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Sunday, November 17, 2019

Which SQL Database Management System Should You Choose?

Database , software
Which SQL Database Management System Should You Choose?

    It’s easy to keep track of data using a basic spreadsheet, right? Up to a certain point, it is. However, the situations are very different when you’re working with information about ten items, and, say, a few thousand of them. That’s why no matter what kind of websites you create, sooner or later you will start looking into smarter data storage solutions. This is where database management systems come in.
It’s rather common to separate all database management systems into two groups, based on whether you can use SQL on them. In this tutorial, we will introduce you to the ones that support it. If by any case you need a reminder on SQL, be sure to take this interactive SQL course.

    Getting the terminology down

    Before we start exploring the world of database management systems, we should make sure we understand fully what is it we’re dealing with. First of all, we have data. Developers use this term to define all the information that is kept in the memory of the computer. For example, an e-commerce website would normally be storing data that relates to the user, such as their name, address, orders, and possibly banking information.
    By entering their details on the webpage, the user sends their data to its server, which then stores it in a database. Without one, it would be hard to actually access and use the data: a database is what brings in the structure. It is a system in which you can store, update, manipulate, and access your data. To put it simply, each database consists of data and a method to access it conveniently.
    Now, what is a database management system (DBMS for short)? It is a special kind of software that you use to create and manipulate your databases. You could say a database management system is an intermediary between the database and the user or the application that uses its data.
    While there are various models, most agree relational database management systems are the most popular. The data they contain must be related in nature. The standard way of working with such databases is using SQL – the Structured Query Language. When asked to name a few relational database management system examples, most mention the most well-known ones: MySQL, Oracle, Microsoft SQL Server, and PostgreSQL. All of them were written in either C or C++.

    Database management system: MySQLMySQL: the industry titan

    When thinking of SQL database management systems, most users instinctively think of MySQL. It’s only natural: not only the name itself contains ‘SQL’, but it’s also the most popular system worldwide. David Axmark and Michael “Monty” Widenius started working on it in 1994 and made the first version available to the public in 1995. Since then, MySQL has become an industry standard. The list of its current clients contains such famous names as NASA, Tesla, GitHub, Facebook, and a whole bunch of other giants. What is more, MySQL is simple and completely free to download and use. Developers praise its well-written and extensive documentation as well.
    Since 2010, MySQL belongs to the Oracle Corporation. The acquisition caused a huge uproar, as the public feared Oracle will put MySQL to end. Michael “Monty” Widenius even started to work on a replacement database management system, creating a new branch of the MySQL of the time and calling it MariaDB. However, despite the worries, Oracle kept the free and open-source MySQL. It stayed on the top easily due to unique features that were never introduced in MariaDB. A large company owning and supporting the system made it even more reliable too.
    The most current version is MySQL 8.0, published in 2018. The team releases small updates every two or three months. The newest version sports updated security, account, resource and table encryption management, as well as a transactional data dictionary. Most companies value MySQL for being very scalable and robust enough to handle huge amounts of data. Additionally, it works well across many different platforms, including but not limited to Microsoft Windows, macOS, and Linux.

    Database management system: OracleOracle: one step forward

    Before Oracle Corporation acquired MySQL, it also had its own relational database management system, called Oracle Database, or simply Oracle. Initially released in 1979, it is now at version 19c, presented in 2019. The letter C in the name stands for the cloud.
    When comparing MySQL vs. Oracle, you will notice the latter has a lot more to offer. It supports XML format, has more data types, more storage features, enhanced security and audit vault. And that’s not all! In 2018, Larry Ellison presented the version 18c as the first completely autonomous database management system. Armed with powerful machine learning capabilities, the new Oracle can perform a lot of tasks without human intervention, which lowers the risk of errors. The company presents the newest version as self-driving, self-securing, and self-repairing. It’s hard to disagree that it’s a huge step toward maximum security and ease of use.
    However, the impressive features come at a price. The biggest difference between MySQL vs. Oracle is that while MySQL is free and open-source, Oracle is a commercial product. There are a few payment options available, depending on your exact needs. There is also a free version called Oracle Database Express Edition, but it has certain limitations: you cannot have more than twelve gigabytes of user data, two gigabytes of RAM, and 3 three pluggable databases.

    Microsoft SQL Server: flexibility for a priceDatabase management system: SQL Server

    Another popular relational database management system is called Microsoft SQL Server. The team initially released it in 1989 and introduced some major updates with version 7.0 in 1998. By now, there are two latest versions: Azure SQL database 12.0 (2014) and SQL Server 2017. Confused? Let us explain.
    To accommodate users with various needs and preferences, SQL Server offers a few different editions. Apart from the mainstream editions (Standard, Enterprise, Web, Express, and a few others), there are specialized ones. Azure might be one of the most popular. What separates it from simpler types is that it is fully cloud-based. The Developer edition is basically the same as Enterprise – however, it cannot be used as a production server. The list of editions goes on and on – what’s important to note is that Developer and Express are the only two versions that can be used free of charge. To take full advantage of Microsoft SQL Server, you will need to pay – and the costs aren’t low, either.
    SQL Server is simple to use, plus, it detects and downloads any updates available automatically. After the initial installation, you can add extra components as well. You can use this database management system in one of the multiple languages, on multiple platforms. Additionally, SQL Server has comprehensive documentation and handy community features, such as forums and even a tech support blog.

    Database management system: PostgreSQLPostgreSQL: the late bloomer

    The PostgreSQL database management system might seem like the youngest of them all: the team at the University of California at Berkeley only formally published it in 1997. However, they did take the first steps in its development as early as 1982.
    At first, there was the Ingres project. However, soon after it was done, the team noticed a few clear issues in using relational database management systems. Therefore, three years later, Michael Stonebraker, the leader of the team, started developing what was then known as Postgres (Post Ingres). His project underwent many updates and improvements: in 1994, it finally started to support SQL, and hence was renamed as PostgreSQL in 1996. In January next year, it was finally released to the public. As of now, the latest version is PostgreSQL 12.0, which went public in the fall of 2019.
    Compared to other DBMSs, PostgreSQL has the most features, plus, it’s reliable and pretty quick. While it is the default choice for databases on the macOS Server, you can use it on all major operating systems. PostgreSQL is also pretty unique in terms of extensibility: you are free to create your own functions and data types. It supports a ton of programming languages, including C, C++, Java, JavaScript, Python, and others.

    Choosing the right database management system for you

    As you can see, each relational database management system has its own pros and cons. Choosing the right one depends on your priorities: do you need it to be free, or would you rather pay and get more features? Do you prefer cloud solutions, or do you want to try an autonomous system? The choice is yours. All you need to know is SQL – and this BitDegree’s online course is a great way to start!
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    What is Machine Learning: Understanding Machine Learning Basics

    ai , Artificial Intelligence
    What is Machine Learning: Understanding Machine Learning Basics

    What was considered to be fiction not so long ago, now is a reality. The technology that only could be seen in movies and read in books is currently a reality we live in. While some of the greatest minds only could’ve dreamed in the past about what is machine learning and what it could bring to humanity, the phenomenon is very much alive.
    Machine learning, or shortened as ML, is a computer science term standing for machine intelligence. It is a technology that can learn and mimic cognitive functions such as neurons. It can solve problems on its own and not just answer questions like a virtual assistant.
    With the rise of machines’ capability to improve people’s lives, we can already notice machine learning software in some parts like face recognition, self-driving cars, social networking, and auto-pilots in planes. As the Tesler’s Theorem says “ML is whatever hasn’t been done yet”. Machine intelligence capabilities that are classified as ML can successfully understand human speech, military simulations, competing at the highest level of computer games, and more. Now that we have tasted a bit of what is machine learning, let’s dive deeper, shall we?

      A deeper insight into Machine Learning TechnologyWhat is machine learning - A robot

      From the virtual assistants like Siri and Alexa, machine learning software is rapidly integrating into our daily lives. Although some of these examples could not be considered as the “true” machine intelligence that can make decisions on its own, the spin-off projects’ impact continues to advance in capability and prevalence.
      To have a better understanding of what is ML, it is needed to go back a little over its development.

      A short history of ML

      The very first ideas of artificial beings were mentioned in antiques and have been in the fiction scene for a very long time. Stories like Frankenstein were the results of it. The field of artificial intelligence studies was born in 1956, at Dartmouth College in the United States. A group of scientists from universities like MIT and CMU became the founders of ML technology research. The programs they created have been considered as the first machine learning basics. They were the ones to create a computer system that could learn checkers’ strategies, solve problems in algebra, and prove logical theorems. They believed that in 20 years or so the machines will be capable to do anything that a man can do.
      Although they were very optimistic about the progress of their creation, they failed to realize what is machine learning development going to challenge them next. Because of the hard financial times, both the United States and British governments decided to stop funding the projects on the exploratory research of ML. The period, in which it was very hard to find enough funds to continue the research was called “ML winter”.
      Nonetheless, the “ML winter” did not last too long. By 1985, the research was alive again and by that time, the market of machine learning reached over a billion dollars. Through stumbles and falls, by the end of 20th, and by the beginning of the 21st century, machine intelligence development has been used in medical diagnosis, logistics, data mining, etc. Machine learning software started gaining success because of increasing computational power. As Moore’s law states, the speed, and capability of computers can be expected to double every two years. That means that the evolution of computer science progresses unquestionably fast and it will continue to increase the quality of people’s work accordingly.

      The basic concept of ML

      Machine learning as a process and as a product is very hard to understand if it’s not in your expertise. To make it as simple as possible, ML technology is a software, that takes input information and turns it into other information, that is output.
      The biggest difference between machine intelligence and other kinds of software programs is that to machine intelligence, the creator, that is a programmer, did not have to give instructions on every feature that it is doing. Through examples and practices, it learns the needed information by itself.

      What is machine learning - BB-8 droidWhy is machine learning important?

      Understanding what is machine learning and its’ importance has to begin with the very simple statement – it was created to reduce human effort and help in the areas where it is dangerous for a person to step in. Although there are many different ways of using machines’ intelligence, it works as a speed-up to some sort of a process and gives the user an accurate result. The idea of ML software is to create an error-free world. Let’s break down some of it’s main and most important features:
      • Machine-learning learns through repetitive learning and discovery through data. Instead of handling the information by yourself, the ML makes robotic automation that can perform high-volume, computerized tasks without experiencing any form of tiredness and tardiness. It is worth to mention that this process still needs a human inquiry since the ML system needs to have the right questions.
      • It will get the most out of the data. As mentioned above, with the right set up from an expert, ML technology can work without fatigue for a very long time. What is machine learning amazing for creating a competitive advantage against business competitors. Data collecting has grown significantly over the last years, and the importance of it has become huge. It’s no surprise that there have been many scandals and data protection regulations over this time. Everyone knows, that the data can play a big role in many work areas, and ML can make it easier to sort through it.
      • Machine learning software plays a huge role in safety. By giving the ML access to data storage, it can work as a fraud detection system a lot faster with the help of deep learning.
      • Using machine learning basics to improve current products. If you are familiar with digital marketing then you know that the internet of things is coming whether we like it or not. Web 3.0, the alternative name to the internet of things (IoT). The definition of IoT means that it extends the purpose of casual and everyday devices that we use. In the consumer market, the internet of things is the synonym of the things that make a “smart home”. It covers devices, appliances, security cameras, thermostats, etc.
      • Deep neural networks help us achieve extreme precision. What is machine learning also astonishing about is that through deep learning, image classification, and object recognition machine intelligence can spot cancer on MRIs just as precise as an expert radiologist.
      As we can see machine learning impact is undeniable in the current stage of computer science and technologies. Don’t get it wrong, it’s not all advantages of ML technology, there are much more than that. But now that we mentioned deep learning and neural networks, what exactly are they?

      Neural Networks

      Theoretically, the neural network is a circuit or a network of neurons. In this case, it is an artificial neural network that helps machine learning to solve a problem. A neural network is a set of certain algorithms that have been modelled to be similar to the human brain. These algorithms are designed to recognize patterns of information. The information is recognized through a machine perception, labelling or clustering raw input. Just like it would be real-life images, sounds or texts, artificial neural networks understand it through n-dimensional tensors(arrays) that hold the values and numbers. It is one of the most important things about what is machine learning all about.
      Neural networks help to cluster and classify data. The whole process helps to group unlabeled data according to similarities among the example inputs, and neural networks classify data when have a labelled dataset to train on. This type of learning is called supervised. On the other hand, there is unsupervised learning, that helps to find previously unknown patterns in data set without pre-existing labels.

      Deep learning

      Another essential part of machine intelligence is deep learning. This process is a machine learning technique that helps them to learn from examples, just like humans do. If you have seen self-driving cars then you probably had your first contact with machine learning.
      In deep learning, machine intelligence can learn to perform tasks from images, texts, sounds, like a human from books, videos or lectures. Human beings always have a chance to make a mistake, while computers with deep learning models can achieve picture-perfect accuracy and exceed human performance. Deep learning models are part of neural networks since they use the labelled data and datasets that have been collected. It is a huge part of what is machine learning.

      Real-life example: Sofia the RobotWhat is machine learning - Real life example Sofia

      Although the name itself suggests that it is a robot, do not get tricked. The robot is what is on the outside – the skeleton of the whole project. What is most impressive about Sofia – it is her mind.
      Sofia is a social humanoid robot that has been developed by a company Hanson Robotics. She was activated on February 14th in 2016.
      Combined with many algorithms, Sofia the Robot can see, follow movements, sustain eye contact with its companion, and recognize people. It can even understand facial, expressions of people, and understand companions’ emotions. This whole process is done through the cameras that are in her eyes. In 2018 she was upgraded and since then, Sofia the Robot can walk.
      The creator of Sofia, David Hanson, said that the goal was to create a machine learning-driven robot that could serve in healthcare, customer service, therapy or education. Sofia’s machine intelligence is constantly being trained in the lab, so she is developing new skills and making fewer errors as we speak.
      Moreover, what is machine learning of Sofia so groundbreaking is that it combines cutting-edge neural networks, expert systems, machine perception, conversational natural language processing, adaptive motor control, and cognitive architecture.
      Sofia the robot can function in separate ways – the first is a completely ML autonomous operation, the second is ML operation mixed with human-generated words. It is a fully functioning hybrid human-ML intelligence.

      Overview

      It is hard to deny that machine learning is currently the biggest cutting-edge technology out there. It is important to acknowledge that if we want to grow and continue making human lives better it is one of the best ways to do so. If you want to understand better on what is machine learning and learn more about it, head over to our BitDegree course and give it a try. If you’re interested in the absolute machine learning basics, then head over to this course.
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      What is Deep Learning: Neural Network Software Basics

      datascience , software
      What is Deep Learning: Neural Network Software Basics


      The evolution of technology has taken humanity to heights like never before. Work areas of medicine, safety, learning, and providing other kinds of help has reached a peak. But it does not stop there. Artificial intelligence is the next big thing in the world of technology and computer science but to understand it, it’s important to know what it consists of. It is essential to know what is deep learning and what artificial neural network means.
      The AI technology field is extremely advanced and interesting. These two tools that are being used in artificial intelligence are very powerful in terms of solving complex problems and to develop even higher standards in science.
      It is safe to say that this kind of mechanism is a transition to the next level of technology. The companies of today have already recognized its importance and started using it in most of their cases. Let’s take Google for example. Google uses search engine AI to learn from its’ users. If you are looking for something in its search bar, for example, a “laptop computer”, and after getting the results you press on it, you just taught Googles’ AI that a “laptop computer” is what you pressed on. Wonder how does it work? Let’s dive deeper and find out.

      standing Deep Learning AIwhat is deep learning - example of a robot

      What is Deep Learning technology so special about, that it is a technique for computers (AI) to learn just like humans do – by trial and error. If you are wondering if you have ever seen it before, you probably have. It is the technology behind such applications as voice control over devices like phones, tablets or television. Not so long ago we have been introduced to the driverless cars, which is also a product of deep learning. With the help of DL, artificial intelligence recognizes stop signs, pedestrians, and other obstacles in the road that might cause a disaster.
      To perform such actions, a computer that is using deep learning techniques requests a large amount of training data (this is the work of neural networks, we will get to that a bit later). Such technological achievements like driverless cars need thousands of video footage and images to recognize every single situation for it to be safe. The recent improvements in Deep Learning have been taken to the level where it outperforms humans in a certain amount of tasks.

      How Does It Work?

      As already mentioned slightly above, what is deep learning using to perform such tasks are neural networks. Most of the times deep learning AI is referred to as a deep neural network. The word deep in this term stands for the layers that are hidden in the neural network.
      Deep learning models are trained by getting a sufficient amount of data and neural network data architectures that learn features directly from the data without manual labour. Neural networks are systems that are connected just like our biological neural networks. These kinds of systems are created in a way to adapt to situational needs. Once the neural nets identify the results for a certain object, the next time the NN systems can identify whether it is the same object or not. The neural networks do not recognize objects the same way we do, it recognizes objects through their own unique set of features.

      Artificial Neural Networks

      One of the most common and popular types of what is deep learning using is known as conventional neural networks or CNN for short. It combines the learned features with input data, and uses 2D convolutional layers, making this architecture well suited to process 2D data. For example, it can be images or coordinate plane sheets.
      Conventional neural networks work in a way that there is no longer a need for manual feature extraction. It extracts features directly from images. Artificial neural networks have an automated feature extraction that makes deep learning models picture-perfect accurate for computer vision tasks such as object classification.
      CNN’s learn to detect different features using numbers of hidden layers. Every number of the hidden layer increases the complexity of the learned image features. CNN’s learn different features from every layer.

      The Common Exampleswhat is deep learning - a robot learning to play piano

      According to sources, there are three most used ways to use deep learning to perform object classification:
      • Transfer learning. The learning approach is mostly used in deep learning applications. It is done by having an existing network and adding new data to previously unknown classes. This way it is a lot better to save some time because instead of you reduce the amount of image processing. It allows categorizing only certain objects rather than going through all different objects until it finds the correct one.
      • Training from nothing. This is mostly used for new applications that are going to have a large count of output categories. It begins by gathering a large number of labelled data sets and designing a network architecture that will learn the features. While transfer learning can take up to hours or minutes, this method takes a bit longer – from days to weeks to train.
      • Feature extraction. Not as popular as the mentioned methods before, but still used commonly. This is a method that is used for a more specialized approach to deep learning. It uses the network as a feature extractor. Since the layers in conventional neural networks are tasked with learning certain features from images, it is also possible to withdraw these features and make it as an input to a machine learning model.

      What Are Other Types of Neural Networks?

      While the conventional neural network could be considered as the standard neural net that has been expanded across space using shared weights, there are also some different types.
      A recurrent neural network, rather than the conventional one, is extended across time by having edges that feed into the next time step instead of the next layer in the same time step. This artificial neural network is used to recognize sequences, for example, a speech signal or a text.
      Also, there is a recursive neural network. This NN system has no time aspect to the input sequence, but the input has to be processed hierarchically.

      Neural Networks in Action

      It might get tricky when trying to understand what are the real benefits of the neural networks in real-life situations. Artificial neural networks are very popular among stock market experts. With the help of NN systems, it is possible to apply “algorithmic trading”, that can be applied to the likes of financial markets, stocks, interest rates, and various currencies. Neural network algorithms can find undervalued stocks, improve existing stock models, and use deep learning to find ways how to optimize the algorithm as the market changes.
      Since neural networks are very flexible, they can be applied in various complex pattern recognitions and predict problems. As an alternative to the example above, the NN system can be used to forecast business, detect cancer from images, and recognize faces on social media images.

      Deep Learning in Actionwhat is deep learning - data connections

      Not only neural networks have real-life examples. Deep Learning can also be described as some of the following creations:
      • Virtual assistants.
      • Chatbots or service bots.
      • Personalized shopping and entertainment.
      • Imagine colourization (uses algorithms to recreate true colours on images that are black-and-white)

      What Are The Key Differences Between DL and NN?

      With all this information it is clear that Deep Learning and Neural Networks are strongly connected and probably wouldn’t work well when separated. To be able to understand what is deep learning and what is neural networks it is essential to know the main takeaway.
      Neural networks transmit data in the form of input values and output values. It is used to transfer data by using connections. Whereas Deep Learning is related to the transformation and extraction of feature which attempts to establish a relationship between stimulus and associated neural responses present in the brain. In other words, Neural Networks are used for natural resource management, process control, vehicle control, decision making, while Deep Learning is used for automatic speech recognition, image recognition, etc.

      Overview

      To sum up, Deep Learning and Neural Network complete each other and will develop into even bigger technological wonder than it is today. Head over to our courses page and take a course on Machine Learning applications. Artificial intelligence is the next step in our age, and the more experience it gets, the more benefits it will provide to society.
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      What is IOT: Understanding What is the Internet of Things

      datascience , IoT
      What is IOT: Understanding What is the Internet of Things

      Ever since the beginning of the internet visionary scientists imagined adding some sort of intelligence to basic objects to make every person’s life a little bit easier. The idea began in the early 1980s but it was slow to realize due to lack of technological advances.
      To gain an understanding of what is IoT we must go back to the past century. In 1999 at MIT, the internet of things term was first mentioned as an idea to bring attention to Procter & Gamble’s (P&G) senior management. In addition to that, a book called “When Things Start to Think” appeared in the same years and drawn the way there the process of IoT should be heading.
      IoT applications have evolved from things like wireless technologies, microservices, microelectromechanical systems and, of course, the internet itself. The convergence of these technologies has helped to break down the operational and information technologies, that enabled devices to receive data and make insights accordingly.

        What is IoT?Amazong Alexa as an example of what is IoT

        From aeroplanes to self-driving cars and many other smaller devices, the internet of things is a reference to numbers of devices around the world that are connected to the internet. Collecting and sharing data, it enables the devices to work on its’ own and adds a “digital intelligence” to them. The electronic devices can communicate in real-time without any person involved and send generated messages.
        To paint a better view of what is IoT, it helps to imagine that it is an ecosystem of devices, machines, appliances or any other things that can be connected to the internet through the wired or wireless network. The established network between devices allows data integration and exchange between the computer system and physical devices. This new chapter of technological advances is meant to be the step towards even better efficiency and productivity of daily people’s life.
        Using the latest cutting-edge technologies like machine learning, artificial intelligence, and machine-to-machine communication, the internet of things extends the capabilities of typical physical devices like smartphones, tablets, desktop computers, and laptops. By expanding the connectivity of the devices that mostly are non-connected to the network, the IoT system bridges everyday devices like washing machines, heating systems, door or garage lock so you can monitor, control and provide other actions on a mobile phone or a tablet.

        How Does IoT Work?

        Just like any other system or mechanism works, the internet of things also has the main steps that are required for it to work. Trying to understand what is IoT and how it works may get confusing, so it is important to take it piece by piece. An IoT system is made of four main components that work together and create the desired output of the scheme. The components are:

        Sensors

        One of the main parts of the IoT engine, since it collects and specifies the data from the surroundings. The data that it collects can be considered as a very simple one – it may be a particular timing, geographical location, supply stock, or even such complex thing as the health state of the patient in a hospital. To notice even the smallest changes in surrounding data, the device can have a bundle of sensors that can be capable of more than data collection. The best example of that could be a mobile phone, that provides a lot of other functions while perfectly managing data.

        Smart thermostat as an example of what is IoTConnectivity

        After collecting the surrounding data IoT devices need to process it somewhere and this is when connectivity plays the main role. Collected data is sent to the IoT platform with the help of a medium. Wi-Fi, Ethernet, Bluetooth, Cellular Network and other network connections are crucial in transferring data to the cloud. Connectivity is what mostly defines what is IoT. Choosing the best connectivity method will decide the tradeoff of medium and power consumption, range of connectivity and bandwidth.

        Data Processing

        As mentioned slightly above, connectivity enables the transfer of data into a cloud where it is stored, analyzed, and processed. The data is processed using a “Big Data Analytics Engine” that helps the system to make better decisions according to the data. Data processing based decisions allow IoT applications to make a wide range of actions. For starters, it can be as simple as turning on the lights when the homeowner comes back at particular hours, or, with the help of surveillance systems, identifies danger or intruders.

        User Interface (UI)

        The final step of the internet of things process is to notify the main user. It can be done through numerous actions, as an alert, reminder, text message, notification or email. These actions can depend on the functionality of the system itself. An advanced IoT system can arguably control the whole home environment and even more. The user interface allows the user to perform a wide variety of actions, for example, adjusting lighting, temperature, air conditioning in the environment, etc.
        One of the best ways to describe what is IoT or how it works is through daily tasks that will be changed after implementing the system.
        • The refrigerator will notify the user when it is out-of-stock of particular groceries.
        • Kitchen appliances will start working in hours when you wake up or get ready for making dinner.
        • Lights turn off or on when it’s time to sleep or wake up.
        • The vehicle sends a notification on gas shortage or delays in the road.
        As said before, the goal is to make the day easier, more efficient, productive, and overall better for the consumer. The devices will overtake most of the chores without human intervention.

        IoT in Labor MarketApple computer saying "Do More"

        It is safe to say that the internet of things can bring many benefits not only to the regular life of casual citizens but also for many business organizations and authority institutions. Enterprises have a lot more access, devices, and appliances, therefore it needs even better and accurate overwatch of devices.
        Manufacturers realized what is IoT and what are the benefits of its capabilities so they started adding sensors to collect data on their devices. By adding sensors, companies can transmit data back and forth, and see how their products are performing. IoT applications and devices can be implemented in various industries, can offer industry-specific sensors or real-time location devices. By the year 2020, it is predicted that across the industries there will be the amount of 4.4 billion IoT units and it will hit $3 trillion revenue. Let’s take a look at the industries that already started applying cutting-edge technology.
        • Medicine and healthcare. The newest sensors enabled doctors to get real-time access to the patient’s health status, collect and store data about it in the cloud. The IoT technology in medicine has significantly decreased the time of typical procedures, simplified the processes while reducing and mitigating disease risks, and improved the use and availability of hardware.
        • Sharing Economy. With the combination of the internet of things and blockchain, the sharing economy has been reshaped into a “Blockchain of Things”. The combo of both technologies has created possibilities for many marketplaces to collect and share data due to the concept of Smart Contracts.
        • Education. What is IoT in education doing, is that with the share of access to data, many people across the world can approach information and formal or informal education.
        • Retail. Automating as much as possible processes of delivery systems is the key to quick and safe transmissions. Automation makes the process effortless.
        • Travel. The migration of the people through the world is one of the most frustrating procedures that require a lot of security attention and information processing. With the implementation of IoT in travelling, agencies are now able to deliver real-time information and automate most of the processes that make travelling a smooth and pleasing experience.

        Career Possibilities in IoT Field

        There is no question that the growing field of the internet of things will need experts that are willing to improve it. Named as the next “Industrial Revolution”, the IoT field can be a great place to start a new career or shift towards it. What are the demanded skills in such an industry?
        • Information Technology Infrastructure Library (ITIL). Considered to be one of the vital elements in what is IoT, ITIL is a great addition of stability, networking, and security in the technology.
        • The Open Group Architecture Framework (TOGAF). Compared to what HTML did to HTTP for web development, TOGAF is the element that will enable connecting everything instantly. Having a TOGAF certification can be one of the best ways to get into the internet of things field.
        • Big Data. As mostly everything on the digital space revolves around data, the IoT will generate even more data to store and process, therefore there will be, or is right now, a huge need of Big Data specialists to handle the amounts of data created by IoT.
        • Blockchain. Although the blockchain is not considered as a part of IoT, the secure nature of it can become crucial in the upcoming years.


        Amazon Go example of what is IoT
        Source: Amazon.com

        An Example of Amazon Go

        If you are still not sure what is IoT or whether it is a relevant thing in your surroundings, there are many daily examples of it where it is used. We can begin by one of the most known examples that people use in their households – Amazon Go. Being one of its kind, Amazon Go is an app that allows users to shop with no checkout required. By having a certain application on your phone, you walk into the store, collect the groceries you need and leave. No lines, no checkouts. The IoT system behind it collects data using deep learning algorithms, computer vision, and sensor fusion. Just like self-driving cars, Amazon Go is using the same technology.

        Overview – What are the Predictions?

        The internet of things technology did not come out of anywhere, it is the evolution of the internet throughout the years that lead to it. Otherwise known as WEB 3.0, the process has still a long way to go. It is predicted that in the upcoming years the definition of what is IoT will become even smarter. Many companies and authority institutions will presumably start using this technology to save money and time, therefore increasing the efficiency of people’s work.
        Of course, with the great benefits that the internet of things will bring to our society, the growing cybersecurity danger will also increase. While managing information remotely and automatically, hackers will look for ways to get into the system and disrupt the security and privacy of users with cyber attacks. Many regulations are still yet to come and there is still a lot of work to improve the current technology, but their future of it looks brighter every day. If you want to learn the main skills that are needed in this field, head to BitDegree courses and become an expert in the IoT field.
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        Learn HTML: Find Out How to Learn HTML Fast

        Developer Tips , html
        Learn HTML: Find Out How to Learn HTML Fast

        HTML, or Hypertext Markup Language, is one of the most common forms of code in the world. It is used on pretty much every single web page in existence, and it allows web designers to present text, images, videos, and other content in a clear, concise manner. Naturally, many beginners choose this language to learn first, yet find the difficulty to understand what is the best way to learn HTML.
        If you want to become a front-end web developer, learning HTML is essential. Luckily for you, there are hundreds of websites out there teaching you HTML basics that will allow you to build a simple HTML page. However, these websites don’t always teach you the best or most efficient way of how to learn HTML. They don’t always teach the most up to date version of the language, and they don’t always teach you everything that you need to know.

          What Is HTML & Why Should I Learn It?

          HTML is incredibly widespread. It is primarily used by front-end web developers to style and present web content in a readable manner. If you want to be a front-end developer, this markup language should be the first one on your list.

          How Does HTML Work?

          One of the primary features of the HTML language is its use of tags to style text and other visual elements. Some examples of these tags include:
          • <p></p>, which are paragraph tags. They tell your web browser that everything between the tags belongs in one paragraph.
          • <title></title>, which tells your web browser what the title of the page is.
          • <video>, which allows you to insert a video directly onto your page.
          It is relatively easy to learn HTML tags when you notice that they have a few features which are clear and universal:
          • Most HTML tags begin with an opening tag, <> and finish with a closing tag, </>. However, there are a few elements that don’t need a closing tag.
          • In most cases, the content that we want to be defined by the tags goes between the opening and closing tags. Sometimes things are included within the opening tag.

          HTML & CSS Go Hand in Hand

          Although it can be used on its own, it is very rare for someone to use HTML by itself. In most cases, HTML is used to define the general layout and look of a webpage, while a different language, CSS, is used to style the content.
          The main reason for this is because HTML is limited in what it can do. Using HTML you have limited styling of text and image properties. You can define what type of text you want to include, you can make tables and lists, and you can embed things like images and videos. However, it is difficult to change things like the font, text colour, and the exact positioning of elements within a web page.
          Therefore, it is recommended learning HTML and CSS together.

          Why Learn HTML?

          HTML is an essential language for anyone who is aspiring to become a front-end web developer. This markup language is used on pretty much every web page in existence, and it makes it simple to create engaging content in a way that web browsers can understand, and it is simple to learn and easy to use.
          Some of the other reasons why you should seriously consider learning HTML include:
          • It is simple. If you have zero coding knowledge, but you would like to become some sort of coder or programmer, it is best to learn HTML in the first place. It is easy to learn and use, it will provide a good introduction to coding, and it will help you get your head around basic coding concepts.
          • It can help you find a job. Programming and coding, in general, are in-demand skills which companies throughout the world are looking for. Simply having some knowledge of HTML basics to put on your resume can make you more employable and can help you find a job.
          • It could result in a promotion or pay rise. As said before, coding skills are in high demand in the modern world. Even the most basic programmers are charging up to $100 per hour, which means that having programming skills could help you get your next promotion or pay rise.
          As you can see, there are plenty of reasons why HTML is a great language to learn.

          Who Should Learn HTML?

          HTML can provide a basic introduction to coding, that it could help you find work, and that it could provide the basis for a pay rise. In line with that, here are three groups of people who should think seriously about learning HyperText Markup Language: 

          Aspiring front-end developers

          HTML, CSS, and JavaScript form the basis of front-end web development. This means that if you are serious about becoming a front-end developer, HTML has to be your second nature. The fact that it is simple and easy to learn means that it is often the first language that aspiring developers dabble in.

          People who work in content management or other internet related fields

          Anyone who works in content management, writing, or anything else related to digital content should learn HTML immediately because it could benefit them greatly. For example, let’s say that you need to write articles for a client’s website, but that you have to publish them directly into the website. Sure, you could probably manage without knowing HTML – content management systems like WordPress and Wix have made sure of that – but it will be a lot easier if you understand how to format a simple HTML page.

          Website/blog owners

          If you own and run your website or blog, you may find it very beneficial to learn the basics of HTML. Doing so gives you more flexibility when it comes to formatting both your website and your content, potentially saving you money. After all, web developers are expensive, and it could cost you a small fortune to employ a developer for even a few hours. You would be much better off if you were able to make small HTML changes by yourself.

          What Is The Best Way To Master HTML?

          Some people will be more suited to different methods of teaching, and the best way to learn HTML for one person won’t necessarily be the best way for another. Keep this in mind as you read the following couple of paragraphs.
          Now, for most people, the best way to learn HTML is through an interactive online course. As a language that has been developed for use on the internet, it makes sense to use the internet to learn the basics of HTML. Some of the features of online HTML courses make them the best way to learn include:
          • They are fun and engaging. This means that they make it easier to stay motivated, which reduces the risk of you giving up before you have finished your course.
          • They cover the basics first, meaning that you aren’t wasting your time learning irrelevant information at the start.
          • Many online HTML courses allow you to write code directly in your browser as you learn, teaching you good habits from the beginning.
          If you think that you would like to learn HTML and that an online HTML tutorial would be a good place to start, then check out the courses on the BitDegr platform.  
          The Interactive Coding for Beginners HTML course is perfect for people who are on the way to becoming front-end developers. It teaches both HTML and CSS alongside each other, it will show you how to use them together, and it will also introduce you to the basics of responsive web design.
          learn HTML and CSS with Space Doggos
          Learn HTML and CSS with Space Doggos
          If you’re a little short on time and just want to get a brief overview of HTML, you could start with the HTML Coding For Beginners Course. This course will teach you the basics of HTML coding, along with some of the most important syntax, in under an hour of video tutorials.
          Alternatively, you could start with a more advanced course, the Comprehensive HTML5 Tutorial. This course contains just under 5 hours of video lessons, and it will teach you basic HTML principles, how to implement these principles on a website, and how HTML is used in apps.

          What Other Resources Should I Use?

          When searching the internet for the answer to how to learn HTML, you will uncover a lot of different resources. Some of these are free, some of them are paid (more on that in the next section), but the single common theme is that they all claim to be the best.
          However, a lot of these resources are outdated. This doesn’t mean that there aren’t good ones out there, but you should be careful. Consider the following things to help you uncover HTML basics alongside your main course:

          YouTube Videos

          Watching videos that touch on difficult or confusing concepts can be a great way to learn HTML and get your head around things that you’re struggling with. If you find yourself having trouble with a specific concept – or if you would simply like a deeper explanation than your course offers – search for the answers on YouTube.

          Language Reference Guides

          Language reference guides are a great resource that you can use to discover new syntax, to refresh your memory on old syntax, or to learn pretty much anything else about a programming language. Check out BitDegree’s HTML reference guide to learn all about the tags and elements you can use. Here you can also find code snippets and try them out live in the free code editor.
          BitDegree Learn HTML resource

          Online Forums

          If you can’t find the answers to your questions anywhere else, you can always ask other people who have a better understanding of how to learn HTML than you do. Online forums and chat boards are a great resource for people who are trying to learn a programming language like HTML. Use them to ask questions, participate in discussions, and to discover the solutions to even your most difficult problems.

          Free Resources vs Paid Resources

          Now that we’ve covered the types of resources available to HTML learners, it’s time to have a quick look at a debate that has grown in magnitude over the past few years – free resources vs paid resources. It is quite simple to find free programming courses and other resources on the internet, but are they worth using? Or should you be paying for your courses to make sure that you’re learning everything you can?

          Historically, people have had to pay to learn HTML and access to high-quality learning materials. There are a variety of such resources on the internet, ranging from paid tutorials to paid tutors and code helpers.
          Pros of Paid Resources:
          • You will be learning from industry professionals who know about the things that they are teaching. This can help reduce the risk of learning incorrect information or poor habits.
          • When you pay for something, you’re more likely to use it. This will help you stay motivated, and may result in better results from the learning process.
          • You will probably find that paid courses are very well organized and that they contain all of the relevant information.
          Cons:
          • Not everyone can afford them.
          • Some people want to delve into coding without committing themselves. Paying to learn HTML can feel like a commitment to some.
          • Paid courses don’t always provide the answers to simple questions quickly and efficiently. If you want to learn how to do one specific thing, look for free resources.

          Free Resources

          The rise of alternative income sources like internet advertising and ‘freemium’ courses means that a huge number of free courses and other free resources have made their way online in recent years.
          Pros:
          • They require no financial commitment, which is great for people with little money.
          • If you don’t like a free resource, you can just choose another one without losing anything from a financial perspective.
          • Free resources are accessible to anyone with an internet connection and a little bit of time. This means that people can learn HTML basics without committing to a course.
          Cons:
          • Free resources can be of lower quality than paid resources. This is because they are sometimes created by people who are less than professionals themselves. They can contain incorrect information, and they can miss important details.
          • There are so many free resources out there that it can be super hard to find the ones which are right for you.
          • Sometimes it’s worth paying someone for a simple answer, rather than having to wade through pages of forum replies or Google search results.
          As you can see, both free and paid resources have their positive and negative aspects. If you are serious about becoming an HTML professional, we would recommend paying for a course. However, if you want to discover the language without committing, free resources can help you do that.

          How Can I Practice Writing HTML Code?

          Once you have decided to learn HTML and have mastered the basics, everything comes down to practice. The best way to learn HTML is by practice and you can do that by creating your website. There are a few options for this:
          • Try to create your own site by using a code editor, add the necessary CSS/JavaScript to make it work. This is featured as well in the Interactive HTML & CSS course, where you are building your website step by step.
          • Use a drag and drop website builder that eliminates the need for more complicated languages like JavaScript or PHP, and focus on the HTML syntax. You can check this best free website builder guide to find some options that won’t hurt your wallet.
          If you think that you are not ready for a website yet, you can further find ways of how to learn HTML and advance your skills by doing small challenges:
          • Try the code examples in BitDegree Learn and tinker them to your liking.
          • Participate in Code Playground and submit your creations.
          • Find interesting pieces of websites and try to copy/recreate them yourself.
          • Participate in coding challenges.
          • Try to solve HTML issues on StackOverflow.
          • Learn CSS and see how it enhances your HTML skills.
          Once you’re ready for more advanced challenges, you can start taking freelance jobs or, if you learn CSS and JavaScript along the way, even start trying to find a proper job as a front-end developer.
          Whatever method you choose, remember this – if you don’t practice a skill, you will lose it.

          So, What Is The Best Way to Learn HTML?

          HTML is the language of the internet. If you are looking for how to learn HTML, you should start with an online course that will explain to you how this language works in a structured and organized way. A lot of people choose to use paid resources when learning a programming language for the first time, but this isn’t essential. Free courses can be useful as well, especially if you aren’t sure if you want to become a web developer or programmer.
          Remember, if you want to learn HTML properly, you need to practice, practice, and practice some more. Good luck, have fun, and welcome to the world of HTML!
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