Unlike traditional rank trackers that show your positions in Google SERPs, these tools monitor how AI systems reference brands, choose sources, and structure their responses. The data helps understand whether your content influences AI-driven search, how competitors appear, and where visibility gaps exist.

The best LLM tracking tools provide three things:

1. reliable monitoring across major models,
2. clear data on citations and mentions,
3. competitive context that shows who dominates specific topics.
   

Below is an updated look at the leading options.

1. Sitechecker 

Sitechecker approaches LLM tracking with a level of detail most tools still lack. It focuses on practical analytics: how often a brand appears, which prompts trigger mentions, how citations shift over time, and where competitors stand. Everything is presented inside a unified dashboard that matches the workflow marketers already use for SEO.

What it does

Sitechecker generates several variations of a prompt for every keyword you track. This reflects the way real users phrase questions, making the visibility data more realistic. The system then runs these prompts multiple times to capture variation in AI responses. It measures:

• brand mentions,
• citation frequency,
• average position among cited sources,
• visibility across selected competitors.
  

You can open individual AI responses directly in the interface to see how the answer was formed and which domains influenced it.

The tool also supports brand variation tracking. If your brand can appear with different spellings, symbols, or spacing, Sitechecker identifies all versions automatically and attributes them correctly. This prevents missed mentions and produces more accurate visibility percentages.

Pros

• Strong prompt-level analytics with realistic question variations
• Clear citation breakdown for all runs of each prompt
• Competitor comparison with visibility trends on a single chart
• Brand variation tracking for misspellings and alternate formats
• Integrated ecosystem with Rank Tracker, GSC Dashboard, and Site Audit
• Useful alerts for visibility changes and new trends
  

Cons

• Multi-LLM monitoring is limited to ChatGPT and Gemini for now (others planned)
• No API yet for exporting raw LLM data

If your priority is dependable data and a clear picture of how AI systems talk about your brand, Sitechecker is the strongest choice. It offers deeper analytics than any other tool in this category and fits naturally into existing SEO workflows. The roadmap for broader LLM coverage makes it even more compelling.

2. LLMrefs

LLMrefs focuses on tracking raw mentions and citations across major LLMs. It supports ChatGPT, Claude, Perplexity, and Gemini, making it attractive for teams that want broad model coverage.

What it does

The tool runs selected prompts and records where a brand or domain appears inside AI answers. It provides weekly summaries, simple citation logs, and basic visibility scoring. LLMrefs does not aim to replace SEO platforms; it is built strictly for LLM-level monitoring.

Pros

• Covers multiple LLMs
• API access for exporting data
• Straightforward weekly reports
  

Cons

• Limited analytics depth
• No integration with SEO tools
• Minimal visual dashboards

LLMrefs works well for teams that only need raw citation and mention data. It gives a wide model overview but lacks deeper insights or visual interpretations.

3. RankLens

RankLens is part of SEO Vendor’s AI Suite and focuses solely on ChatGPT visibility. It attempts to capture variation by running a large number of prompt samples, giving users a broader view of how ChatGPT might respond.

What it does

The tool uses the MGPT sampling engine, which runs hundreds of prompt variations and gathers citation information from every response. This helps show how often a brand appears and which domains ChatGPT prefers to cite.

Pros

• Detailed sampling with up to 500 iterations
• Detects citations and references within answers
• Useful for early research into ChatGPT visibility
  

Cons

• Supports only ChatGPT
• No historical charts or annotations
• No API or collaboration tools

RankLens is suited for experimentation and initial analysis of ChatGPT behavior. It delivers useful data but lacks long-term tracking features and broader model support.

4. SE Ranking 

SE Ranking added an AI visibility module to its existing SEO platform. It shows how often a brand appears inside ChatGPT answers for selected keywords and integrates the results into the familiar SE Ranking dashboard.

What it does

The module provides simple visibility scores, weekly reports, and historical data depending on your plan. It is designed to complement traditional SEO metrics rather than replace them.

Pros

• Integrated directly into SE Ranking
• Historical visibility charts
• Easy setup for existing users
  

Cons

• Tracks only ChatGPT
• Add-on requires an active subscription
• No raw AI response export or API
  

This is a convenient add-on if you already use SE Ranking. It covers basic visibility needs but lacks the depth of specialized tools.

5. Nightwatch

Nightwatch added LLM tracking as a beta feature inside its SEO suite. The tool monitors brand mentions in ChatGPT and Claude responses, displaying visibility changes over time.

What it does

The module offers time-based charts and simple competitive comparisons. It is still under development and currently limited in scope.

Pros

• Integrated into Nightwatch’s SEO dashboard
• Covers ChatGPT and Claude
• Includes daily keyword tracking for SEO
  

Cons

• AI module still in beta
• Limited analytics depth
• No citation details or raw AI response export
  

Nightwatch provides a lightweight LLM visibility layer for existing users but lacks detailed insights. It’s a supportive feature rather than a full tracking solution.

Final Verdict

LLM visibility tracking is becoming as important as monitoring Google rankings. Among the current tools, Sitechecker offers the most reliable and actionable approach. Its prompt-level analytics, citation tracking, competitor comparisons, and brand variation analysis make it the most practical choice for businesses that want a clear view of their presence across AI-generated answers.

Other platforms provide partial visibility or early-stage features, but none match Sitechecker’s depth, workflow, or usability.

The post <strong>The Best LLM Visibility Trackers in 2026</strong> appeared first on DM Onzon.

Below is a practical look at which languages are worth your time in 2026 and why they matter.

Why Choosing the Right Language Matters Now

Developers used to choose languages based on personal preference. In 2026, the landscape is shaped by:

• AI integration in nearly every product
• Growing demand for scalable cloud infrastructure
• A shift toward cybersecurity-ready development practices
• Cross-platform experiences that must work on mobile, web, and desktop
  

With these trends in mind, here are the languages that give you the strongest ROI this year.

1. Python — Still the King of AI and Data

Python isn’t going anywhere. If anything, its dominance has strengthened as AI workloads continue to expand.

Why Python Matters in 2026

• It powers most machine learning, deep learning, and automation workflows.
• Endless libraries: PyTorch, TensorFlow, FastAPI, Pandas.
• Startups and enterprises rely on it for quick prototyping and production-grade AI services.
  

Best Use Cases

• AI/ML systems
• Data engineering and analytics
• Automation and scripting
• Backend APIs
  

If you want to work with AI or modern analytics tools, Python remains the safest bet.

2. JavaScript & TypeScript — The Backbone of Modern Web Apps

Web development continues to revolve around JavaScript, and in 2026 TypeScript has fully taken over as the preferred choice for scalable projects.

Why TypeScript Is Essential

• Strong typing reduces bugs and improves maintainability.
• Works across frameworks: React, Next.js, SvelteKit, Vue, Astro.
• Expanding into backend development with Node.js, Bun, and Deno.
  

Best Use Cases

• Web apps (frontend + backend)
• Real-time applications
• Cross-platform web-native products
  

If you want to build anything for browsers or cloud SaaS, TypeScript sits at the top of the list.

3. Go (Golang) — The Cloud-Native Powerhouse

Go continues gaining ground because companies need extremely fast, reliable infrastructure for distributed systems, microservices, and DevOps tooling.

Why Go Matters in 2026

• Exceptional performance with minimal resource consumption.
• A favorite for Kubernetes, containerization, backend tools, and cloud platforms.
• Clean syntax and a quick learning curve.
  

Best Use Cases

• High-performance APIs
• Cloud infrastructure
• Distributed systems
• DevOps and automation tools
  

If you’re aiming for backend or cloud-native engineering roles, Go is one of the best investments you can make.

4. Rust — The Future of Secure, High-Performance Development

Rust’s growth has been unstoppable. Its reputation for memory safety without sacrificing performance makes it a top choice for systems programming.

Why Rust Is Booming in 2026

• Zero-cost abstractions and unmatched performance.
• Adopted by major players: Microsoft, Amazon, Cloudflare, Meta.
• Increasingly used for security-critical and high-performance systems.
  

Best Use Cases

• Systems engineering
• Cybersecurity tools
• Blockchain and cryptography
• Game engines
• High-performance backend services
  

Rust has a steeper learning curve, but the long-term payoff is big.

5. Java — The Enterprise Workhorse That Refuses to Die

Despite the rise of modern languages, Java remains a cornerstone in enterprise development.

Why Java Is Still Relevant

• Massive existing codebases across banks, telecom, healthcare.
• Modern Java (versions 21+) is faster, more efficient, and cleaner.
• Popular frameworks like Spring Boot continue evolving.
  

Best Use Cases

• Large-scale enterprise systems
• Backend development
• Android development (still widely used)
  

If you want stability and steady demand, Java delivers.

6. Kotlin — The Smart Choice for Android and Multi-Platform Apps

Google continues strengthening Kotlin as the primary Android language. In 2026, Kotlin Multiplatform is finally mature enough for production.

Why Kotlin Stands Out

• Clean syntax, fewer bugs, modern patterns.
• Lets teams share logic across mobile, desktop, even backend.
• Much faster development cycle compared to legacy Java.
  

Best Use Cases

• Android apps
• Multiplatform products
• Backend (Ktor)
  

If mobile development is your direction, Kotlin is the best long-term bet.

7. Swift — Dominating the Apple Ecosystem

Apple isn’t slowing down with Swift. Its performance, clarity, and ecosystem integration make it the only logical choice for iOS, macOS, and watchOS apps.

Why Swift Matters in 2026

• Heavily optimized for Apple hardware.
• SwiftUI has matured, making UI development far easier.
• Apple device market continues to grow globally.
  

Best Use Cases

• iPhone and iPad apps
• macOS apps
• Cross-device Apple ecosystem products
  

If you want to build for Apple users, Swift is essential.

8. SQL — The Underrated Skill You Still Need

SQL isn’t flashy, but it remains one of the most demanded skills across IT roles.

Why SQL Still Matters

• Every modern application reads and writes data.
• Even AI systems rely on structured data pipelines.
• Essential for analytics, backend development, finance, and BI.
  

Best Use Cases

• Database engineering
• Data analysis
• Backend systems
• Reporting and BI tools
  

No matter what language you specialize in, SQL will support your career.

Which Language Should You Learn First?

Here’s the no-nonsense breakdown:

• AI / Data → Python
• Web apps / SaaS → TypeScript
• Cloud / Backend → Go
• High-performance systems → Rust
• Enterprise → Java
• Mobile → Kotlin or Swift
• Data fundamentals → SQL
  

You don’t need all of them. Choose based on the type of products you want to build.

Final Thoughts

In 2026, the best programming language isn’t just about popularity—it’s about where the industry is moving. AI continues reshaping products, cloud-native systems are expanding, and cross-platform development is becoming the norm. If you pick one or two languages aligned with your goals, you’ll stay relevant and competitive over the next decade.

If you want, I can also create a shorter version for social media, a long-form SEO version, or a visual comparison chart.

The post <strong>The Best Programming Languages to Learn in 2026</strong> appeared first on DM Onzon.

A creative website design agency must remember that a website’s design should be aesthetically pleasing, functional, and easy to understand. To achieve this, creative website designers must consider the learnability of their designs.

Fortunately, there are some tips and best practices you can follow when designing your website to ensure maximum learnability for users.

Understand User Goals

In web design, one must think about what the user wants to achieve through their interaction with a site. This implies that the interface should be self-evident and easy to use so that users can achieve their goals faster. Consequently understanding what your audience wants will help create a better site for them.

The first step in understanding user goals is identifying the user’s main objectives. For example if the user wants to buy something then the design should make it possible to view product details easily; compare prices as well as purchase products with ease. If someone just wishes to browse through it, design should offer a simple navigation system with clear labels and menus.

Once goals are identified it is important to think about how to make the website more user friendly. This involves making sure that navigation is understandable, layout is clean and concise while content remains accessible always. The design of the webpage has also got to be mobile-friendly because many people now access websites using phones.

It’s also imperative for any designer creating a web page not only considering but focusing on its usability by end-users as well. To achieve this, they may use such methods as testing by users where real individuals are asked about different issues related to surfing in order to define problems if they exist at all or maybe get insider knowledge on what users actually want.

Make Navigation Intuitive

Navigation design is crucial for any website since it determines how easily visitors find what they need. The most popular actions on the site, like logging in or searching, should be prominent and labeled clearly. Also, all essential pages—the homepage, contact page, etc.—should be accessible from anywhere else on the website.

Navigation elements should be clear and organized in a way that makes sense with labels that accurately describe the page they lead to. All page navigation elements should be consistent so that visiting another page from one doesn’t cause confusion.

Navigation should also be designed with mobile users in mind. Mobile devices typically have smaller screens and fewer interactive elements than desktop devices, so it’s crucial to design concise and easy navigation on a smaller screen. This may mean using fewer navigation elements and more concise labels.

Use Simple Visual Design

Learnability in web design largely depends on its visual simplicity. It implies using few interface components such as minimalistic color scheme or fonts minimizing content complexity and promoting an explicit hierarchy of information structure. A simple visual design assists users to swiftly interpret the goals of a page; locate the right information; and move about without difficulty inside the site.

The structure and hierarchy of content are also pertinent. Every page must have a clear purpose and be easy to navigate. This will therefore require that the navigation is uniform all through the site and there must be pages arranged in hierarchical manner and sections followed by it. Labels should be self-explanatory, pages should follow one another in a logical way.

Make sure that your page content can be understood by users by keeping it concise and well organized. Split the text into headings and subheadings, while images or other visuals should only help underline key concepts.

This makes it easier for users to understand web designs that use simple visual design as well as those that concentrate on structure and hierarchy. In this way, they can quickly find what they are looking for without getting lost or confused during their search.

Use familiar interaction patterns

One of the most significant things about web design is “learnability” which refers to how easy it is for people to learn how to use a website. Designers should thus ensure that they apply familiar interaction patterns so that users can quickly learn how to use websites. By applying familiar interaction patterns, users may recognize the design elements and know how they function accordingly.

Commonly used elements in web design make up these kinds of mutual interaction routines. Examples include navigation menus, buttons as well as forms. Users will identify them from other sites which they have been using because they are using these types of templates hence would know exactly how to go about using them within an instant but designers may also utilize various visual indications like arrows or icons pointing at these components.

Using familiar interaction patterns is also helpful in reducing confusion among users. These already familiar elements help the user avoid having them start understanding from scratch on-site workings; instead directing focus onto site’s content thereby facilitating faster browsing experiences.

User Testing To Measure Learnability

Learnability is an important element when it comes to web design; hence user testing cannot be avoided here. By observing and recording the behavior of real users as they interact with a website or app, user testing provides valuable insights into how easy it is to use a web design and how users interact with it. That’s why we need to have this data in order to identify the areas we can make better so that overall experience may be easier for all.

Selecting adequate methods for user testing is essential for your web-design project. A variety of options including A/B testing, usability testing, and focus groups are available. Each has its own pros and cons; hence you should consider which one could fit your project better.

User Testing aims at identifying where improvements are needed by understanding how users engage with the design. Thus, effective measurement of right metrics accompanied by relevant questions are necessary.

Always look out for patterns when sorting through user data from tests. If similar problems appear regularly, then an upgrade to the design may be required. Also check if the data shows that the user was able to reach their goal.

Informed decisions about web design can only be made with data from user testing. Still other research methods need to be used even though user-testing produces useful information on how easily a person can navigate a website. User test results should give more insight into feedback and analytics therefore enhance our knowledge of customer behavior.

Conclusion

Web design must be learnable. While designing for the web, it is crucial to consider how quickly a user can learn your website or app. In this regard, user testing helps designers to determine how easily people can learn how to use websites.

Thus, the most effective web design agencies will make website designs that users will find easy to comprehend by utilizing familiar interaction patterns, arranging content in a logical manner and performing user testing. This allows users to get the information they need without being disoriented or bewildered as a result. Hence, knowing learnability is crucial in creating a successful web design.

The post Understanding Learnability for Web Design: Tips and Best Practices appeared first on DM Onzon.

Real Estate Technology Trends

Several technology trends are modernizing real estate in 2023. PropTech startups are introducing solutions spanning property management, investments, transactions and more. These innovations are increasing efficiency, transparency and convenience across the real estate ecosystem.

Specific technologies like artificial intelligence, augmented reality and big data analytics are enabling brokers to tap into insightful market trends. Immersive 3D virtual property tours are becoming popular to remotely view homes, while digital transaction management is accelerating closings.

Blockchain platforms also offer decentralized, transparent property exchanges. Meanwhile, digital concierge mobile apps facilitate broker-client communications.

Such exponential technology growth is expected to continue disrupting real estate business models in 2024. The top trends include hyperautomation, cloud enablement, AI augmentation and tokenization of assets via blockchain.

Programming Innovations in Commission Advance Systems

Amidst the PropTech boom, commission advance solutions specifically are undergoing major programming upgrades. Commission advance systems allow real estate agents and brokers to receive a part of their commission early before the actual closing. This provides vital cash flow between listings and sales completion.

Programming innovations are now allowing seamless integration of commission advance platforms with existing brokerage systems. Automated data tracking and transfers eliminate manual work for brokers to send listing data. AI algorithms also enable customized advance amount recommendations based on predictive sales closure timing.

Smart contracts further streamline commission release workflows on blockchain. One key benefit is decentralized commission tracking that provides transparent system audit trails. Overall, these advancements are significantly improving user experience and efficiency.

For brokers and agents, a major advantage is instant access to commission liquidity. Instead of waiting for the entire sales cycle to complete, they can now utilize up to 80% of their estimated commissions instantly. This aids business continuity between listings and sales closure, especially helpful amidst market uncertainties.

Programming innovations also enable optimized advance amount calculation aligned with closing timelines. For developers, fractionalized commission monetization unlocks new recurring revenue streams.

Challenges and Opportunities

However, some risks remain around data privacy, security and integration with existing tools. Education is also needed for wider adoption across brokerages and agents less familiar with commission advance mechanisms. Compliance with state real estate regulations is another key consideration during technology buildouts.

But overall, programming innovations open up many new opportunities. Those embracing commissión advance systems early can gain a strategic edge. Firstly, offering flexible, tech-enabled commission liquidity options attracts top real estate talent. This subsequently drives more listings and sales.

Secondly, faster access to capital means brokers can easily scale their business despite market fluctuations. Overall by adopting the latest commission advance platforms, real estate professionals can accelerate growth while future-proofing their operations.

Conclusion

In conclusion, the real estate sector is undergoing immense technology-led transformation. For commission advance systems specifically, programming upgrades like automation, blockchain and AI are enabling step change improvements in efficiency.

While some challenges exist, innovation in commission advance mechanisms presents huge opportunities for the industry. Real estate brokers, agents and developers must proactively embrace these emerging technologies for sustaining their competitive edge and scaling success.

The post The Future of Real Estate: Programming Innovations in Commission Advance Systems appeared first on DM Onzon.

There are a huge amount of frameworks and methodologies that are used in the software development process, including Agile, Scrum, Kanban, and other approaches. While each of them has its own advantages, the only thing that can really make your product a success is competent execution. 

In this article, we will dive deep into risk management in software development and discuss the most common risks and the ways to avoid them. 

Success criteria

Let’s start, however, with traits that make the product a success:

• launched on time
• within the limits of a budget
• little to no bugs and crashes
• functions as intended
• popular among end-users
• solves specific business goals
• meets the stakeholders’ requirements
• delivers tangible business value

The reality is, that not all of those criteria are usually met, and you need to be prepared for the scenario when something goes wrong. Hopefully, this article will help. 

What can go wrong during the custom software development process and what you can do about it

Risk 1: Low expertise of contractors

Finding a development partner can be confusing because everybody promises a full development cycle and turnkey services.

For example, having decided to digitize part of the business, the company turns to a web studio (aka digital agency/web integrator). The service takes place in the format of one window, where they are asked to fill out a brief, and then, based on it, they come up with technical requirements. If the system is complex and requires experienced programmers, then the development is given to outsourcing production.

The subcontractor is required to perform work on poorly created technical requirements. If the product lives up to the release, it often turns out that it does not solve the company’s problems, and no one wants to use it.

This is a market problem – the contractor inadequately assesses its own strengths, makes the wrong decisions, and, as a result, does not help in any way.

How to avoid it

First, you need to find trusted partners with good reviews and proven experience with successfully completed projects, preferably in your industry. After that, communication is key. Make sure that your development partner is ready to make business trips and open to communicating with stakeholders, end users, and developers that are involved in the process. 

While creating technical specifications and requirements, the experts must not only describe the elements of the interface but also understand the complex integrations and algorithms that are hidden behind visual elements.

Risk 2: Exceeding the budget before the release of the product

The software development services market is dominated by fixed budgets and postpaid. Therefore, accounts and sales departments try to agree on an estimate and conclude an agreement as soon as possible. If the web studio incorrectly compiled the design, carried out an incomplete assessment, and attracted a subcontractor for development, then production hell can happen.

The volume of work will increase, and the general contractor will begin to protect its interests and push performance to meet the budget. This process harms the performance of both the client and the contractor. 

These political wars are hidden from the client. The client has no idea how many links are in the chain, and how the development process goes – the partners of the web studio signed an NDA. As a result, the developer sacrifices the quality of the product to avoid ending up with a financial loss, and the web studio only thinks about how to sign the acts and get paid as soon as possible. Nobody cares about the quality level of the product.

How to avoid it

When coming up with estimates, web studios are limited only to the general stages of work: analytics, design, layout, and programming. While a competent performer will add to the estimate of all the functional elements of the system being developed.

It is impossible to estimate the amount of work on the digital transformation of a business based on a five-minute conversation. Therefore, the work with the estimates requires several stages, and without analytics, it will not be possible to get the final cost of design and development.

Risk 3: Changes in the project during the development

The development of an integrated information system, on average, takes at least a year. During this time, anything can happen.

It may happen that in the middle of the journey the client changes the way the business is done, or better technologies are introduced, or maybe something just changed in the world.

For example, the IT vendor is developing a courier delivery system, but the market changed due to the political situation. Significant aggregators reduced the commissions, and the product no longer solves the previously set goals. In such a scenario, it is absolutely normal if the customer starts changing tasks without waiting for the development to be completed.

How to avoid it

If the customer proposes to change something, then firstly you should figure out the reasons, and start an open conversation in order to understand the details.

Only after that, evaluate these changes, and try to foresee the associated risks, including budget overruns. Then find the best approach to implement these changes and propose it to the client. 

Risk 4: Loss of interest from the owner

When something changes in the world, the customer can get carried away with another line of business, and forget about the current project. The loss of interest leads to the fact that the performer is either asked to completely stop the work or, worse, to leave it in limbo. Waiting for a decision leads to team downtime and overhead expenses.

But more often interest disappears when there are serious changes in the organizational structure on the side of the customer, and people change on the project. As a rule, these people are not aware of the full context, and therefore do not see the value in the development. 

How to avoid it

To keep the owner interested, the vendor should show intermediate results. Large systems usually consist of a set of services, so as a result of each iteration of development, the fully completed functionality of a single service that can already be used should be demonstrated. So the client sees that the product solves the business problems.

Risk 5: The client does not have enough time for participation

Employees on the client side do not provide the necessary information, and the manager responds with significant delays, slowing down the entire process. At the same time, the solution is being actively developed, interest has not been lost, and the deadlines are still on.

Unfortunately, this happens often. In this case, an inexperienced developer will begin to take offense, lower priorities for tasks, and eventually switch the entire team to another project. The logic of the developer is clear here, no one wants downtime due to unreasonably long approvals. This leads to damaged relationships and not finishing the project.

How to avoid it

It will be a good idea to set responsible persons on the clients side and make an agreement on the degree of their involvement throughout an entire development process. 

Risk 6: Unnecessary adjustments and improvements

The client is not always competent enough to assess the degree of readiness of the software, and this is fine. It is much worse when the developer does not understand whether the solution is ready. The launch is often delayed due to unreasonable edits.

This situation happens due to the fact that edits are proposed by those who are not responsible for the final result, unqualified people who have an incomplete context. 

An inexperienced contractor will either endlessly question these changes in order not to make them at his own expense, or vice versa, take into account absolutely all the comments. 

How to avoid it

If comments come from a person who is not responsible, then it is better to record them and discuss with those who are directly responsible. Before making any changes, it is important to understand how these changes will influence the overall goals, deadlines and the budget. 

Risk 7: Infrastructure not ready for launch

The fact that the infrastructure is not ready on the client side, legal nuances are not formalized, and there are no partnership agreements can also delay or stop the launch from happening. 

For example, a system is designed to run on SSD drives, but the current infrastructure uses an HDD, or a business is launching a new line that has not yet received approval from a government agency.

The vendor in this situation sometimes continues to work, ignoring the problems. Because it is comfortable not to go beyond his area of ​​responsibility. Formally, the vendor does the right thing, the problem is on the client’s side. But what is the use of a product that will be impossible to launch?

How to avoid it

Communication is once again is the solution here. It is important to talk openly about all possible blockers for the release on both sides. 

Conclusion

All risks are connected in one way or another. A specific problem not fixed in time can cause a snowball effect. But as experience shows, there are three universal ways to prevent and minimize the consequences of risks:

• Avoiding potential risks
• Having an action plan to fix the consequences if something happens
• Willingness to change the development course and search for alternative solutions

The post 7 Key Reasons Why Web Projects Don’t Get Completed appeared first on DM Onzon.

dbForge SQL Tools

SQL Tools is a great development tool for anyone who works with SQL Server or SQL Azure. It includes features for many different scenarios, such as database schema design, SQL queries, stored procedures, triggers, data migration, and deployment. dbForge DevOps Automation is an excellent tool that allows you to automate tasks while increasing your productivity and reducing expenses.

Pros:

Quickly write, beautify, and refactor your code while drastically increasing your productivity thanks to the IntelliSense-style SQL code completion in SSMS, a great collection of code snippets, SSMS tab coloring & document sessions, intelligent renaming of aliases and variables, advanced customizable code formatting profiles, and warning before executing code that could cause a crash.

dbForge Query Builder for SQL Server allows you to quickly and easily build complex SQL queries using a visual interface. You don’t have to write the query manually. We’ve built a new visual SQL query builder, which makes it easier to develop SQL queries for SQL Server. This graphical SQL query designer and all of its interactive query building features will be most appreciated by users who need to create various queries for databases.

With this application, you can view and decrypt the encrypted stored procedures, views, functions, and triggers without the need to connect to DAC. Save your time while decrypting database objects. Use syntax highlighting to view DDL scripts of stored routines, use Unicode support, and take advantage of decryption caching, batch mode, output options, and other features to help you.

Cons:

That’s a shame, because they’re two completely separate tools. They could, however, have the ability to link up a little better, and make them even easier to use. Comparing two schemas of databases, it would be really useful to have a button to “compare data”. This launches data comparison and displays the differences.

Price:

• $1,299 for a standard license
• Or $1,299 for a professional license
• Free Trial available

Navicat for SQL Server

Navicat is an amazing MySQL database management tool that allows you to simultaneously connect to MySQL, MariaDB, MongoDB, SQL Server, Oracle, PostgreSQL, and SQLite databases from a single application. Compatible with the popular cloud database systems: Amazon RDS, Amazon Aurora, Amazon Redshift, Microsoft Azure, Oracle Cloud, and Google Cloud. You can easily build, manage and maintain your databases.

Whether you’re working from your laptop, smartphone, or any other mobile device, data transfer, data synchronization, and structure synchronization help you migrate your data, and synchronize data between devices for less overhead.

Data and Structure Synchronization is a very powerful feature in DataBase Manager that will help you to synchronize your database. Set up and deploy the comparison in seconds. Get the detailed instructions to specify the changes you want to make.

Pros:

When it comes to migrating a big and complex structure between two databases, it’s a challenge. You used to have to dump SQL files using a 3rd party utility, and then create database objects on the target DB. New version of Migrator Pro is ready to go live. Now you can connect to both simultaneously and perform all of your migration work from one tool. The latest version – 15 – added a couple of features that you have really enjoyed.

The first is Dark Mode. You have an eye condition called myopia, or short-sightedness, which causes your eyes to get tired after a few hours of bright computer screens. Using dark mode helps them focus, and having the new data visualization tool helps them make more progress. This allows you to transform my company’s data into sharp-looking visualizations so that you can better identify trends and patterns in the business. Data Analysis is the art of summarizing large amounts of data to make an educated business decision or strategy.

Cons:

Navicat Premium has probably too many features, but it’s the best tool for connecting to a MySQL database. Some products you don’t use at all. Like the Visual SQL Builder, which is used to create advanced database queries. While it’s important for beginners who aren’t very familiar with SQL to have this book, you don’t need it.

Price:

• $64.99 per month
• Or $1,299 for a perpetual license
• Free Trial available

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The company needs an experienced programmer with detailed knowledge of the RISC-V command system and the Vector Arm command system. He will join the Vector and Numerics Group (VaNG) team, which is part of the Core Operating Systems group. The Vector and Numerics Group team is responsible for developing and improving all kinds of embedded subsystems running on iOS, macOS, watchOS and tvOS.

Known for its secrecy, Apple does not say directly what solutions it intends to implement using RISC-V, but the job description states that the programmer should work with machine learning, computer vision, and natural language processing systems. Some background in low-level, high-performance programming is required, and indeed the job description itself mentions that Apple is already working with RISC-V. It’s stated explicitly that they would be working in a team which is already “using innovative RISC-V solutions.

Today, Apple has dozens of products of all kinds. For example, high-performance products like the Mac, including the MacBook, iPhone smartphones, iPad tablets and Apple TV set-top boxes use chipsets based on custom Arm Cores. In addition, devices like the Apple Watch, AirPods and Homepod Mini use Arm SiP technology, and Arm cores are also used in controllers like the T2, W3 and U1.

In addition to chipsets for high-performance devices, each Apple device uses multiple Arm cores (although individual devices still use chips based on x86 architecture). Apple pays licensing fees for the use of each core, and as the number of cores in devices like SSD controllers and smartwatches continues to increase, we have to pay more and more. In this regard, the use of open and accordingly free RISC-V architecture looks extremely attractive, it could save the company millions of dollars in royalties.

At the same time, integration of custom cores based on RISC-V architecture into Apple’s ecosystem requires software preparation and verification of hardware and software compatibility. This is where programmers familiar with both RISC-V and Arm are needed.

Considering that Apple is already working on RISC-V based solutions, it is still a matter of time before some core types are replaced by an alternative architecture. It is known that RISC-V is mostly used today for auxiliary solutions with low performance, but with the evolution of technologies we cannot rule out more interesting solutions.

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According to Qichacha analysts, China now has 439,000 registered AI-related companies. In 2020, the number of new organizations in the field of AI was 172 thousand, and in the first half of 2021 such organizations were registered another 153 thousand. Thus, the growth of registrations for the year was 150.8%, and the year is not over yet!

The transition from 2019 to 2020 showed an increase in the number of new AI companies in China at 292.8%, and 2021 promises to be even more “fruitful” for the field of AI in China.

The issue of finance is extremely interesting. Most Chinese AI companies declare quite large share capital. Apparently, local investors are willing and invest a lot of money in AI development. For example, companies with registered capital of less than 1 million yuan ($155,000) account for only 24% of the registered companies, while those with registered capital between 1 and 5 million yuan account for 39%, and those with capital over 5 million yuan (from $755,000 and more) account for 37%.

It is also interesting to note that the most AI companies in China are registered in three neighboring provinces on the southeast coast of the country: Guangdong, Jiangsu and Zhejiang. There are 64,000, 50,000 and 40,000 AI companies in each, respectively. Programmers have always been drawn to the south and to the sea, which in the case of Chinese regional development programs is further supported by subsidies for provincial economic development.

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Among the exotic programming languages for writing malware are Go (Golang), D (DLang), Nim and Rust. As a rule, these languages are used to create malicious software aimed at large organizations and which exploits weaknesses in the protection of the corporate infrastructure. We are talking about malware that implements multi-stage, carefully planned and organized cyber-attacks.

Once on the victim’s computer, these software modules bypass traditional defenses to later download, decode and launch remote access Trojans, most often Remcos and NanoCore, as well as Cobalt Strike beacons.

In some cases, when the cybercriminals have sufficient resources, non-standard languages for these purposes are used not only for the modules performing the initial attack, but also for the whole malware package. The Go language is of particular interest to attackers. It is used by hackers on an almost regular basis for all major platforms.

According to the authors of the study, new or unusual programming languages make it difficult to decompile malware, circumvent defenses that use signature-based detection tools with relative ease, and simplify cross-platform compatibility of attacks. The code base of such malware itself is an additional level of disguise. Their developers, in fact, do not have to make any additional effort; the effectiveness of the attack is increased simply by the fact that one of these programming languages is used.

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According to the developers, Codex can now significantly simplify the work of experienced programmers, as well as help to train beginners. Artificial Intelligence literally turns a stream of words into real software like websites or rudimentary games. For example, a user can describe the basic appearance of a site or its functionality by listing requirements like the location of menus or text boxes using plain spoken English, and Codex will generate a finished product based on its own “insights” into what needs to be accomplished.

In this variant, programming skills are not required at all in some cases. However, basically Codex will only work as an “assistant” or “deputy” programmer, implementing the conceptual ideas of the “creators” in the simplest way possible.

According to Greg Brockman, the technical director and co-founder of OpenAI, the new tool is intended for a wide range of programmers. First of all, it will allow them to get rid of monotonous repetitive work using libraries, functions and APIs.

Codex is based on the GPT-3 algorithm – created by OpenAI for generating “meaningful” texts based on analyzing many terabytes of text material on the Internet. However, it can provoke a negative reaction from developers who put free and open source software online. The algorithm uses additional data that was literally “shoveled” from free software repositories for subsequent analysis.

OpenAI has said it does not violate any copyright or related rights laws. Nevertheless, many people expect criticism from volunteers who created countless lines of code – the company intends to cash in on the efforts of the community, who posted their software to be parsed and used for free. So far, the programmers do not have a common or at least dominant position on the newly created tool.

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