Hardly any news feed appeared in the last few days without updates on ChatGPT – for experts an easy read, for the most readers hard to understand. With this post on the BIENE IT blog, we want to give you a brief overview of the hype issue and summarize the most important information about the OpenAI chatbot. And here we already come to the first special term: AI is an abbreviation for “Artificial Intelligence”. ChatGPT enjoys a high level of attention since its launch in November last year: after only two months, the application counted more than 100 million users worldwide. Among other things, the program is described as a significant milestone in the development of Artificial Intelligence. What makes the Generative Pre-trained Transformer, short ChatGPT so special?

Digital chatbots are not new per se: computer-based programs that are able to interact with real persons exist for quite some time now. But conventional chatbots are mostly topic-limited and often wrong with their answers: the ChatGPT mainly impresses with human-like interaction. Communication with the new AI chatbot is based on the principle of machine learning (ML in short), not on predefined answers as usual. The AI tool is built on a special model of Artificial Intelligence, called transformer. This allows the AI program to understand and operate on a large amount of data and then apply it accurately. The application remembers the conversation progress and keeps learning. This makes the dialogs less rough and more realistic: Artificial Intelligence that is intended to make the most natural impression possible. The self-definition of the OpenAI chatbot is: “My purpose is to engage in natural language conversations with users and provide them with accurate and relevant information on a wide range of topics. I am constantly learning and evolving as I receive more input and data from users, which helps me to improve my responses over time.” The AI program was trained on a large amount of texts data
from various sources, including books, articles, news, and websites. It was developed by OpenAI: first generations of GPT chatbots were released back in 2018. As for the technology, it is an in-house product of the AI pioneer. The Artificial Intelligence program is currently not connected to the Internet, so its knowledge is limited to the test data, which extends to 2021. The further development ChatGPT-4 provides for some changes, including real-time connection to the Internet as well as refined speech processing and conversation control.

ChatGPT: Use, perspectives and limits
The intelligent AI chatbot can be applied to a wide range of tasks, including text generation, translation and voice control. The main advantage of ChatGPT is time saving: thanks to its ability to perform human-like conversations, it can support customer service interaction, for example. Machine learning makes it possible for the AI tool to acquire more and more relevant knowledge and remember the previous conversations. Text generation is also of interest to marketing and sales departments, among others. The interactive AI program can furthermore improve the user experience in virtual and augmented reality applications.

The future of AI chatbots is promising. With continuous development and increasing amounts of data, follow-up versions of ChatGPT can take on more complex and challenging tasks and be used in e-commerce and online banking, among other fields. The use of AI chatbots in education and healthcare is also a possibility. But it is important to keep in mind potential risks and ethical concerns. As it is typical for any other Artificial Intelligence, ChatGPT can make mistakes or deliver problematic results. A filter is used to prevent the output of false information or violent and discriminatory content, but it doesn’t work properly at all times. There is also room for improvement in terms of understanding context: the OpenAI chatbot can have difficulty in categorizing complex contexts correctly. The AI tool cannot always respond accurately to emotional topics that require empathy. Also of concern, according to experts, are privacy and security issues: Artificial Intelligence relates to large amounts of data, some of which may contain sensitive and private information. These require special attention and explicit legal regulations.

Scripts and cyber security: what about ChatGPT in IT?
The AI chatbot can also be used the IT sector: Its script skills include common programming languages, such as Python, Javascript, C++, Java, PHP, Go, Swift, Typescript and PowerShell. Unlike traditional AI models that can write codes, ChatGPT is able to revise the codes it creates. If you find bugs, you can describe them to the AI program and ask it to make appropriate corrections. As a reminder, thanks to machine learning, the AI tool builds its capabilities with each request. There is no need to write a script from zero. So, ChatGPT can save a lot of time and effort, but it also poses risks. Hackers can take advantage of the AI program to generate malicious code. Further cyber security threats arise from the ability of the chatbot to produce error-free text. This makes it easier to create phishing emails: one of the criteria for unmasking them so far consisted of a big number of errors in spelling and grammar. A direct request to set up a phishing mail would be rejected by the AI program thanks to the built-in filter, but it composes a support mail asking for private data or offering malicious software for download without any problems. As mentioned above, ChatGPT cannot contextualize well yet.

Other IT risks include identity theft (the AI tool can simulate real people or organizations and request confidential information) and social engineering attacks (the ChatGPT can conduct human-like conversations and, in the worst case, persuade the conversation partners to take certain actions, such as downloading malware). Deception of customer support to illegally capture sensitive information is also possible. AI chatbots can help criminals improve the quality of their attacks: cyber security awareness is becoming increasingly important in this context.

How to use: try the ChatGPT for free
After informing you about the features, risks and opportunities of Artificial Intelligence, we are pleased to explain how you can use the AI Chatbot for free. You can access the ChatGPT via this link: https://chat.openai.com/. In order to use the application, you must register. During registration, you provide your email and phone number, and confirm your request with a verification link and an SMS code. In addition to free use, OpenAI also offers a paid version of ChatGPT. It stands out with more detailed answers, integration possibilities with other applications and priority support, just to name a few. If the website is not available due to many requests, just visit it again later. We from BIENE IT wish you a lot of fun with the innovative AI program!

IT security is becoming more and more important in the business environment. There are many reasons for this change. On the one side, the Corona pandemic favoured remote working, and on the other, the trend towards new work structures emerged years ago. Known as New Work, this way of working refers to location-independent labour, whether on the road, in a home office or in co-working spaces. Accordingly, many employees have virtual access to relevant IT systems and applications. These usually contain important information including sensitive business and customer data that is not intended for third parties. If this information becomes public (for example through a cyber attack), it can not only destroy the reputation and customer trust, but also damage the entire economic viability. A cyber attack is a real threat to companies of all sizes and industries today. The good news is: with a sophisticated IT security strategy, the risks from such an attack can be minimised and downtimes limited. Prevention activities that include several components are particularly successful.

For us, the following preventative activities proved to be effective:

1. Additional analogue data backup on tape
The additional backup to tape using physical storage media is still one of the most effective backup solutions. With this analogue variant, it is important to back up and check all business-critical data regularly. The obvious advantage of this offline alternative: tape backup offers a quick way to restore data. The information can be easily recovered to the original systems. Other advantages of this storage technology: large capacity, good price-performance ratio per gigabyte, relatively high data transfer speed and long durability. Backup to tape is of particular interest to companies that need to store or archive large data backups for long time periods. If the backup tapes are stored at the external location, they are also well protected against possible break-ins to the company rooms or natural local disasters. As offline data media, the tapes are separated from all IT networks (“air-gapped”), so they cannot be infected with malicious software.

2. Weekly tests of data backups
Regular backups of relevant business data are essential. It is equally important to test these backups on a regular basis. We recommend random tests of data backups once a week. In fact, the recovery performance relates to the purpose of the data backup: to restore the information quickly and completely in the event of an incident. Otherwise, there is a risk of data loss and, in most cases, the associated financial damage. Therefore, test data backups should be a regular part of the company’s internal backup solutions.

3. Use of Next Generation Firewall (NGFW)
In opposite to the previous versions, which examine the incoming data traffic on the basis of known protocols and ports and block access to the system in case of abnormalities, the newer firewalls differentiate much more strongly between the individual types of data transmission. They analyse not only the port and protocol, but also the content of the data stream. This makes it possible to filter out individual infected files before they are transmitted and thus proactively protect the network. The Next Generation Firewalls also act much more autonomously and can decide independently of existing rules which contents are blocked – based on their own analyses. NGFWs thus combine a rule-based approach with Intrusion Prevention Systems (IPS) and application control. This means: the Next Generation Firewall can independently take different steps to defend against the attack when dangers are detected. Some modern solutions offer additional functions, including content filters, anti-spam or anti-virus.

4. Use of Next Generation Antivirus (NGAV)
Conventional anti-virus works on the basis of signature match and heuristic analysis. The original AV solutions recognise certain sign sequences that are assigned to different types of malware and thus prevent a cyber attack. The NGAV solutions are designed as a holistic security approach and are also effective against fileless attacks or non-malware threats, among other things. In general, the term Next Generation Antivirus refers to security solutions that pursue a proactive and system-oriented protection approach and cover an even greater variety of risks. They are characterised by automatic response actions: This involves the ability to detect and fix problems on their own, without user input. Modern solutions usually require less space, and their installation and operation are less time- and resource-intensive. In addition to malware signatures or heuristic analyses, the latest generation of virus protection uses other technologies, such as cloud scans.

5. Segmentation of network areas
Network segmentation is an architectural approach in which a network is divided into several segments, creating separate segmental networks. Each one then functions as a sub-network, i.e. a small network of its own. This type of network segmentation is called physical. In logical segmentation, sub-networks are usually created by so-called Virtual Local Area Networks (VLANs). In VLAN-based approaches, data traffic is automatically routed to the appropriate sub-network based on special markers. Segmented network areas can stop the spread of threats or limit them to a single network due to the isolation. It is possible to determine security controls and requirements individually for each sub-network. The clear benefit of any segmentation: prevention of greater damage. Another less obvious benefit: thanks to network segmentation, overloads are reduced and therefore the total performance is improved.

6. Use of IPsec / SSL security protocols
The term IPsec stands for Internet Protocol Secure. It refers to a group of protocols used while building encrypted connections between devices. IPsec protects data that is transmitted over public networks by encrypting it. The term SSL stands for Secure Sockets Layer. This security protocol encodes HTTP traffic, for example in connections between user devices and web servers. The SSL is also able to block certain cyber attacks. Because this security protocol authenticates web servers, it can detect fake websites and also prevents hackers from manipulating data during transmission. Both IPsec and SSL are used in VPN setup. The main difference: with a security protocol based on SSL, it is possible to configure limited access to web applications. With IPsec VPN, every user can see all the data contained in the VPN: the function of individual access control is not available in this case.

7. Citrix Workspace with greater restrictions
Citrix Workspace offers digital workplace solutions that are available regardless of location and device. Access is provided by a standardised user interface and follows the zero-trust approach. This can prevent attacks at the network level. We carry out further special configurations, for example in terms of security policies, so that your IT security is additionally improved.

8. User account with 2FA access
2FA is an acronym for two-factor authentication (the generic term is MFA, means multi-factor authentication). This refers to a login process that requires more than just a password. In addition to the password, another factor is needed for logging into the user account. The context: many users share the same password for several accounts. If one of them is hacked, it is easy for cyber criminals to log in into other systems. Two-step verification builds an additional security barrier by asking for a one-time code or fingerprint, for example. The combination of factors from different categories, for example knowledge (password, code, security questions), biometrics (fingerprint) and property (smart card) is considered particularly secure. By the way: the same security approach can also be applied to VPN connections.

9. Weekly Nessus scans of the entire IT infrastructure
Nessus is a network and vulnerability scanner for almost every common operating system (Linux, Unix, Windows, macOS). It is one of the best established tools for testing IT security: with the help of Nessus scans, vulnerabilities can be discovered and security gaps can be closed. Users have many plug-ins available which, once downloaded, check the relevant systems and elements carefully. Thanks to the client-server principle, Nessus makes it possible to connect to one or more clients from the server. This is why it is also called a “remote scanner”. As soon as all desired scans have been executed, Nessus gives an overview of possible security gaps or open ports. We recommend weekly Nessus scans of the complete IT infrastructure.

10. Implementation and evaluation of a pentest
The so-called IT penetration test, or pentest for short, is a detailed security test of individual computers and/or networks. Basically, it is a controlled test hacker attack. Since it is an arranged monitored attack, the term Ethical Hacking is used synonymously. With your consent, we simulate a hacker attack on your systems (internal and/or external) to detect and close possible security gaps and vulnerabilities (server systems, firewalls, WLAN networks, VPN access, etc.). The pentest is a kind of snapshot, because it always refers to the current state of your systems and the threat scenarios known at the time of execution. A penetration test is a customised service and is tailored to the IT infrastructure being tested. The pentest not only allows you to identify possible vulnerabilities, but also to prevent serious reputational and financial risks. The results provide information about the current security level and vulnerability of your IT systems. The reports should be analysed in detail and serve as a basis for the company’s internal IT security concept.

What is SD-WAN?

SD-WAN or Software defined WANis a software-defined approach to managing wide-area network (WAN). This means that SD-WAN automatically determines the most efficient way to route traffic between branches and data locations. Powerful Software enables Information Technology (IT) and network engineers’ employees to remotely program edge devices, reduce delivery times and minimize or eliminate the need to manually configure routers in remote locations because SD-WANs are managed by a centralized controller.

What is DevOps?

There are multiple interpretations of DevOps (development and operations). Essentially, many features of this approach already exist in most well-functioning cloud organizations. From this angle, DevOps looks more like an evolution than a revolution in the way the company IT sector works.

DevOps can be viewed from three angles – people, processes and technologies. Seen through the prism of human relationships, DevOps is a philosophy that seeks to break down traditional organizational silos, and especially the strict separation of teams engaged in application development and infrastructure management. It is common to see development teams as messengers of change, and admin teams as guardians of stability, or as two teams with opposite goals, which leads to inefficiency. The DevOps approach changes that. When it comes to processes, DevOps integrates agile development principles into mode. As a standard, agile principles are used to continually create code ready for the production environment, but with DevOps this thinking is transferred to managing the entire infrastructure.

OEM (Original Equipment Manufacturing) and ODM (Original Design Manufacturing) are two important terms related to the manufacturing and electronics industries. These terms can sometimes be confusing to people who are new to these industries. Small companies or startups hire some resources from OEMs and ODMs to produce and design their final products.

What is OEM?

OEM (Original Equipment Manufacturer) is a term that describes the network of relationships among hardware component manufacturers, IT software vendors, IT hardware suppliers, and channel partners, such as distributors and resellers. The term Original Equipment Manufacturer used to refer to a company that originally built a particular product, which was then sold to other companies for re-branding and resale. At this point, this term has become a label used to describe different companies and relationships between companies. OEM relationships are very often similar between companies that bring IT products to market. It is not uncommon for a company to act as an OEM and simultaneously sell systems to other OEMs. This fluidity in the IT world creates unclear relationships because they can easily confuse product designers, resellers and manufacturers.

On the other hand, we can say that the OEM product is made according to the customer’s product specification. For example, any product tailored to the design, material, dimensions, functions or even colors can be classified as OEM.

OEM Main Benefits

• It’s hard to duplicate your product
• The intellectual property of the product is yours
• You can customize the product to your requirements

What is ODM?

ODM (Original Design Manufacturer) is a term that describes a company that takes the original specifications of another company or individual and builds a product designed to the exact specifications based on it. ODM, as a way of doing business, enables a company to market a product without the need for complete hardware design, and therefore without investing in manufacturing facilities. The company that created the specification usually retains ownership of the design. The best example of classic ODM is the white box server, (white box server it’s a data center computer not manufactured by a well-known brand vendor). ODM usually builds equipment from commercial components and may be slightly adapted to specific environments. The advantage of ODM is that it can build and deliver custom servers faster, and it can also offer a parts protection guarantee.

ODM products, often referred to as “private label products”, can be branded with a customer logo.

ODM Main Benefits

• Saves money and time
• Faster market development than OEM
• The company is not responsible for the creation of new equipment
• Dealing with trusted manufacturers reduces the chances of product duplication

OEM Hardware

The use of the term OEM in the IT industry’s hardware segment has several meanings. OEMs can best be described by the most famous companies such as Hewlett Packard Enterprise (HPE), HP Inc., Dell, EMC, and Lenovo. These aforementioned companies are well-known hardware manufacturers who buy components from other companies and sell complete systems under their own designation. Such companies procure microprocessors, hard drives, and other equipment from OEM parts suppliers, who see them as OEM customers. Component suppliers often create an OEM product as well as retail versions of their offering. Hard disk sellers, for example, produce bare hard drives for OEM customers and retail hard drives that come in an accessory box, such as cables and installation instructions. Original brand manufacturers can also purchase entire systems from Original Device Manufacturers (ODMs), which produce various computing devices from laptops to servers. ODMs such as Foxconn Electronics Inc. and Quanta Computer Inc. historically have sold systems to OEMs, but in recent years, some ODMs have begun selling directly to large end customers.

OEM Software

Software companies also sell OEM versions of their products to large OEMs or smaller system vendors who embed software in their own products. Third-party operating systems and applications that deliver to end customers are pre-installed on a multitude of products. The best examples of OEM software are desktop computers, laptops, tablets and smartphones. OEM software arrangements can also be found between software developers as well as between developers and hardware companies. The best example of this is VMware, as it allows OEM partners to incorporate some of their virtualization products into their software offering. Also, Autodesk enables third-party solution developers or third-party software vendors to develop custom applications based on Autodesk’s computer design software. 

OEM VS ODM

When it comes to OEM and ODM Vs, it is necessary to consider several aspects, including the advantages and disadvantages of both types of production system.

OEM companies make products based on designs provided by another company. The OEM produces only what the customer requires. This way both companies benefit from each other. In some cases, companies rarely have the machines needed to produce large quantities of products on time, and outsourcing production may be cheaper compared to in-house production. So, these companies outsource production to OEM companies.

ODM, on the other hand, designs and manufactures the products themselves. These products are often known as Empty Products or White Label. The buyer company can re-brand and sell them as their products.

In most OEM products, customers typically require the production of specific parts or machine parts that are based on a particular design. The customer assembles and sells these parts of the product under the trademark. Most of these products are available at competitive prices because the costs incurred during the OEM manufacturing process are relatively lower.

ODM companies, on the other hand, produce the kind of product you need. But only in these products can changes be neglected. However, customers can benefit from such suppliers because there is almost no need to design products and spend time on research and development. Customers can use the expertise of ODM companies that produce bulk goods for the benefit of smaller companies. There are basically two types of categories in the production of ODMs, namely private and white label. Private labeled products are finished products that are sold to a particular seller. White label products, on the other hand, are generic products sold to different retailers, sold under different brands.

OEM products are basically components that a manufacturer sells based on a customer specification, whereas ODM products are finished or pre-designed products that will be sold with the buyer’s company brand.

ODM products are complete and finished products compared to OEM products.

Author: Miloš Denić

What is Kubernetes?

Kubernetes is a very popular open source platform for container orchestration. That means the Kubernetes platform is used for managing applications built from multiple, mostly standalone runtimes called containers.
Since the launch of the Docker Container Project in 2013, containers have become increasingly popular. As container’s use increased over time, large and distributed container applications have become increasingly difficult to coordinate. Just for this reason Kubernetes appeared and launched a revolution. Kubernetes has become a key part of the container revolution because it is making container applications drastically easier to manage at scale. Kubernetes is most often used with Docker (Docker is the most popular containerization platform). Kubernetes can also work with any container system that conforms to the Open Container Initiative (OCI) (OCI is standards for container image formats and runtimes). As mentioned above Kubernetes is open source and because of that has relatively few restrictions on how it can be used. Kubernetes can be used freely by anyone who wants to run containers, also, it can be run in the public cloud or on-premises, or both.

What are Containers?

Container technology gets its name from the shipping industry. Instead of devising a unique way of sending each product, the goods are placed in steel shipping containers, which are already designed to be lifted by the crane at the dock and put on board designed to accommodate standard sized containers. In short, by standardizing the process and holding the item, the container can be moved as a unit, and it costs less to do it this way.

Container is a technology method to package an application so it can be run, with its dependencies, isolated from other processes.

With container computer technology, this is an analogous situation. Did it ever happen that a program on one machine worked perfectly, but then turned into a clumsy mess when moved to the next? This can happen when the software is migrated from the developer’s computer to a test server or physical server from the company’s data center, to a cloud server. There is a problem moving the software due to differences between the machine environment, such as installed OS, SSL libraries, network topology, security, and storage.

Just as a crane takes an entire container as a unit to put on a boat or truck for transportation, which makes it easy to move, computer container technology does the same. Container technology not only contains software, but also dependencies, including libraries, binaries, and configuration files, together, and they migrate as a unit, avoiding machine differences, including OS differences and basic hardware that lead to incompatibilities and crashes. Containers also make it easier to deploy software to the server.

Containerized microservices architectures have profoundly changed the way development and operational teams test and deploy modern software. Containers are helping companies modernize by facilitating scaling and deployment of applications, but containers have also introduced new challenges and complexity by creating a whole new infrastructure ecosystem.

Large and small software companies now place thousands of copies of containers daily, which is the complexity of the scale they have to manage. This is the reason why they use Kubernetes.

Why use Kubernetes?

Kubernetes is originally developed by Google and as we mention above is an open-source container orchestration platform designed to automate the deployment, scaling, and management of containerized applications. Definitely we can say that the Kubernetes has established itself as the standard for container orchestration and is the major project of the Cloud Native Computing Foundation (CNCF). Kubernetesis supported by the most popular companies in the IT industry like Google, Microsoft, IBM, AWS, Cisco, Intel and Red Hat.

Here are the 4 most important reasons why more and more companies are using Kubernetes:

1. Kubernetes is very efficient and reduces costs.

Kubernetes and containers allow much better use of resources as opposed to hypervisors and VMs, because the containers are light in weight thanVMs, they require less memory, CPU, and other resources to operate.

2. Kubernetes is very compatible with cloud.

Kubernetes runs on Google Cloud Platform (GCP), Amazon Web Services (AVS), Microsoft Azure and you can run it on-premise. You also can move loads without having to redesign your applications or completely revise your infrastructure – allowing you to standardize on the platform and avoid locking vendors.

3. Your cloud provider will manage Kubernetes for you.

Major cloud service providers offer numerous Kubernetes-as-a-Service deals. Google Cloud Kubernetes Engine, Azure Kubernetes Service (AKS), Amazon EKS, Red Hat OpenShift and IBM Cloud Kubernetes Service all fully manage the Kubernetes platform so you can focus on what’s most important to you – uploading applications that delight your users.

4. Kubernetes helps you move faster and growth your business.

Kubernetes allows you to deliver a self-service platform as a service (PaaS) that creates an abstraction of the hardware layer for development teams. Your development teams can quickly and efficiently request the resources they need. If they need more resources to handle with the extra workload, they can get it just as quickly because the resources come from infrastructure that is shared across all your teams.

How Kubernetes work?

Kubernetes makes it much easier to deploy and handle applications in a microservices architecture. It does this by creating an abstraction layer on top of the host group so that development teams can deploy their applications and let Kubernetes manage all the important processes.

Processes managed by Kubernetes are:

• Moving an application instance from one host to another if there is a shortage of resources in a host or if the host dies.
• Monitoring resource consumption and resource limits to automatically stop applications from consuming too many resources and restarting the applications again.
• Automatically leveraging additional resources made available when a new host is added to the cluster.
• Evenly spreading application load across a host infrastructure.
• Controlling resource consumption by team or application.
• Easily performing rollbacks and canary deployments.

The phrase “Internet of Things” was first used by Kevin Ashton, most likely in 1999, as the title of a presentation he gave at Procter & Gamble. When he was a part of the company, Ashton came up with the idea of putting RFID, an intelligent barcode, on every lipstick they produced so that they could retrieve information about the number of products sold, and when to replenish the shelves at any given point of time. He very rightly claimed that such data could solve many problems in everyday life.

Today, billions of devices are an integral part of the Internet of Things platform, using embedded hardware and software to send and receive data through various communication protocols. So, they could also use our smartphones to access the internet, which would again be connected to some other piece of hardware that would be in our household, for example, and act as a central part of the network.

Many people dream of “smart homes” where every device would automatically function when required. The wake-up alarm and the coffee machine would be programmed to make the day easier, the lights would come on when the owner approaches the house, and a computer device would answer his voice commands, read messages and select the television channel on demand while he prepares the dinner. For decades, such instances were a part of science fiction movies, and today they are already a part and parcel of our reality, and would not be fascinating any more in near future, and all modern technology, which will be an integral part of that future, forms a database they term, the Internet of Things.

The Internet of Things (IoT), also called Internet of Everything (IoE), is made up of all devices that can connect to the network, collecting, sending and operating according to the data they collect from the environment, using built-in sensors, processors, and communication hardware. These devices, popularly known as “connected” or “smart”, can sometimes “talk” to other connected devices, using a process called machine-to-machine (M2M) communication, and operate on the basis of the data received from one of the other devices. Users can set up these gadgets, give them instructions, or access data, but the devices generally work independently. Their existence and connectivity have become possible, thanks to the components available today and the constant online user presence, both at home and in the workplace.

Die Analyse großer Datenmengen ist nur ein Teil dessen, was die Big Data Analyse von früheren Datenanalysen unterscheidet. Es gibt Daten und dann gibt es Big Data. Hier finden Sie heraus, welche anderen Faktoren gelten und wo die Unterschiede liegen.

Was ist Big Data?

Big Data bezieht sich im Allgemeinen auf Datensätze, die so umfangreich und komplex sind, dass traditionelle Datenverarbeitungssoftwareprodukte nicht in der Lage sind, Daten innerhalb einer angemessenen Zeitspanne abzurufen, zu verwalten und zu verarbeiten. Diese großen Datensätze können strukturierte, unstrukturierte und teilstrukturierte Daten beinhalten, die jeweils überschrieben werden können, um einen besseren Informationsgehalt zu erhalten. Ab welcher Datenmenge ist eigentlich von „Big Data“ die Rede? Diese Frage ist nicht eindeutig zu beantworten. In der Regel geht es aber um mehrere Petabyte, bei den größten Projekten sogar um Exabyte.

Big Data charakterisiert sich durch 5 Typen:

1. Volumen – Erstellt einen Plan für die Menge der Daten, die im Einsatz sein werden und wie und wo sie gespeichert werden.
2. Variety – Identifiziert alle Arten von Daten in einem Ecosystem und wählt die richtigen Werkzeuge für deren Verarbeitung aus.
3. Velocity – Geschwindigkeit ist in modernen Unternehmen von entscheidender Bedeutung. Erforscht und implementiert die richtigen Technologien, um sicherzustellen, dass das große Datenbild so zeitnah wie möglich erstellt wird.
4. Veracity – Sehr wichtig und stellt sicher, dass die Daten korrekt und sauber sind.
5. Value – Nicht alle gesammelten Informationen sind gleich wichtig. Daher ist es von Bedeutung, dass eine Big Data-Umgebung aufgebaut wird, welche die Geschäftsanalytik versteht.

Die Datensammlung der Big Data kann aus Quellen wie Websites, Social Media, Desktop- und mobilen Anwendungen, wissenschaftlichen Experimenten und – zunehmend – aus Sensoren und anderen Geräten bis hin zum Internet der Dinge (IoT) stammen.

Enable SSH login and use root account on your Debian 9 server.

• Install Apache

apt-get update && apt-get upgrade

apt-get install apache2

Edit /etc/apache2/mods-available/mpm_prefork.conf in your text editor and edit the values as needed to optimize: