This article showcases advanced yet user-friendly network inventory platform features that empower IT, teams, to deeply analyze asset inventory information, integrate with other systems, and customize tracking aligned to business priorities. Unlocking an inventory tool’s full potential boosts efficiency, risk management, and planning. Visit softinventive.com to explore how the right network inventory tool can transform your IT management.

Intuitive Custom Query Building

While pre-configured queries deliver common asset list reports, ad hoc business questions demand filtering device data differently. Simple checkboxes are limited, but learning query languages like SQL or dealing with rigid templates also impedes users. Custom query builders bridge the divide.

An intuitive search interface allows combining vital categories like hardware specs, software titles, location details, lease expiration dates, etc. with Boolean logic. This transforms inventory data into flexible segmented lists without coding barriers, unlike exploring raw databases. Queries are saved for reuse while new needs are quickly addressed by refining search criteria.

API and Webhook Integrations

Inventory platforms accumulate immense device data from across networks. However, security tools, service desk apps, monitoring software, and other systems also provide contextual IT insights. API and webhook integrations blend data streams for greater awareness.

Common integration examples include:

• Triggering alerts in monitoring tools when unauthorized hardware changes are logged
• Enriching ticketing system device profiles with hours of usage data
• Blocking network access for devices with prohibited apps installed
• Automating warranty claims when hardware failures are detected

No manual exporting, reformatting and uploading needed. Real-time data syncing delivers integrated efficiency.

Custom Reporting and Scheduling

Purpose-built reporting enhances inventory data visualization beyond basic tables or spreadsheets. Management requires executive dashboards with graphs summarizing hardware lifecycles, software spending trends, security risks, and operational metrics. IT teams need reports filtered by network segments, locations, and other attributes.

Custom reports incorporate:

• Branded templates and formatting
• Multiple file type exports like PDF, Excel, CSV
• Scheduled generation and role-based delivery
• Hundreds of layout and chart combinations

Automated-focused reporting provides insights for fact-based strategic decisions.

Best Practices for Unlocking Data Potential

Ensuring Success in Your Data Journey

To truly unlock the potential of network inventory data, organizations should consider the following best practices:

• Regularly Review Data Access Needs: Ensure that the right people have the right level of access to the data they need.
• Invest in Training: Educate your IT team on how to use these advanced features effectively.
• Start Small and Scale: Begin with a small project to demonstrate value, then scale your efforts based on success.

Role-Based Insights and Security

Inventory tools aggregate immense amounts of consolidated data pulled from across entire networks. These details cover a range of aspects, including infrastructure specifications, software titles, authentication credentials, usage patterns, and traffic flows. While technology generalists may run inventory scans, customized and contextually relevant dataset access aligned to specific user profiles limits unnecessary exposure.

Configurable role-based permissions allow network inventory platforms to balance utility with security by empowering insight generation without unauthorized information leakage. Key capabilities include:

Customizable User Profiles

Create identity-centric access controls through groups, teams or individual assignments to define inventory dataset visibility. This ensures users only see asset details, queries and reports applicable to their responsibilities like help desk ticketing, capacity planning, license reconciliation or other duties.

Audit Trails and Access Logs

Comprehensive activity monitoring provides visibility into which users viewed, modified or exported what inventory data and when. Reviewing access chronologies aids troubleshooting, internal investigations, and external regulatory audits while serving as a deterrent against improper data interactions.

Inventory tools that lack basic access to governance open themselves up to insider risks. Role-based permissions get relevant insights to the right teams without wholesale exposure that undermines security or compliance. Customized profiles based on principles of least privilege prevent unauthorized extraction or manipulation of confidential inventory data.

Conclusion: An Analytics Foundation

Network inventory tools collect immense asset data, but this typically gets underutilized for strategic initiatives when merely dumped into basic lists. Utilizing advanced yet user-friendly features for ad hoc queries, systems integrations, and customized reporting unlocks an analytics foundation. This foundation maximizes hardware and software value. With flexible data exploration, unlocking inventory platform potential allows technology investments to dynamically align with business objectives. This approach shifts the perspective from presenting static views of expenditures to fostering proactive asset management.

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What is Open Source Platform Development?

Open source platform development is a software development approach that involves creating and maintaining software applications and websites using open source technology. Unlike traditional software development, open source software is developed collaboratively by a community of developers who share the code and make modifications to it. It is also typically free to use and anyone can contribute to it, making it more accessible and adaptable to a wide range of users.

The popularity of open source platform development has grown in recent years, as companies recognize the benefits of using open source technologies. One of the key advantages of open source development is the ability to leverage the collective knowledge and expertise of the community, resulting in faster innovation and development. Additionally, open source software is often more secure, reliable, and customizable than proprietary software.

When planning an open source platform development project, it is important to define the project scope and objectives, as well as identify the tools, resources, and expertise required for successful implementation. Some of the best open source platform development tools, courses, and services include GitHub, GitLab, Apache Maven, and Udacity’s Open Source courses, among others.

Open Source Platform Development Strategy

When developing an open source platform, having a well-defined strategy is crucial. Firstly, creating a roadmap of the project that outlines the goals, timeline, and tasks required to complete it is essential. Additionally, a list of the technologies and tools that will be used in the project should be created.

It is also important to have a plan for project management. This should include the roles and responsibilities of each team member, how tasks will be assigned and tracked, and how communication will be handled. Furthermore, a plan for testing and deploying the code should also be created.

Open Source Platform Development Tips

When developing an open source platform, there are a few tips that can help to ensure a successful project. Firstly, you should ensure that the project is well-documented. This includes the goals of the project, the timeline, the team members, and the tasks that need to be completed. Additionally, you should create a plan for how the project will be managed and how communication will be handled.

You should also create a plan for how the code will be tested and deployed. Additionally, you should ensure that the project is well-structured, with clearly defined roles and responsibilities for each team member. Finally, you should ensure that the project is well-tested, to ensure that any potential issues are identified and addressed quickly.

The Best Open Source Platform Development Tools

When developing an open source platform, there are several tools that can be used to streamline the process. Here are some of the best open source platform development tools:

GitHub: GitHub is a widely used platform for hosting and managing open source projects. It offers a wide range of tools for version control, collaboration, and project management.

Bitbucket: Bitbucket is a cloud-based source code repository and version control system. It provides tools for collaboration, code review, and project management.

Jenkins: Jenkins is an open source automation server that can be used to automate building, testing, and deployment of software applications.

Docker: Docker is an open source container platform that can be used to package, deploy, and run applications.

Puppet: Puppet is an open source configuration management tool that can be used to automate system administration tasks.

Courses for Open Source Platform Development

The open source platform development process can be complex and challenging. To help make the process easier, there are a number of courses available for those interested in learning more about open source platform development. Here are some of the best courses for open source platform development:

Open Source Platform Development Services

If you don’t have the necessary time or resources to develop an open source platform on your own, there are several companies offering open source platform development services. These companies can assist in creating an open source platform from start to finish. Here are some of the best open source platform development services available:

DevOps: DevOps is a cloud-based open source platform development service that offers tools for version control, collaboration, and project management.

CloudBees: CloudBees is an open source platform development service that provides tools for collaboration, code review, and project management.

Zendesk: Zendesk is a cloud-based open source platform development service that provides tools for automated testing, deployment, and system administration tasks.

GitHub Actions: GitHub Actions is an open source platform development service that provides tools for automating the building, testing, and deployment of software applications.

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What is FinOps?

FinOps is an approach to managing financial operations that focuses on finding ways to maximize efficiency and cost savings while maintaining accuracy. The idea is to use a combination of financial best practices, processes, and technologies to streamline financial operations and improve financial performance. FinOps is a holistic approach to financial management that requires a comprehensive view of the organization’s financial operations.

FinOps is a process that involves the use of data to analyze financial operations, identify areas of improvement, develop strategies to address those areas, and implement new processes and technologies to improve financial operations. FinOps is not just about cost reduction; it is about making data-driven decisions that will ultimately improve financial performance.

The goal of FinOps is to provide businesses with the insights they need to make better decisions about their financial operations. This includes understanding where money is being spent and how it is being used, as well as insights into customer behavior and trends. FinOps enables businesses to become more agile and responsive to customer needs.

Benefits of FinOps

FinOps can offer numerous benefits to businesses, including improved financial performance, cost savings, and improved customer experience. FinOps can help businesses reduce their costs by streamlining financial operations and eliminating redundant processes. It can also help businesses improve their financial performance by providing insights into customer behavior and trends, allowing businesses to make better decisions about their financial operations.

FinOps can help businesses improve their customer experience by providing insights into customer behavior and preferences. This can allow businesses to tailor their services and products to meet the needs of their customers. It can also help businesses develop effective marketing strategies to better reach their target audience.

FinOps can also help businesses reduce risk by providing insights into financial risks and opportunities. This can help businesses identify potential risks and develop strategies to mitigate them. FinOps can also provide businesses with the tools and resources they need to manage their finances more effectively.

FinOps Strategies

In order to effectively implement FinOps, businesses need to develop a comprehensive strategy. This strategy should include the following components:

• Identifying areas of improvement: Identifying areas of improvement in financial operations is essential to developing an effective FinOps strategy. This includes analyzing financial data and identifying areas of inefficiency or areas that can be improved upon.
• Developing strategies to address areas of improvement: Once areas of improvement have been identified, businesses need to develop strategies to address these areas. This could include implementing new processes or technologies to improve financial operations or streamlining existing processes.
• Setting objectives: Setting objectives is essential for tracking progress and measuring success. Objectives should be measurable and achievable, and should be tailored to the specific financial goals of the business.
• Implementing the strategy: Once a strategy has been developed, businesses need to implement it. This includes training staff on new processes, implementing new technologies, and monitoring progress.
• Evaluating progress: Evaluating progress is essential for assessing the success of the strategy. This includes monitoring KPIs and other metrics to ensure the strategy is achieving its desired results.

FinOps Best Practices

In order to effectively implement FinOps, businesses need to adhere to certain best practices. These best practices include:

• Automating processes: Automation is essential for streamlining financial operations and improving efficiency. Automating processes can reduce manual errors and save time, allowing businesses to focus on more strategic tasks.
• Leveraging data: Leveraging data is essential for making informed decisions. Data can provide insights into customer behavior and trends, as well as areas of inefficiency.
• Utilizing technology: Utilizing technology can help businesses streamline financial operations and automate processes. Technologies such as cloud computing, artificial intelligence, and machine learning can help businesses reduce costs and improve efficiency.
• Adopting agile principles: Adopting agile principles can help businesses become more responsive to customer needs. Agile principles emphasize flexibility and quick response times, which can help businesses provide better customer experiences.
• Establishing KPIs: Establishing KPIs is essential for measuring the success of a FinOps strategy. KPIs should be tailored to the specific financial goals of the business and should be monitored regularly.

FinOps Technology

Technology plays an essential role in FinOps. Technologies such as cloud computing, artificial intelligence, and machine learning can help businesses streamline their financial operations and automate processes. These technologies can also provide insights into customer behavior and trends, which can help businesses make better decisions about their financial operations.

Cloud computing is particularly beneficial for businesses implementing FinOps. Cloud computing allows businesses to store and access their data from any device, which makes it easier to share and access data across multiple locations. It also provides businesses with the ability to scale their operations as needed.

Artificial intelligence and machine learning can also be used to automate processes and provide insights into customer behavior and trends. These technologies can help businesses make better decisions about their financial operations by providing data-driven insights.

FinOps Processes

FinOps processes are the steps that businesses need to take to implement FinOps. These processes include identifying areas of improvement, developing strategies to address those areas, and implementing new processes and technologies to improve financial operations.

In order to develop an effective FinOps process, businesses need to understand their financial operations. This includes analyzing financial data, understanding customer behavior and trends, and identifying areas of improvement. Once this information is gathered, businesses need to develop strategies to address those areas, such as implementing new processes or technologies.

Once strategies have been developed, businesses need to implement them. This includes training staff on new processes, implementing new technologies, and monitoring progress. The final step is to evaluate progress and measure success. This includes monitoring KPIs and other metrics to ensure the strategy is achieving its desired results.

FinOps KPIs

KPIs are essential for measuring the success of a FinOps strategy. KPIs should be tailored to the specific financial goals of the business and should be monitored regularly. Common FinOps KPIs include customer retention rate, cost savings, revenue growth, and cost per acquisition.

Customer retention rate is a key metric for measuring the success of a FinOps strategy. It measures how successful a business has been at retaining customers over time. Cost savings is another important metric. It measures how much money a business has saved by implementing a FinOps strategy.

Revenue growth is another key metric. It measures how much a business has increased its revenue since implementing a FinOps strategy. Cost per acquisition is also an important metric. It measures how much money a business is spending to acquire new customers.

FinOps Automation

FinOps automation is the use of technology to automate financial operations. Automation can help businesses streamline financial operations and reduce costs. Automation can also help businesses improve their customer experience by providing insights into customer behavior.

FinOps automation can take many forms, including the use of cloud computing, artificial intelligence, and machine learning. Cloud computing allows businesses to store and access their data from any device, which makes it easier to share and access data across multiple locations. Artificial intelligence and machine learning can be used to automate processes and provide insights into customer behavior and trends.

FinOps Success Stories

FinOps is a powerful tool that can provide businesses with numerous benefits. There are many success stories of businesses that have implemented FinOps and seen significant improvements in their financial performance.

One such success story is that of an insurance company that implemented a FinOps strategy to streamline its financial operations. The company was able to reduce costs by 20%, significantly improve customer experience, and increase revenue by 25%.

Another success story is that of a retail company that implemented a FinOps strategy to improve its financial operations. The company was able to reduce costs by 15%, increase customer retention by 10%, and increase revenue by 20%.

Conclusion

FinOps is a powerful tool for businesses looking to maximize their financial performance. By leveraging data, utilizing technology, and automating processes, businesses can streamline their financial operations and reduce costs. FinOps can also provide businesses with insights into customer behavior and trends, allowing them to better meet customer needs. The success stories outlined above demonstrate the power of FinOps and its potential to transform businesses.

For businesses looking to unlock the power of FinOps, it is important to develop a comprehensive strategy that includes identifying areas of improvement, setting objectives, implementing the strategy, and evaluating progress. Additionally, businesses should adhere to certain best practices, such as leveraging data and utilizing technology, in order to effectively implement FinOps. By following these best practices, businesses can unlock the power of FinOps and improve their financial performance.

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The first computers were programmed by switching switches and reconfiguring equipment. As a result, the early programmers had to be intimately familiar with computer hardware. But we’ve come a long way, and high-level programming languages require little or no familiarity with basic hardware.

Up until recently, corporate directors could bring laptops or tablets to board meetings (or, with larger firms, have assistants with these devices sitting behind them) to use as research tools if the need arose. The key word here is “tools”-the devices were used to gather information so that the director could speak intelligently or vote on a particular topic-the computer system could even make a recommendation for action to be taken, but the technology has always been subservient to the director, who can ignore the data gathered or the recommendations of so-called “artificial intelligence.”

AI as decision makers
Well, the game has just changed! As Rob Wile wrote in Business Insider in 2014 in an article titled “Venture Capital Firm Just Named Algorithm to Its Board of Directors – Here’s What It Really Does,” the computer analysis system was named an equal, not a tool, to the Board of Directors. Wile writes, “Deep Knowledge Ventures, a firm that works on drug projects for age-related diseases and regenerative medicine, says a program called VITAL can make investment recommendations for life sciences companies by analyzing large amounts of data…. How Does the Algorithm Work? VITAL makes its decisions by scanning future company funding, clinical trials, intellectual property and previous funding rounds.” The real trump card in this story is that VITAL is a voting member of the Board with as much weight as any other member.

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Application programming usually involves issuing system commands to use basic functions of the computer’s hardware and operating system, such as saving a certain piece of data in the computer’s physical memory or a file on the hard drive. Programs of this type have nothing to do with the details of hard disk or physical memory operation. Conversely, system programmers care about the details of the operating system and hardware components. This allows them to create software that defragments hard disks and checks the integrity of the computer’s physical memory.

In addition to their ability to create such tools, systems programmers are usually experts in the basic functioning of operating systems. All programmers are familiar with system calls, thread management, and I/O processing, but system programming requires the software engineer to be able to manipulate these operating system mechanisms. This allows the system programmer to perform specialized settings and automate system maintenance tasks.

Knowledge of the operating system kernel is also necessary to maximize application performance on a particular hardware configuration. For example, very busy online retailers need their websites and transaction processing systems to run as efficiently and reliably as possible. Using their knowledge of the internal mechanics of operating systems and hardware components, such as how to make a particular operating system optimize thread processing or which algorithms run faster on which hardware components, a systems programmer can help fine tune application performance.

This detailed access to the inner workings of hardware components and the operating system requires that system programming be done in a language that provides this type of low-level hardware access. Languages such as Java, Python, or Ruby on Rails are what programmers call high-level languages. This means that they make it easier to program applications without allowing the programmer to handle the fine details of hardware control. System programming requires exactly this kind of access, so system programmers use a low-level language such as C or C ++.

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Most often system programs are developed in the low-level Assembler programming language, which can be specific to a particular computer architecture and CPU. Modern high-level languages also have the ability to write system program code. For example, the C language allows the use of assembly inserts in the program text or the connection of assembly language subprograms to the program text.

Classification of system programs
The system software is usually arranged as the function libraries which can be attached to the created application programs.

System programs can be roughly divided into the following categories:
operating systems;
drivers;
service programs for equipment maintenance; diagnostic tools; software tools which ensure automation of application programming development.

The operating system is a set of interconnected programs designed to manage the computer resources, taking into account the microarchitecture of the computer system devices and providing the user with the necessary set of functions in the form of libraries.

Drivers are software components that are used by the devices of a computer system (processor, memory, video card, keyboard, external plug-in devices) to interact with the operating system. Drivers are usually developed by hardware manufacturers for different operating systems and are sold as an integral part of those tools. They mediate between the computer hardware devices and the operating system, ensuring the transfer of data between them.

Thus, one can imagine the following communication scheme: if the programmer who develops an application program needs to transfer data into computer memory or save a file to the hard disk he refers to the corresponding function from the operating system library, which in turn refers to the driver of the device used in this operation.

Service programs for equipment maintenance allow you to optimize the operation of hardware for more efficient use. For example, as a result of multiple file writes and overwrites, a hard disk becomes fragmented over time, i.e. parts of a single file become scattered in random order, which greatly slows down the writing and reading of these files. Disk defragmentation service program allows you to arrange the files in an orderly manner, which greatly speeds up the work with them.

The registry of your operating system over time, due to malfunctions, incorrect program termination or removal of unwanted programs, accumulates “garbage” or unnecessary links. The registry cleaner cleans it from unnecessary data, thereby increasing the operating system’s performance.

Diagnostic tools allow you to check the health of hardware resources, detect and correct failures. This helps the application programmer to make sure that his program does not work because of a hardware failure and not because of incorrectly written code.

Software tools that automate the development of application programming are translators, debuggers, linkers, resource editors, and others. These programs also relate to the system ones for they are developed taking into consideration the architecture of hardware resources and peculiarities of the computer’s operation system. Applying such tools in practice, application program developers can use universal high-level programming languages, and when compiling the program into executable file the peculiarities of computing architecture will be taken into account automatically by the compiler.

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Nowadays, some use has been found for embedded C++. The implementation of the main parts in the operating system and in the use of networks needs system software developers. For example, the implementation of pagination (via virtual memory) or device drivers.

The term System Programming is directly related to the term System Programmer. It is a programmer who works (creating, debugging, diagnosing, etc.) on system software.

System programming is a kind of activity that consists of working on system software. The main difference between system programming and application programming is that the result of the latter is the release of software offering certain services to users (such as a word processor). while the result of system programming is the release of software offering services to interact with hardware (such as defragmentation of hard disk), which implies a strong dependence of such programs on the hardware hour In particular, let us highlight the following:

• the programmer must take into account the specific hardware and other properties of the system in which the program functions, to use these properties, for example, by applying an algorithm specially optimized for this architecture.
• Usually a low-level programming language or such dialect of a programming language is used that
• allows to function in an environment with a limited set of system resources
• runs as efficiently as possible and has a minimal termination time lag
• has a small or no runtime library (RTL)
• allows direct control (direct access) to memory and controlling logic.
• allows making assembler inserts into the code
• program debugging can be difficult when it is impossible to run it in a debugger due to resource limitations, so computer simulation can be used to solve this problem.

System programming differs significantly from application programming, which usually leads to specialization of a programmer in one of them.

Often, a limited set of tools is available for system programming. The use of automatic garbage collection is quite rare and debugging is usually difficult. The runtime library, if available, is often less capable and performs fewer checks. Because of these limitations, it is usually used in monitoring and recording data – operating systems.

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