User interface: the key factor in interacting with software and applications

The more complex technology becomes, so do our needs. Two of the essential needs we seek, especially when it comes to business processes, are speed and efficiency. While we meet the need for speed and efficiency, we have realized that there is also another need: entertainment. We want to be entertained, to have interaction during our engagements. The user interface fills that void since our lives have been inundated by digitization. We may not realize how common and crucial its functions are. One thing is for sure: user interfaces make our lives much easier. In this blog, we have discussed the topic of user interfaces with a very basic approach, as this topic can easily become very detailed and technical.

What is user interface?

The term is self-explanatory: user interface (UI) is a tool/object that helps people interact and operate more efficiently and easily. In other words, it enables human interactions to occur with computers, software, applications and websites. There are two aspects that occur when humans begin to interact with the user interface: the ability to command efficiently and easily and to receive instant feedback that aids the decision making process for the operating human.

User interfaces are created with multiple layers, with the goal of appealing to users’ senses, such as touch, sight and hearing. These layers help humans expend as little effort as possible to achieve the expected results when interacting with it. Layers are supported by various devices to increase and facilitate the level of interaction, such as keyboard, mouse, microphone, touch screen, camera and many more.

Why is it important to have user interfaces?

In addition to facilitating and increasing the efficiency of human interaction, user interfaces play a key role in terms of the functionality of computers, software, applications or websites. Functionality is often measured by the speed and responsiveness of the user interface. It is also important to consider the user experience when designing and focusing on the functionality of user interfaces.

Below, we highlight important components of user interfaces. These components provide valuable information about the goals of user interfaces. However, user interfaces, in most cases today, contain multiple components.

Information architecture: Its goal is to provide an easy process, bringing out the most important information with minimum effort for the user. Information architectures can be built in hierarchical, sequential or matrix form. They also include tooltips, icons, progress bar, notifications, message boxes and modal windows.

Visual design: When it comes to visual design, color, contrast, typeface and video play a crucial role in maximizing user appeal. While the goal is to create the attraction, it is also considered mission critical to make the user continue the interaction as much as possible.

Input design: These controls allow users to interact with computers, software, applications and websites to complete the desired action. They include check boxes, radio buttons, drop-down lists, list boxes, buttons, toggle buttons, text fields and date fields.

Navigation components: As you can understand, they are placed in order to provide easy and efficient navigation for the user to interact with. Breadcrumb, slider, search field, pagination, slider, labels and icons are common examples.

User interface on the IDboxRT platform:

The IDboxRT platform is based on state-of-the-art technology and the latest IT security implementations with the ultimate goal of bringing efficiency, security and ease to your production.

Our platform is the ideal place to view, control, compare and analyze everything related to your business processes. We provide all the necessary information with an in-depth view. Moreover, the in-depth view is applied for each component level.

IDboxRT is a platform in constant development and evolution. Depending on the specific needs of the company, the platform can be adapted to the configuration of the operation.

Please contact us for more information on the updates from the IDboxRT team of experts.

The 3 technology trends that will transform the world

What distinguishes the fourth industrial revolution from previous ones is the convergence and interaction of several technological trends at the same time. Here are some of the main technological trends that that will permanently change our businesses and our lives.

Trend 1: Everything connected and smart

You’re no doubt familiar with the Internet of Things (IoT). IoT refers to the growing number of smart, connected devices and objects capable of collecting and transmitting data.

In the future, everything that can be connected will be connected. Not just devices and products – although this is certainly a key factor for businesses – but also the spaces in which we live and work. From smart, connected factories and offices to entire smart cities, the spaces around us will be increasingly equipped to track what is happening and act accordingly.

Trend 2: The datification of the world

Ubiquitous computing and IoT are bringing huge amounts of data being generated every day. But along with this machine-generated data, we humans also generate an enormous amount of data during our daily activities, a process that shows no signs of slowing down.

The good news is that companies can use this data to develop better products and services, improve business processes, make decisions and even create new revenue streams. However, companies also need to be aware of the risks associated with data, particularly data privacy and security.

Trend 3: Artificial Intelligence (AI)

All the data generated is an important tool for artificial intelligence, which has taken an incredible leap forward in recent years.

The result for businesses is that, as our interactions with machines become increasingly intelligent, customers will expect all types of products and services to have some form of AI capability.

Now, following all of these trends, we understand that we are entering an era of rapid and continuous evolution, where multiple technology trends combine and feed into each other to produce major changes. For businesses, this means that the days of incremental technology upgrades are gone forever. Continuous change is the way of the future.

If you want to know more about how technologies can improve your business processes, contact us and our best experts will inform you.

Web 3.0: What is it and how does it differ from Web 2.0?

What is Web 3.0?

Although Web 2.0 may seem like an advanced approach to the Internet, it still has many drawbacks. What about the security of your personal data? With Web 2.0, trusted institutions take control of user data, especially because of the need for trusted intermediaries. If two parties want to make a transaction but do not know and trust each other, they will have to resort to the services of trusted intermediaries. However, the intermediary has control over the storage and management of the data, thereby increasing its power over the users. In addition, centralized power has never led to success in times of crisis, which requires decentralization.

Web 3.0 is a promising improvement over Web 2.0, especially given the major transformations in terms of infrastructure. The third generation of the Web, also called the semantic Web, uses an improved metadata system. The metadata system helps structure and organize all types of data, making them readable for humans and machines. The main benefit associated with Web 3.0 is almost the best twist on the differences between Web 2.0 and Web 3.0. Web 3.0 eliminates the need for centralized intermediaries and introduces the universality of information.

How revolutionary is Web 3.0?


Understanding the comparison between Web 2.0 and Web 3.0 should also focus on the uniqueness of Web 3.0. The third iteration of the Web is a formidable response to Web 2.0’s shortcomings with an emphasis on innovative technology. Web 3.0 uses artificial intelligence to enable machine-to-machine interaction as well as advanced analytics. In addition, Web 3.0 uses a decentralized network to bring data under the control of the owners. As a result, users are able to own their data as well as determine how it is distributed. In addition, the differences between Web 2.0 and Web 3.0 are improvements in user privacy and security. Web 3.0 uses encryption and distributed ledger technology to address trust issues that were evident in Web 2.0.

Notable features of Web 3.0


You can build a stronger foundation for understanding “What’s the difference between Web 2.0 and Web 3.0?” by focusing on Web 3.0 features. Here are some of the most important features of Web 3.0 that will help distinguish it from Web 2.0.

  • Web 3.0 uses artificial intelligence to deliver the right results at a faster pace along with access to real-time information.
  • Web 3.0 also allows users to tap into the potential of 3D images and graphics.
  • Web 3.0 has a Semantic Web functionality. This means that Web 3.0 can support understanding the meaning of words. As a result, machines and people can easily find, share and analyze information on Web 3.0.
  • Web 3.0 also offers important features such as improved privacy and security.
  • Web 3.0 uses improved authorization mechanisms using distributed ledger technology and encryption to protect user identity and data.

If you want to learn all about how Web 3.0 and related technologies can improve your business processes, contact us and our top experts will inform you!

What is the best way to successfully define, scale and lead Digital Transformation?

DEFINE A CLEAR DIGITAL STRATEGY
Planning a company’s digital transformation from the outset involves being able to see the big picture. You also need to be clear about your desired outcomes. Define your objectives from the outset. Decide what you want to achieve and make sure you understand why the organization needs to transform. Depending on your current and planned methods of operation, the following may be decisive factors:

  • Reduced supply costs
  • Increased sales volume
  • Reducing waste or duplication
  • Increasing profits
  • Attracting new customers
  • Catching up with or surpassing competitors
  • Implement new technologies

In summary, start by assessing the current state of your business. Consider the requirements of your employees and systems, as well as potential areas for improvement.

CALCULATING ROI BEFORE STARTING IOT PROJECTS
A digital transformation should include an assessment of how much the proposed technology will drive revenue growth. A return on investment (ROI) calculation provides a feasibility check prior to

SELECTIVE TECHNOLOGY INVESTMENT
Choosing the right tools and technology is critical. There are many digital transformation trends being discussed in the marketplace, but technology must serve the business, not the other way around. Choosing the best strategy for the IoT journey remains a challenge. Before deciding on an expensive IoT implementation and choosing the direction of your journey, examine your options and seek advice on choosing the best technology and systems for your business.

IT/OT INTEGRATION FOR IOT SOLUTIONS
Integrating information technology (IT) and operational technology (OT) is no easy task, but with the right approach, it can deliver unprecedented growth. By implementing the right IoT solutions, you can successfully bridge the gap and create an intelligent, interconnected foundation to improve business processes and add value to your data. By integrating IT and OT systems, you can unlock the power of your data to generate accurate predictions and make informed decisions.

To ensure that your digital transformation efforts do not stall, it is important to have a trusted partner to guide you on your digital transformation journey. Each digital journey is individual and should be tailored to the client’s needs.

By checking off the different aspects of this list, you will be on your way to a successful digital transformation. If you would like to discuss digital transformation readiness in more detail, please contact us and we will put you in touch with our experts.

WHAT IS INDUSTRIAL ARTIFICIAL INTELLIGENCE?

INTRO

Although Artificial Intelligence (AI) technologies began to be developed several decades ago, several definitions currently coexist that include concepts such as Big Data, data science, machine learning or IoT.

AI is defined as a set of tools and methodologies that allow machines to simulate processes and develop tasks that require applying human intelligence such as decision making, object recognition or speech understanding.

The industrial sector has been immersed for years in its digital transformation in what has been called the fourth industrial revolution or Industry 4.0. There is no doubt that this sector has a high potential to lead the application of AI technologies in the monitoring and optimization of its processes, providing an appropriate scenario to test its benefits, from design and manufacturing processes to the management of the value chain. Thus, large companies such as GE, Siemens, Intel, Funac, Kuka, Bosch, ABB, NVIDIA and Microsoft are investing heavily in the development of new systems to improve their production.

At this juncture, the concept of Industrial Artificial Intelligence (IAI) has recently emerged, which can be defined as the application of AI to the operations, processes and physical systems of a company, so that the behavior of these operations, processes and systems can be monitored, optimized or controlled to improve their efficiency and performance, providing them with greater autonomy. Thus, this concept includes applications related to the manufacture of physical products, production lines and warehouses, or operations related to different processes.

It is an end-to-end system, in which sensors generate data, which are sent, managed and analyzed by means of different algorithms and models that generate decisions in real time and whose results are returned for actual implementation in the actuators.

USE CASES

There are several different use cases related to three categories of applications depending on the degree of automation involved: monitoring, optimization and control.

Monitoring

Industrial processes need to monitor the performance of their systems and products to identify or predict failures and other situations that lead to unsatisfactory results. Some examples that will benefit from IAI technologies are as follows:

  • Quality Control

Companies find it difficult to maintain high levels of quality and comply with regulations and standards due to the current short time-to-market for new products and services and their increasing complexity. On the other hand, consumers expect defect-free products, so companies must avoid the damage that complaints and defective products can do to the brand.

In this context, AI algorithms enable a new form of quality control. On the one hand, algorithms based on image recognition technologies warn production teams in real time about faults in production systems that can reduce product quality (e.g., recipe deviation, changes in raw materials). On the other hand, the implementation of these algorithms allows the prediction of maintenance and planning tasks that minimize the associated risks. Finally, the integration of such algorithms with IoT platforms allows the collection of data on the use and behavior of products during their useful life, information that can be very valuable when making strategic and design decisions.

  • Predictive maintenance

The continuous maintenance of production machinery represents a major expense in manufacturing processes, so it is important to implement solutions based on AI algorithms that allow predicting future failures in a part, machine or system in order to drastically reduce unplanned downtime and increase the useful life of production systems.

Optimization

IAI-based decision making and planning systems allow users to design plans to optimize a set of business metrics.

  • Process planning

Many industrial scenarios include complex work sequences whose order of execution can significantly impact factors such as cost, time, quality, workloads, supplies or waste. The application of AI-based optimization algorithms allows such sequences to be defined dynamically in real time.

  • Generative design

AI is changing the way products and services are designed. Generative design uses AI algorithms to design new products based on their description, including parameters such as type of material, means of production, budget or time to market. These algorithms analyze different configurations before proposing the best solutions.

  • New market adaptation strategies

The application of AI is not limited to the production plant; its algorithms make it possible to optimize supply chains or help companies anticipate market changes. All this is a great advantage for business management, moving from a reactive approach to a strategic one. Thus, estimates of market demand can be formulated by searching for patterns that relate location, socioeconomic and macroeconomic factors, weather patterns, political status or consumer behavior so that companies can optimize their resources or control inventory.

Control

Finally, control systems are at the heart of industrial process operations and are essential to reap the full benefits of automation. Examples of applications that benefit from AI include the following:

  • Robotics

Traditionally, industrial robots have been explicitly programmed to move between a series of 2D or 3D points and perform specific actions at those points. New approaches such as collaborative robots or co-robots simplify programming by allowing the capture of these points based on the robot’s physical position. However, in both cases, the robot does not detect changes in the environment or in the position of the parts it is manipulating. Therefore, computer vision allows robots not to interfere with people or other robots, and to interact independently.

  • AGV

Autonomous mobile robots (AGVs) are used in warehouses and companies to transport and collect materials thanks to the use of image-based AI algorithms that enable them to understand, map and navigate these environments more efficiently.

CHALLENGES OF INDUSTRIAL ARTIFICIAL INTELLIGENCE

Industrial AI presents a number of challenges that set it apart from other consumer-facing AI applications.

  • Data acquisition and storage

IAI systems rely on data captured by sensors that seek to digitally represent the real world. The implementation of IoT platforms and cyber-physical systems (CPS) has enabled large volumes of data in industrial processes whose acquisition, management and storage has led to different architectures and storage systems.

However, it should not be forgotten that large volumes of data are often captured with a lot of noise, which makes it difficult to acquire and store the data for subsequent analysis. Therefore, advanced simulation techniques including digital twins are used to generate training data under different conditions.

  • Data hybridization

A challenge of IAI is the generation of common formats for heterogeneous data coming from diverse sources (images, videos, dwg plans, …). For this, it will be necessary to develop semi-automatic models that help to structure (e.g. extraction of information from a plan, extraction of tags from an image), homogenize (e.g. spatial/temporal interpolation techniques to move from data in one unit to another) and/or harmonize data (e.g. product matching/record linkage techniques to associate data from different sources).

  • Training

The correct application of IA algorithms is associated with the availability of annotated training data. Capturing this data can be complex in industrial environments, as it is often difficult to detect and reproduce some of the failures or lack of quality of products and services.

  • Regulated environments

Industrial environments must comply with certain standards and regulations that impact their operations, such as product safety, public health, environmental impact or occupational safety. In some cases, regulatory controls can make it difficult to implement AI technologies.

As stated in the European Data Strategy1 published by the European Commission in February 2020, Europe must become a model of a data-empowered society for better decision making in the public sector and private enterprise. To this end, the European Union will promote a legal framework in relation to data protection, fundamental rights, security and cybersecurity. The aim is to generate an ecosystem of trust thanks to a regulatory framework for AI2.

SITUATION IN SPAIN

According to a study by EY for Microsoft, the majority of companies surveyed in Spain (65%) have plans, pilot projects or proofs of concept around AI. However, only 20% have solutions in operation, 12 points below the European average.

The “Strategy for Artificial Intelligence in R&D&I in Spain” includes a section oriented to the application of AI in the Connected Industry. As the document states, Spanish industry represents 13% of the country’s added value and employs 11% of the employed population, so the social and economic impact of AI technologies is essential.

What are the features and benefits of Smart Building?

The era of the smart building has arrived. Today, thanks to advances in technology, a building can not only provide all the services the occupants need, but also do it as efficiently as possible, minimizing costs and increasing energy savings over the life of the building. It’s a balance that will be key to business in the future.

What is a smart building?


A smart building is a building that uses technology to use resources efficiently and economically, while creating a safe and comfortable environment for occupants. Intelligent buildings can use a wide range of existing technologies and are designed or retrofitted to integrate future technological developments. Internet of Things (IoT) sensors, building management systems, artificial intelligence (AI) and augmented reality are some of the mechanisms and robotics that can be used in a smart building to control and optimize its performance.

The benefits of smart building analytics?


Smart buildings generate a lot of valuable data about how they are used. Analyzing this data can give you insight into usage patterns and trends, allowing you to make informed decisions to optimize building performance, providing the following benefits:

  • Increased productivity.
    Providing a space that promotes good indoor air quality, physical comfort, safety, sanitation, lighting, efficient processes, and space that employees need at an optimal level will allow them to perform well. Therefore, identifying and understanding how people use and move around your building is integral to improving the physical layout toward optimizing frequently used space while minimizing waste. Increasing the size of a cramped, high-traffic area can be a practical example of this.
  • Reduced energy consumption.
    Smart buildings can improve energy efficiency and, in turn, reduce energy costs. By connecting IoT sensors that track occupancy to your building management system, you can automatically turn off lights or HVAC systems in unoccupied rooms or spaces to reduce unnecessary energy consumption that these aspects emit.
  • Lower operating costs.
    Building overhead is a significant expense for any building owner/user. However, while they are a necessary expense for a business, the level of cost is often wasteful because it is not applied wisely. By identifying patterns of underutilization, you can reduce the footprint of a property to reduce costs.

There are many benefits to implementing smart systems in a building, from cost-effectiveness to making the structure more environmentally friendly. Today, smart buildings are relatively new, but given the wide range of benefits they offer, they will soon become the norm.

How can you make your building smart with data?


The key to successfully turning your building into a smart and efficient space is understanding that only accurate and reliable data can help. At the heart of smart building systems is the data that determines how a facility is used. Once you have this information, you can determine where improvements can be made, either by integrating with other smart technologies and building systems that provide automation or by facilitating strategic decisions. The IDboxRT Operational Intelligence solution can help you monitor different types of usage data in real time.

Want to get started or learn more about how your building is being used? Request a Demo and talk to our experts.

Synoptic: the best data visualization tool

We often find ourselves in the situation of possessing or having access to information, a lot of information, but which, without any kind of organization, is of little use. What is the point of having thousands of data if I am not able to exploit them? Organized data becomes information, very valuable at times, and that is precisely what operational intelligence platforms such as IDboxRT offer me.

This ability to squeeze the most out of my data to obtain valuable information is presented to me in many different ways: the ability to graph and compare historical and real-time data, performing calculations to obtain new data, positioning this data on maps, reports…, but we also offer a more visual way to work with this information: the synoptic.

A synoptic is that “which presents the main parts of a subject in a clear, quick and summarized way”, as dictated by the dictionary. In our case, we use the synoptics to capture data in a visual way, being a schematic representation of reality, which allows us, at a glance, to obtain that valuable information and to know what is happening at the present moment.

Throughout all these years working with synoptics we have used many different approaches based on the nature and needs of each project and client, but experience has made us adopt certain techniques to improve these representations that are often repeated. This is the case of the drill-down approach, in which we start from a generic representation, a high-level visualization, where at first glance it is interesting to know general data, KPIs, and get an idea of where everything is located. From this first level we would navigate to the next one in which we could go into the detail of the selected area, and even obtain data of this in comparison with the rest of the analogous areas, and so, we would continue descending in level to go more and more into detail and get to the specific data.

A real example that we have developed with this approach could be: A first representation of a map of the world, dealing with a client that operates globally, where the top management can get at a first glance information on how their manufacturing plants are operating, and compare to make sure everything is working correctly. With a single click we could navigate to a second, more country-specific level to see the detail of the country’s plants, and in turn navigate to a plant, either because we want more detail or because something has caught our attention when reviewing the KPIs. Once we are visualizing the representation of the plant, we can consider the navigation to specific areas of the plant, and even continue down to the level of machinery or specific parts of each of the machines.

There are infinite approaches for this type of representation, although it must always be in accordance with the need for information. The synoptic representation loses its usefulness if the data shown are not understood or provide unnecessary information.

It is also important that the design of these graphic representations is carried out in accordance with the client, since usually each company has its own way of representing its assets (diagrams, maps, drawings, plans…) and it would be a contradiction to propose something that is unfamiliar to them and would involve a work of adaptation. In addition, we work to maintain the corporate identity of each client so that they perceive these representations as their own and feel “at home”. In this way, they can also make use of these representations at company level on information panels or videowalls. All this entails a previous work to the realization of the synoptic based on the study of the brand and its uses.

Following this approach we have worked on the representation of water treatment plants, road construction projects, industrial production monitoring, refining plants, energy efficiency in buildings, Smart Cities projects and so on.

On the other hand, it is important to highlight that all our synoptic representations use the standard SVG (Scalable Vector Graphics) format, which makes the representations scalable ensuring that there is no loss of quality, and allows the customer to make use of their own representations by importing them directly into the platform.

In addition, from IDboxRT we have an extensive library of pre-made elements of all kinds, so the user can make use of these forms with a simple drag and drop, and even add their own forms to this library.

Synoptics are undoubtedly one of the most powerful tools for data analysis within IDboxRT and are widely used by our clients, regardless of the sector, as they greatly facilitate the understanding of the data and are visually very attractive.

Digital transformation and monitoring and control systems – VI edition of Madrid Monitoring Day #MMD19

Digital transformation and digitization of the business began to take importance many years ago and today it has become the key to the survival of the company. A company needs to adapt to changes in order to stand out from its competition. In this transformation process, technology allows us to be at the forefront of the changes that businesses are going through today.

Technology provides the speed and agility that a business needs to stand out.


Large organizations are developing their digital transformation actions to drive innovation, improve competitive advantage, increase productivity and reduce costs, using new technologies and using innovative IT platforms.

With trends such as Monitoring, Operational Intelligence, Cloud, mobile devices, Big Data, Internet of Things (IoT) or Indsutrial IoT (IIoT), and big data changing the way consumers connect with businesses, many businesses are facing challenges related to adapting their technologies to current needs.

The need for digital transformation arises largely from the large volumes of data generated by IoT devices.

Here arises the need for a monitoring system, which makes the most of the data by obtaining information from any environment for further analysis. Thanks to this analysis, decision making will be more effective.

In addition, with monitoring systems it will be possible to ensure quality through predictive maintenance, and monitor operations from anywhere.

Still don’t know how to face the digital transformation of your business? Still haven’t implemented a signal monitoring system? We invite you to the VI edition of Madrid Monitoring Day.

VI edition of Madrid Monitoring Day #MMD19, a reference event in Monitoring and Operational Intelligence Solutions.


Through the #MMD19 it will be possible to learn about the monitoring tools needed for the digital transformation of your business, as well as discover the benefits and the important economic impact of its implementation.

We will also highlight the value of the monitoring process in critical environments, and we will discuss the problems in various sectors through real cases in large organizations.

A reference event focused on signal monitoring solutions in various environments: Energy, Smart City and Industry 4.0.


Madrid Monitoring Day #MMD19 is an event that in all its editions has been very well received, with more than 300 attendees annually. Among the profiles that attend the event we can find managers of technology companies, IT directors, CTOs and CIOs, project managers, service companies and energy solutions, consulting, engineering and municipalities, among others.

Madrid Monitoring Day will highlight the benefits of monitoring and information control platforms as tools for the Digital Transformation of the business.

This year’s agenda is full of novelties. You will be able to learn about various monitoring projects through presentations and demonstrations.

Speakers from organizations such as Vodafone and Cepsa will participate in the VI edition.

This edition will feature half a day of presentations by experts from different fields who will present their experience with monitoring systems and the benefits that this type of platform has brought to their business.

The meeting will also have an exhibition area, with a space of stands dedicated to the presentation of products and solutions related to digital transformation. There will also be a demo room where you will be able to discover the opportunities offered by Real-Time Data Analysis and Operational Intelligence tools.

A networking environment will be fostered for the exchange of ideas between attendees and speakers throughout the day.

To end the event, a Lunch and a Gin&Tonic tasting will be offered by the best cocktail makers.

BIG DATA and OPERATIONAL INTELLIGENCE: a connection for life

The data generated by the machine makes Big Data analysis really interesting. Among other things, they allow you to improve the user experience, increase IT stability, detect security threats and even analyze customer behavior. But for that, the information must first be found and reviewed.

What is operational intelligence (OI)?

OI can be defined as a form of real-time business analysis that offers actionable visibility and an insight and management of all business operations.

The data produced by real-time operational intelligence enables operators to understand the performance of distributed infrastructure, make predictions, improve efficiency, and even prevent disasters. This gives a greater ability to make the right operational decisions and engage important stakeholders. Importantly, IO software learns from past actions through artificial intelligence (specifically, machine learning) and can therefore improve its own decision-making processes.

Operational intelligence, along with machine-generated data, provides the ability to understand exactly what is happening in individual systems in the IT infrastructure, in real time.

Therefore, modern Big Data platforms for operational intelligence are capable of processing more than 100 terabytes of machine data every day, which then serves as a prerequisite for making informed decisions in different business processes. Product managers can bring applications and services to market faster, managers improve the availability and performance of internal IT solutions, while sales teams have the ability to tailor services and products to customer behavior. The opportunities for business process optimization are endless.

How operational intelligence works

Operational intelligence plays directly with IT itself: A large amount of information is produced there from different IT segments to solve exact problems such as performance. This information generally includes web infrastructure logs, network data, application diagnostics, or cloud service information. Shortly after consolidating this data, it is possible to conduct a cause investigation and react to specific incidents, failures, and other problems. Monitoring mechanisms and alarms allow you to monitor your entire IT infrastructure, including applications, by identifying specific conditions, trends, and complex patterns. With this real-time report of an organization’s “machine rooms”, IT administrators will be able to develop a service-oriented view of their IT environment. This enables on-the-fly reports and data visualizations that provide an overview of events from different perspectives. This includes information about how applications, servers, or devices are connected to mission-critical IT services.

The main characteristics of an Operational Intelligence Software

  • Monitoring of all business processes in real time.
  • Detection of all kinds of situations throughout an operational process in real time.
  • Big Data control and analysis. Our Operational Intelligence Software continuously monitors and analyzes a variety of high-speed, high-volume Big Data sources.
  • Analysis of different situations, trends, the root of the problems.
  • Different users can view the data dashboards in real time.

Conclusion

Applications, sensors, servers and clients constantly generate data. This machine information can be used for user transactions, customer behavior, sensor activity, machine behavior, security threats, fraudulent activity, and other measures. For meaningful analysis and subsequent decision making, special operational intelligence platforms are suitable. They allow you to discover the value of hidden information by collecting, indexing, searching, analyzing and viewing the vast amount of information. It offers companies real-time information about the increasingly digitized business world that can be used for decision-making and corporate governance.