical analysis, graphics representation and reporting. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team.

The core of R is an interpreted computer language which allows branching and looping as well as modular programming using functions. R allows integration with the procedures written in the C, C++, .Net, Python or FORTRAN languages for efficiency.

R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows and Mac.

R is free software distributed under a GNU-style copy left, and an official part of the GNU project called GNU S.

 R is world’s most widely used statistics programming language. It's the # 1 choice of data scientists and supported by a vibrant and talented community of contributors. R is taught in universities and deployed in mission critical business applications.

Source: www.tutorialspoint.com

CRM software

CRM software consolidates customer information and documents into a single CRM database so business users can more easily access and manage it. The other main functions of this software include recording various customer interactions (over email, phone calls, social media or other channels, depending on system capabilities), automating various workflow processes such as tasks, calendars and alerts, and giving managers the ability to track performance and productivity based on information logged within the system.

Common features of CRM software include:
Marketing automations: CRM tools with marketing automation capabilities can automate repetitive tasks to enhance marketing efforts to customers at different points in the lifecycle. For example, as sales prospects come into the system, the system might automatically send them marketing materials, typically via email or social media, with the goal of turning a sales lead into a full-fledged customer.
Sales force automations: Also known as sales force management, sales force automation is meant to prevent duplicate efforts between a salesperson and a customer. A CRM system can help achieve this by automatically tracking all contact and follow-ups between both sides.
Contact center automations: Designed to reduce tedious aspects of a contact center agent's job, contact center automation might include pre-recorded audio that assists in customer problem-solving and information dissemination. Various software tools that integrate with the agent's desktop tools can handle customer requests in order to cut down the time of calls and simplify customer service processes.
Geolocation technology, or location-based services: Some CRM systems include technology that can create geographic marketing campaigns based on customers' physical locations, sometimes integrating with popular location-based GPS apps. Geolocation technology can also be used as a networking or contact management tool in order to find sales prospects based on location.

The CRM technology market: The four main vendors of CRM systems are Salesforce.com, Microsoft, SAPand Oracle. Other providers are popular among small- to mid-market businesses, but these four tend to be the choice of large corporations.

Project Charter

A project charter (PC) is a document that states a project exists and provides the project manager with written authority to begin work.

The document helps the project manager to communicate his authority and explain to project participants and stakeholders why the project is needed, who it involves, how long the project will take to complete, how much it will cost, what resources are needed and how successful completion of the project will help the organization. Once created, the document is rarely (if ever) amended.

Depending on a company's culture and management style, a charter may serve the same purpose as a business case.  In a large corporation, the charter may be a multi-page document written up by mid-level management after a business case has been approved but before the project scope has been defined.  In a small startup company, however, the charter might just be a few paragraphs with bulleted items and the company president’s signature.

Project charter templates often include the following components:

Project goal - documents the reasons for undertaking the project in clear, concise language.
Project participants - identifies what people need to be involved in the project and clearly states their roles.
Stakeholders - identifies other people who will be directly affected by the project and need to know about the project's progress.
Requirements - identifies what resources are required for the project's objectives to be achieved.
Constraints - documents potential roadblocks or bottlenecks.
Milestones - identifies start date and completion dates as well as dates for other important checkpoints.
Communication - specifies how the project manager will communicate with project owners, participants and stakeholders through the project.
Deliverables - documents what specific products, processes or services the project will provide upon completion.

Prerequisites for Developing Business Requirement Specification

§  Project Charter – The first prerequisite for the Business Requirements Specifications is the Project Charter. The Business Requirements Specification allows you to review the Project Charter and ensure that its objective, goals, scope, team, and approvers are correct.

§  Current Environment Assessment – The second prerequisite is a current environment assessment. This includes a process map of the current environment highlighting areas that will be changed during the project.

IT Jargon

Cloud computing

This is a classic example of an IT term that very few people can explain. Even company directors whose entire business model depends on cloud computing would struggle.

It becomes even more confusing when we refer to 'the cloud' as if it is some magical place in the sky. The cloud is basically a metaphor for the internet, so why not call it that?

That would essentially make cloud computing internet computing. Put it that way, and it may be easier to explain how it all works and prevent people from gazing expectantly at the heavens. 

XaaS

The term XaaS is used to describe something that is provided as a service over the internet. A cloud-based service, to use the jargon referred to above.

We have SaaS (Software as a Service), PaaS (Platform as a Service), IaaS (Infrastructure as a Service) and many more, and each acronym basically describes something that has traditionally been provided locally that is now provided via the web on a subscription or pay-per-use basis.

So it's cloud computing, right? Or internet computing as we've established? Well, yes, when you think about it. So perhaps we could just use the term internet-based services instead of adding all the a's and S's.

Big data

When we say big data, we essentially mean lots of data. In fact, it's a vast amount of structured and unstructured data that is coming from a huge array of different sources.

It's called big data, not because there's anything inherently new or different about it, but because it is now much more available to us, it's much more varied than ever before, and because we now have the technical capabilities to store it and to analyse it effectively.

In this sense, all data is big data. So why don't we just call it data? Of course it's not just the term big data itself that causes confusion, but the huge amount of jargon that's been invented around it, from NoSQL databases to acid tests and massively parallel processing. Now we're really confused.

Gamification

This is one we're hearing a lot at the moment, and it is used to describe the use of game elements in non-gaming applications to make them more engaging to users. It's about breaking things down into simple steps with rewards at the completion of each one, like a game.

It's become something of a buzz word - one of those that makes you sound really intelligent if you can throw it into a conversation. But it essentially means turning something that can be pretty boring into something fun.

Of course, the word gamification is used in other industries, but it crops up frequently in the IT sector because, let's face it, there's a lot about IT applications that is less than thrilling to those who don't have an innate passion for technology.

Digital disruptors

Who are these people? They sound like villains out to destroy our world. Well, this is and is not true. If you're a business owner, then perhaps they are, but if you're a consumer then the opposite is true. The digital disruptors can be the heroes, using technology to make everyone's lives that bit easier.

They are simply individuals or companies who employ technology to create better products and services than the non-digital versions that have come before. An example? The makers of the diet and fitness apps that are slowly eating away at subscriptions to traditional weight loss clubs.

In this sense, they are in fact disrupting traditional business models. But we live in a digital age, so of course technology is going to challenge what has come before. It's called moving with the times. If we didn't, we'd still be sending telegrams. So let's just call them rivals, shall we?

Cognos vs Informatica

Cognos and Informatica are not same tool that does the same work.

Informatica is a ETL tool.  It extracts data from various sources (Oracle, db2, Sybase, etc) transforms it and loads data into the warehouse.

Cognos is a reporting tool.  It is used for business purpose to generate some reports (may be pictorial or statistical representation).   It uses the datawarehouse information to generate a report.
Oracle business intelligence is another reporting tool which is becoming famous today.

Software Development Framework

.NET Framework (pronounced dot net) is a software framework developed by Microsoft that runs primarily on Microsoft Windows. It includes a large class library known as Framework Class Library (FCL) and provides language interoperability (each language can use code written in other languages) across several programming languages. Programs written for .NET Framework execute in a software environment (as contrasted to hardware environment), known as Common Language Runtime (CLR), an application virtual machine that provides services such as security, memory management, and exception handling. FCL and CLR together constitute .NET Framework.

FCL provides user interface, data access, database connectivity, cryptography, web application development, numeric algorithms, and network communications. Programmers produce software by combining their own source code with .NET Framework and other libraries. .NET Framework is intended to be used by most new applications created for Windows platform. Microsoft also produces an integrated development environment largely for .NET software called Visual Studio.

Grails is an Open Source, full stack, web application framework for the JVM. Grails is an open source web application framework that uses the Groovy programming language (which is in turn based on the Java platform). It is intended to be a high-productivity framework by following the "coding by convention" paradigm, providing a stand-alone development environment and hiding much of the configuration detail from the developer.[citation needed]

Grails was previously known as 'Groovy on Rails'; in March 2006 that name was dropped in response to a request by David Heinemeier Hansson, founder of the Ruby on Rails framework.[1] Work began in July 2005, with the 0.1 release on March 29, 2006 and the 1.0 release announced on February 18, 2008.

G2One - The Groovy Grails Company - was acquired by SpringSource in November, 2008,[2] and it was later acquired by VMware.[3]

A JDK is required in your Grails development environment. A JRE is not sufficient.

Grails was developed to address a number of goals:

Provide a web framework for the Java platform.

Re-use existing Java technologies such as Hibernate and Spring under a single interface

Offer a consistent development framework.

Offer documentation for key portions of the framework:

The Persistence framework.

Templates using GSP (Groovy Server Pages).

Dynamic tag libraries for creating web page components.

Customizable and extensible Ajax support.

Provide sample applications that demonstrate the framework.

Provide a complete development mode, including a web server and automatic reload of resources.

Kind of Testing

• Black box testing - not based on any knowledge of internal design or code. Tests are based on requirements and functionality.
• White box testing - based on knowledge of the internal logic of an application's code. Tests are based on coverage of code statements, branches, paths, conditions.
• unit testing - the most 'micro' scale of testing; to test particular functions or code modules. Typically done by the programmer and not by testers, as it requires detailed knowledge of the internal program design and code. Not always easily done unless the application has a well-designed architecture with tight code; may require developing test driver modules or test harnesses.
• incremental integration testing - continuous testing of an application as new functionality is added; requires that various aspects of an application's functionality be independent enough to work separately before all parts of the program are completed, or that test drivers be developed as needed; done by programmers or by testers.
• integration testing - testing of combined parts of an application to determine if they function together correctly. The 'parts' can be code modules, individual applications, client and server applications on a network, etc. This type of testing is especially relevant to client/server and distributed systems.
• functional testing - black-box type testing geared to functional requirements of an application; this type of testing should be done by testers. This doesn't mean that the programmers shouldn't check that their code works before releasing it (which of course applies to any stage of testing.)
• system testing - black-box type testing that is based on overall requirements specifications; covers all combined parts of a system.
• end-to-end testing - similar to system testing; the 'macro' end of the test scale; involves testing of a complete application environment in a situation that mimics real-world use, such as interacting with a database, using network communications, or interacting with other hardware, applications, or systems if appropriate.
• sanity testing or smoke testing - typically an initial testing effort to determine if a new software version is performing well enough to accept it for a major testing effort. For example, if the new software is crashing systems every 5 minutes, bogging down systems to a crawl, or corrupting databases, the software may not be in a 'sane' enough condition to warrant further testing in its current state.
• regression testing - re-testing after fixes or modifications of the software or its environment. It can be difficult to determine how much re-testing is needed, especially near the end of the development cycle. Automated testing approaches can be especially useful for this type of testing.
• acceptance testing - final testing based on specifications of the end-user or customer, or based on use by end-users/customers over some limited period of time.
• load testing - testing an application under heavy loads, such as testing of a web site under a range of loads to determine at what point the system's response time degrades or fails.
• stress testing - term often used interchangeably with 'load' and 'performance' testing. Also used to describe such tests as system functional testing while under unusually heavy loads, heavy repetition of certain actions or inputs, input of large numerical values, large complex queries to a database system, etc.
• performance testing - term often used interchangeably with 'stress' and 'load' testing. Ideally 'performance' testing (and any other 'type' of testing) is defined in requirements documentation or QA or Test Plans.
• usability testing - testing for 'user-friendliness'. Clearly this is subjective, and will depend on the targeted end-user or customer. User interviews, surveys, video recording of user sessions, and other techniques can be used. Programmers and testers are usually not appropriate as usability testers.
• install/uninstall testing - testing of full, partial, or upgrade install/uninstall processes.
• recovery testing - testing how well a system recovers from crashes, hardware failures, or other catastrophic problems.
• failover testing - typically used interchangeably with 'recovery testing'
• security testing - testing how well the system protects against unauthorized internal or external access, willful damage, etc; may require sophisticated testing techniques.
• compatibility testing - testing how well software performs in a particular hardware/software/operating system/network/etc. environment.
• exploratory testing - often taken to mean a creative, informal software test that is not based on formal test plans or test cases; testers may be learning the software as they test it.
• ad-hoc testing - similar to exploratory testing, but often taken to mean that the testers have significant understanding of the software before testing it.
• context-driven testing - testing driven by an understanding of the environment, culture, and intended use of software. For example, the testing approach for life-critical medical equipment software would be completely different than that for a low-cost computer game.
• user acceptance testing - determining if software is satisfactory to an end-user or customer.
• comparison testing - comparing software weaknesses and strengths to competing products.
• alpha testing - testing of an application when development is nearing completion; minor design changes may still be made as a result of such testing. Typically done by end-users or others, not by programmers or testers.
• beta testing - testing when development and testing are essentially completed and final bugs and problems need to be found before final release. Typically done by end-users or others, not by programmers or testers.
• mutation testing - a method for determining if a set of test data or test cases is useful, by deliberately introducing various code changes ('bugs') and retesting with the original test data/cases to determine if the 'bugs' are detected. Proper implementation requires large computational resources.