Common pitfalls to avoid when searching for a research paper writing service

Choosing the wrong research paper writing service can have severe consequences, including plagiarism, missed deadlines, and subpar quality. To avoid these pitfalls, it’s crucial to steer clear of the following:

1. Unrealistically low prices: While affordability is important, extremely low prices often indicate compromised quality or even potential scams. Reputable services charge fair rates for their expertise and resources.
2. Lack of transparency: A reliable service should be upfront about its policies, processes, and writers’ qualifications. Be wary of companies that are vague or evasive about these details.
3. Negative reviews and complaints: Before committing to a service, thoroughly research its reputation by reading customer reviews and checking for any unresolved complaints or legal issues.
4. Poor communication and customer support: A trustworthy service should have responsive and professional customer support to address your concerns and inquiries promptly.

Factors to consider when choosing a research paper writing service

When evaluating potential research paper writing services, consider the following factors:

1. Expertise and qualifications: Look for services that employ writers with advanced degrees and expertise in your specific field or subject matter.
2. Quality assurance processes: Reputable services should have rigorous quality control measures in place, such as plagiarism checks, multiple rounds of editing, and adherence to academic writing standards.
3. Confidentiality and privacy: Ensure that the service values your privacy and has robust security measures to protect your personal and financial information.
4. Turnaround time and deadlines: Consider the service’s ability to deliver high-quality work within your specified timeframe, especially for urgent or complex assignments.
5. Customer support: Evaluate the service’s responsiveness, professionalism, and willingness to address your concerns and inquiries.

How to determine the credibility of a research paper writing service

Assessing the credibility of a research paper writing service is crucial to ensure you receive high-quality work. Here are some strategies to help you determine a service’s credibility:

• Check for accreditation and certifications: Look for services that are accredited or certified by reputable organizations, as this can indicate adherence to industry standards and best practices.
• Review samples and portfolios: Reputable services should provide samples or portfolios of their work, allowing you to evaluate the quality and writing style before committing.
• Verify writer credentials: Inquire about the qualifications and experience of the writers assigned to your project. Reputable services should be transparent about their writers’ backgrounds and expertise.
• Seek recommendations: Ask for referrals from trusted sources, such as professors, academic advisors, or fellow students who have used the service successfully.

Tips for finding reliable customer reviews of research paper writing services

Customer reviews can provide invaluable insights into a service’s reliability and quality. However, it’s essential to approach these reviews with a critical eye. Here are some tips for finding reliable customer reviews:

• Check independent review platforms: Look for reviews on third-party platforms like TrustPilot, SiteJabber, or Reddit, where users can share their experiences without censorship or manipulation.
• Analyze review patterns: Pay attention to patterns in the reviews, such as consistent praise or criticism for specific aspects of the service.
• Verify the authenticity of reviews: Be wary of reviews that seem overly promotional or lack specificity, as they may be fabricated or biased.
• Consider the source: Reviews from verified customers or those with detailed experiences tend to be more reliable than anonymous or vague reviews.

Questions to ask when contacting research paper writing services

When contacting potential research paper writing services, it’s essential to ask the right questions to gather the information you need to make an informed decision. Here are some key questions to consider:

• What is the process for assigning writers to projects, and how are their qualifications determined?
• What quality assurance measures are in place to ensure originality, adherence to academic standards, and proper formatting?
• How do you handle revisions and ensure customer satisfaction?
• Can you provide examples of previous work or a portfolio to assess the quality of your services?
• What is your policy on confidentiality and data protection?
• How do you handle urgent or complex assignments with tight deadlines?
• What payment methods do you accept, and are there any additional fees or charges?
• Do you offer any guarantees or refund policies in case of dissatisfaction with the delivered work?

By asking these questions and carefully evaluating the responses, you can gain valuable insights into the service’s professionalism, expertise, and commitment to delivering high-quality research papers.

Finding a reliable research paper writing service requires diligence and careful evaluation. By following these tips and being an informed consumer, you can increase your chances of finding a trustworthy service that meets your academic needs and delivers exceptional results.

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Graphic card

A graphic card is an irreplaceable PC component responsible for putting pixels in a certain order on your screen. If your computer doesn’t have a graphic card, it wouldn’t even launch.

Graphic cards come with different stats. If you are planning to use your computer for working with graphics, editing videos, photos, etc., you will need a powerful GPU (Graphic Processor Unit – Graphic Card). But your task is to build a PC for coding and programming, you will do well with a mediocre GPU. And if you ever want to kick back and spin some free fruit games of chance, this machine should have enough power for that.

But if your task is to build a PC for crypto mining, you will need plenty of computing power from the GPU. In such cases, users build unique “farms” consisting of multiple GPUs.

Motherboard

The motherboard is your PC’s foundation, a piece you place all your other hardware on. So, it needs to match your other details. For example, if you are building a platform on the Ryzen processor, look for motherboards with a matching chipset. Or you want to have multiple drives on your computer. Each motherboard can support a certain amount of drives due to the limited number of connectors. The same rule is applied to RAM, graphic cards, fans, etc.

When it comes to power, the motherboard doesn’t produce any of it on its own. But it handles it and gets hot due to that. So if you want a high-power PC (or even overclock it), you need good cooling on your power circuits.

RAM

RAM is an essential part of your computer, just like the motherboard or the GPU/CPU. For comfortable PC usage, you need to have at least 8 Gb RAM nowadays. But if you are building a platform for hard tasks (editing, programming, etc.), your PC needs to have more. While a programming platform can do well with just 16 Gb, a PC for editing will need more (you will achieve a comfortable editing process with at least 32 GB RAM).

Processor

And the last PC part that is a part of its core is a central processor unit (CPU). This piece is involved during all the tasks completed by your machine and works together with many other PC elements.

All your other PC components will differ based on the CPU you chose. So you can go with a Ryzen or Intel processor. Intel is more of a casual choice that doesn’t require much additional work from a person who builds a PC. While Ryzen has some preferences like it works better with faster RAM (3200 GHz is an optimal point to start). You should also know that both these processors have different chipsets. So you will be unable to put an Intel processor into the Ryzen CPU socket, and vice versa.

If you don’t need any computing power from the GPU on your PC, you can avoid purchasing it by getting a processor with an integrated GPU. Both Ryzen and Intel have such options, and their GPU power should be enough to comfortably run any Casino Online Romania you would like.

HDD/SSD

Your platform must have the drive to store data (which is essential for a PC). Drives can have a different amount of space, directly influencing their price. Traditionally, a default space amount for a drive is 1TB, which should be enough for casual users. But if you know that your PC has to store lots of data, you should look for at least a couple of TB.

There are also a few drive types: HDD and SSD. HDD is a default hard drive that is not very fast when it comes to data loading. But if you want a real loading speed, you should look for an SDD. But remember that SDDs are much more expensive than HDDs.

PC Case

The PC case will be a home to all of the computer parts. Therefore, the case must have good cable management capabilities by creating many holes and compartments. You should also match your case to the form factor of your motherboard (ATX, miniATX, etc.). And remember that a PC case has to facilitate a good airflow from the fans you will place inside it.

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1. To program, you need to have a very high level of intelligence.
   This is the most popular myth. But in fact, you don’t have to be very smart to write programs. All you need is the desire, assiduity, and practice.
2. It is necessary to understand mathematics.
   To create applications and sites, school knowledge is enough. For more complicated things, university knowledge is required. But there is a great probability that someone else has already written this and you can use readymade material.
3. You need to be suitable for age.
   There are no restrictions on this trait. It can not be that a person is too young or too old for programming. The main thing is to have the ability to learn, diligence and quality training material.
4. Women can’t be programmers.
   This is not true. The first programmer was a woman. Other than the ambiguous attitudes of men and society, there is no reason that prevents the mastery of this profession.
5. Programmers lead asocial lives.
   In fact, they are no different from other people. And in many cases they need social skills for teamwork.
6. It is a boring profession, far from being creative.
   A person needs to apply imagination and fantasy to achieve the simplicity and reliability of the program. Therefore, the process can become fascinating. In addition, this business does not require talent, but only motivation and practice. The more one practices, the better one will get.
7. Once having studied the program of higher education institution or having passed courses it is possible to master a profession completely.
   Programming requires constant practice and development. At any time the situation on the market can change, and yesterday’s specialist will not be needed. Take new courses, study other languages and follow the trends.

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What is a REST API?
To make it easier for us to understand, let’s look at a small example. Suppose we have a full-fledged web application. Such an application or in other words such a website consists of two parts:

• The client side;
• The server side.

Everything the user sees and everything he will interact with is on the client side. Everything about the database, working with cookies and sessions, server configuration and so on is on the server side. Usually for these two things opposite technologies are used. For example, the client-side functionality is Vue JS and the server-side functionality is the Python language. Of course, instead of Vue JS and Python, you can substitute other technologies and languages that do similar things.

So, here’s the challenge. How to combine two completely different technologies so that they understand each other? This is where the REST API comes in.

Principle of treatment
For a long time programmers try to separate maximally two adjacent spheres:

• Front-end (the external part of the project, its design);
• Back-end (the server side of the project, its functionality).
• You can set things up so that the user can link directly to the server through the “http” protocol. This method is widely used, but it also has a better alternative – REST API.

It is what allows us to separate the two components. Thus, Back-end and Front-end developers will not conflict with each other in any way.

Basic Actions
When a user works with a database, he has to perform several basic actions:

• creating a record;
• reading records;
• updating records;
• deleting.

These actions are additionally called CRUD (Create, Read, Update, Delete).

The essence of the REST API is that you, on the client side, address a certain URL to your project, and it in turn performs the desired action and returns an object with data in JSON format.

Example usage
Suppose we have a site called “itproger.com”. We need to get all the articles from the database. We can send a direct “http” request and mix Front-end and Back-end together. Instead of this approach, we do the following:

• We create a new file on the server at “http://itproger.com/api/articles”;
• In the file we write the code in the server language: Python, Java, C#, PHP or any other;
• In the code we access the database and select all articles from the table “articles”;
• There we convert the result into JSON format and display it on the page.

Now we can address this URL from the client side and we will get all records from the database right away. It turns out that Front-end and Back-end are separated as much as possible. All that connects them is one URL.

By addressing the address, we get a JSON object, and it is easy to fetch such an object using any Front-end technology, be it plain JavaScript or frameworks like Vue JS, React JS, Angular and others.

Other files and URLs are implemented in a similar way. For example, you can create a page “http://itproger.com/api/articles/1” to get a specific record. Any number can go instead of one and it will be a unique identifier of the record we want to get.

We can send different HTTP requests. If we send a GET request, we will get all or one record (depending on the URL). If we send a POST HTTP request, we will put a new record. If PUT – record update and if DELETE – record removal.

The difference between Rest and Restful
In fact, the two concepts are one and the same. If you create a project and you only implement the URL for fetching data, it’s a REST application, or it’s also called a REST like application.

If you implement all the server functions through REST then it is a complete REST application, or in other words a RestFul application.

There will always be the word API in the name because it means referring one project to another. When you’re working with REST, you have the Front-end side addressing the Back-end side anyway.

The post What is a REST API? Developing a RESTFul project in Python Flask appeared first on Bubblemark.

Web development consists of two options for building software: front-end (HTML, CSS, JavaScript) and back-end (PHP, Python, Java, etc.). The front-end is responsible for the server operation and user interaction with the application interface. The back-end is in turn responsible for the work of the internal (hardware and software) part of the server. The front-end can function separately or together with the back-end. But in order to develop a fully functional application there must be a connection between the front-end and the back-end.

The goals of front-end and back-end developers are different. The former focus on the visual experience of the web application, the latter on the interaction between the two components.

There is a whole pool of requirements and skills for back-end developers. The main skill a backend pro simply must have is an understanding of how backend frameworks work. Because of the large variety of frameworks, many developers get lost and do not know which backend framework to use in their work.

Spring Framework (Java)
Java is often used for backend development as the main programming language, and is reputed among developers as “evergreen. Spring Framework is rightfully holds the palm of the palm among the most in-demand frameworks used to develop standalone and production web applications.

All software platforms based on Spring boot offers a lot of useful options, including: caching, manageability of settings and transactions, monitoring and security. And in the Spring boot software platform, in addition, there are no large configuration costs.

Django (Python)
The most famous software platform in Python, which is used today by web developers. Masters appreciate it for the security and high speed of development process due to the principle of DRY, focusing on code reuse.

Django framework is easy to learn and easy to use. It ranks as one of the most popular frameworks with full functionality. The platform integrates a lot of functionality for web developers, in particular support for “REST APIs”.

Express.js (JavaScript).
It is JavaScript is considered a very in-demand language for webmasters on the planet, guaranteeing full-stack creation from front-end to back-end. It is very quickly taught to beginners. Its popularity after the appearance of the Node JS framework among backend developers has only increased and strengthened.

In recent years, Node JS is considered the top among other frameworks. As early as 12 years ago, for Node webmasters developed Express. js, a minimalistic framework used to create highly flexible web applications. For the novice and experienced wizard, Express JS is a competent choice.

ASP.NET core
This framework is a new and improved modification of the NET version. It combines MVC and Web API solutions into one super-powerful high-performance module. It serves to create NET-based Internet applications. The platform is self-contained, the source code is open-source.

Laravel (PHP)
Hypertext Preprocessor (PHP) is the most popular programming language among backend programmers, specifically designed for web applications development. It has open source code that directly integrates into HTML markup.

Laravel framework is developed on MVC architecture – very simple and accessible tool for novice developers, which has intuitive interface, large library and excellent API support. Using Laravel framework will greatly simplify back-end development in new and secure web applications for highly specialized projects.

Ruby on Rails (Ruby)
Among developers it’s known as Rails, which is a server-side framework based on MVC architecture. The Ruby on Rails programming platform has an intuitive interface, so it’s suitable for novice developers. Of course, Rails has its own shortcomings, as any other software platform, but for the convenience and clarity of its recommended by many back-end professionals from all over the world.

Fiber Framework (Golang).
A framework designed specifically for Golang-developers. The platform is based on Fasthttp, a fast-acting CMS for Go. It makes it easy to develop applications with 0 memory reallocation and performance options. Fiber framework although simple (similar to Express.js), but very productive.

With minimal compactness and small memory footprints, the framework easily implements peripheral libraries with Martini. At the same time, the software platform gives maximum scalability with minimum overhead. The framework also supports routing, allows you to serve non-dynamic files, build REST APIs, support flexible software between platforms, and a template engine.

CakePHP (PHP)
The software platform is written in Hypertext Preprocessor (PHP), based on the aforementioned Ruby on rails back-end framework. The architecture construction is MVC. The platform contains features useful to the novice and advanced wizard, among which are: front-end controller, active account, data mapping and configuration agreement.

Flask (Python).
Like Django (position #2), the Flask framework is written in Python, readily used by webmasters for back-end development. It’s also called a miniframework because it doesn’t need any tools or libraries. It does not depend on external factors and does not contain form validation. The Flask software platform is clear and easy to learn. And thanks to the Python language, using the software platform is very easy.

Play (Scala)
The software platform Play is considered a fairly powerful framework for back-end development, made on the basis of architecture MVC. The back-end platform is written in Scala and Java. Among the useful features of the software platform are: fast code reloading, has a REST network architecture, displays software errors and focuses on increasing the profitability of the web developer.

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Paradoxically, there are more programming languages than ordinary languages, but never mind. We all know that English is the most popular language now. Then there is Spanish, Chinese and so on. The same situation is with programming. We will look at the top 10 most in-demand programming languages that you can choose to learn:

1. PHP.
   The programming language, which is used to create Web resources – sites, CMS. Take, for example, WordPress – a content management system (CMS), which is used ⅓ of all sites on the Internet. WordPress is written in PHP. Facebook, too, by the way… and there are many more such large-scale examples.

The level of demand is more than high. PHP is very easy to learn. We can say that this programming language can be the first to learn – it’s just perfect to get acquainted with this area. But… now let’s talk about the disadvantages. We are in the year 2022 and the fact that Facebook was written in PHP speaks about the authority of the language, but when it was. Things change and some things become obsolete. PHP is no exception. Take for example the TIOBE index. As of January 2022, PHP is already in 11th place, though in 2021 it was in top 8. This source is a fairly accurate description of the world’s demand situation.

The bottom line is that almost no one practiced to create something new in PHP. In this language, there are some problematic aspects, in particular the non-uniform syntax (PHP developer could stupidly not understand what wrote the other PHP developer). Since this language is easy to learn and it is not trendy or outdated, and earnings are not ahti, on average – $ 1000. If we talk about the Western markets, the figure is certainly more, but it is still not comparable to the programmers of another class.

2. JavaScript / JS.
   It’s trendy, it’s cool, it’s a trend. Over the past 5 years javaScript has the dynamics of popularity, as no other language. You can write in it – web sites, mobile applications, the server side and a bunch of other things. After mastering JS you can become a Frontend developer, Backend developer, Fullstack specialist – these are the most popular specialties in IT today. Read more about what is frontend, fullstack and other obscure words in our article about – JS learning plan.

For the beginner, the JavaScript language will be as easy as PHP. The earnings here are on average $3000. Knowing the tendency of aging of all languages, we can say with confidence that JS will still be in trend for at least 5 years, but beyond that we won’t make vangos. As such JS has no disadvantages. It is not for nothing that our IT-school Lemon School in Kiev launched courses on JS Script. After them you can easily become a programmer, get a job at any IT company and earn good money even at the start.

3. Java.
   You should not confuse this language with JavaScript. They have no common roots, and this name came out of the deal Netscape and Sun Java. Basically it’s just a marketing thing, not that Java was the ancestor of JS.

Java is a general purpose language. What is a general purpose programming language? To put it simply, with its help you can write software for anything – for example a service system in banks. If we talk about web resources, the business network Linkedin or the search engine Yahoo are good examples.

Is Java good for beginners? No… It’s not a good place to start but if we’re talking about demand for the language, it’s still firmly in the top 3.

4. Python

Python is a high-level programming language. Even other programming languages can be written with this language – that’s the power! Some people think Python is easy to learn, others do not. Schools are already full of it teach children. Yes, if you learn the basics since childhood, then the study of this language will seem easy, but if you just yesterday decided to do programming and choose Python as the first language, then … get ready for difficulties.

Python has long been in the top 3 internationally in terms of popularity. It’s a very, very popular programming language. Google developers code in Python. AI development is done in Python. Python programmers are the ones that get a staggering $7,000 on average. The outlook here is staggering and in the next 10 years this language won’t become obsolete for sure!

5. C++
   If you like computer games, you know that most likely it was developed in C++. It is the brainchild of the now obsolete C language so if you learned it then C++ will be very easy to learn. Learning it from 0 will be difficult because the syntax here is, oooh…head bursting.

In addition to games, this language is capable of creating operating systems and various application programs. The demand is huge.

6. C # or SI Sharp.
   Just like the previous language, SI Sharp takes its roots from the C language. It is also universal. It is used to develop games and all sorts of business software. Microsoft works mostly with it, so if you want to work for this company, learn C #.
7. Visual Basic
   This is the successor of the fundamental language Basic. Specifically Visual Basic is geared towards programming various Windows applications. Let’s not dwell here for long, because the demand for this language is slowly dropping and its evolution stops.

Now of course Visual Basic is in the top 10, but it is not a language which should be studied at the very beginning of the way and even in its continuation.

8. SQL
   This programming language is still considered the best when it comes to interacting with databases. How does this language work? Roughly speaking, there is an array of data of all students in the school and we want to find this database of all Pupkins. We make a query, and voila, we see the result. SQL is used to make it work correctly. As you know there are many databases and they must be constantly updated, upgraded, so there is enough work.

SQL language is not difficult to master and may be suitable for a beginner, but … this language is specific and demand for him specific – here the demand is much less than offers.

9. Golang or GO.
   This language appeared in 2009 and was presented by Google, of course. They’ve managed to promote it to a very authoritative level. Someone thinks Go is better than Python. Somewhere it is faster and easier than Java. In general, the prospects for this language are huge. Maybe in 5 years it will be at the top 1, so you can learn it for the future, but for beginners it will be difficult.
10. Assembler or Assembler language.
    This is a low level language – that doesn’t mean it’s clumsy or you can’t write anything in it. It simply means that its syntax is as close as possible to the computer’s understanding. This means that here you have to learn a lot, become a machine yourself.

It seems that why do we need such a complex language at all? Yes, it is needed, and how! The Assembler code goes directly to the CPU and the memory, and that means the speed of any operation is very high. The language is definitely a difficult one not just for the beginner, but even for the experienced programmer. There are areas where Assembler is worth its weight in gold, for example when you want to hack someone’s server.

Which programming language should a beginner learn?
All of the above languages are worthy to learn in 2022 and beyond, within up to 5 years.

Programming languages such as GO, Assembler, SQL, Visual Basic need to understand what to learn. You must have a goal to get a job in a company. It’s not a good idea to just start learning these languages.

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There is a concept Fullstack developer – a specialist who knows how to work with both the frontend and the backend, the part that is not visible to the user – often the admin panel. If we’re talking about JS backend development, then the so-called Node comes into play – a platform that allows you to convert Java Script into server-side code outside the browser.

A full-stack developer is a specialist who knows html, css, JS + popular frameworks. To put it simply, frameworks are JS libraries that already have pre-code. These are templates that you have to know how to work in. Among the most popular are:

• React;
• Angular;
• Vue;
• JQuery;
• Backbone;
• Node – this is also a framework, which has its own frameworks, the most popular of which is Express. You can read more here.

The plan for learning JavaScript begins with an awareness of the scope of work, so to speak. To effectively learn a programming language like JS you should have a good knowledge of layout + a good knowledge of English.

Having made friends with the typesetting and having confident skills in English (level Intermediate at least) you can learn the basis of JavaScript.

The next stage of development will be the study of the most popular frameworks for the frontend, namely React and Vue. Studying programming on the server side, that is Node will allow you to work as a Fullstack developer, which is more in demand in Western markets. As you gain more knowledge and expand the list of frameworks, in about 5 years you will grow to Senior Full Stack JS Developer with an average salary of $5000 in the domestic market.

Decide what you want to be – a layout maker, JS developer, Frontend developer, Backend developer or Fullstack specialist. All of these areas can be studied separately from each other, but the efficiency will be lost, so the sequence is better to choose – layout, JS, React, Vue, Node, and all the rest.

Starting to master JS
If we talk more specifically about mastering JavaScript, the training plan can be structured as follows:

• Basics of HTML, CSS and jQuery – interaction of JS with HTML.
• Basics of JS: history of JS, code structure, variables, data types, operators, functions, recursion.
• Data structure: numbers, strings, objects, arrays, stacks, queues.
• JSON is the most common data exchange format.
• Object-oriented programming in JS: introduction, getters and setters, classes, modules.
• Working with events.
• Frontend: CoffeeScript, TypeScript and other syntaxes, AJAX and COMET, MVC, React and Vue frames, DOM, code optimization.
• Backend: SSR, CSR, Node, Express, asynchrony in JS, databases, DBMS.
• GIT – version control tool.
• Frontend and backend code testing tools: Jasmine, Jest, Mocha, Protractor.

This is a brief outline which can still be supplemented and supplemented. For a better understanding of the structure and scope of learning JavaScript, we suggest using proven books and video reviews.

The post JavaScript study plan appeared first on Bubblemark.

Where does the line between regular and big data cross?
In Russian, the term “big data” is often used in conjunction with the English term “big data. But where is the line that divides the data into “big data” and “normal data”? It is generally accepted that the volume of big data begins with a terabyte, as this amount of data is already difficult to store and process in relational systems. There are other criteria that explain why new methods were needed to handle big data.

Variety. Big data most often consists of unstructured information that can come from multiple sources in a variety of data formats (video and audio files, text, images, etc.). Big data technologies allow processing heterogeneous data simultaneously.

Speed of accumulation. Data is being generated faster and faster. For example, an online store needs to constantly collect information on the number of customers and their purchases. To store such data non-relational databases are better suited, since they can easily be scaled horizontally by adding new servers (most relational databases are scaled vertically by increasing the RAM).

Processing speed. Big data, despite its impressive volume, must be very quickly processed, often – in real time. For example, recommendation systems in online stores instantly analyze customer behavior and produce results on what other products he may like. Such a high speed of processing is achieved by distributed computing.

Thus, for programmers, working with big data implies solving a complex, contradictory problem: how to ensure the collection and storage of constantly growing volumes of heterogeneous data, while achieving very high processing speed.

What you need to know to work with big data
Handling big data is not an easy task for programmers, and new methods and tools are constantly emerging to solve it. However, there is a basic stack of technologies that are most often found in job postings.

• Apache Hadoop is a platform for parallel processing and distributed data storage. It represents a large set of tools, the most important of which are Hadoop Distributed File System, or HDFS (data storage), and MapReduce (data processing).
• Apache Spark is a framework for parallel data processing. It can be used to process streaming data in real time. It supports in-memory processing to improve performance for big data applications.
• Apache Kafka – a platform for streaming data processing. The advantages of the technology are high speed of data processing and its safety (all messages are replicated).
• Apache Cassandra is a distributed non-relational database management system. It consists of multiple storage nodes and is easily scalable. Cassandra is fault tolerant – all data is automatically replicated between cluster nodes.

What programming paradigms are used
When working with big data, you will refer to different programming paradigms: imperative, declarative, and parallel. For example, SQL programming for databases uses the declarative approach, where you specify the task and the desired result without specifying intermediate steps. To cope with the fast processing of large data sets, you need to apply multi-threaded and parallel computing. One solution is the MapReduce paradigm. It is a computational model for parallel processing of distributed data. The algorithm allows to divide tasks between cluster machines, so that data processing takes place simultaneously on all involved computers.

What you can do in big data
Work with big data can be divided into two areas. The first is creating and maintaining the infrastructure for collecting, storing, and processing data, and the second is analyzing and extracting useful information. Each of these processes requires specialists with knowledge of programming. The first direction involves familiar IT specialties – engineers, architects, administrators, but possessing technologies for working with big data. Data analysis is a narrower specialization, often requiring a specific education or experience.

Big data engineer
Develops technical solutions related to storing and processing big data. He may also be responsible for the delivery and distribution of data from different sources (website, social networks, sensors, etc.) to the storage system.

Database architect (Data architect).
Designs databases based on the needs of the organization that collects the information. The architect chooses the technology to store and process the data.

Database manager
Monitors the performance of the databases and troubleshoots database performance as needed. The specialist ensures that the servers are up and running at all times so that the data always remains intact.

Big data analyst.
Conducts descriptive data analysis, makes data visualization. An analyst finds meaningful information in scattered data sets.

Data scientist.
Looks for hidden patterns, trends in datasets, based on the specific task. Excellent knowledge of mathematics and statistics is mandatory for this specialty – you need to apply machine learning algorithms and build predictive models.

The list of career opportunities in big data is constantly expanding – as technology advances, new, narrower areas appear:

Data governance manager
Responsible for the data collection process. He decides what data to collect and how to store it. He is also in charge of data verification.

Data security administrator
Creates a strategy to protect the data from unauthorized access. The data security administrator can monitor the security of databases and implement security features.

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