Data Integration: Digital Transformation In Retail

October 6, 2021

The trade is constantly changing. If you want to be successful as a retailer, you have to react to new trends and developments in good time. The main focus is on digitization and the associated integration of data into the various systems. The trick is to automate the processes as much as possible and avoid manual intervention.

The Challenge In Retail: Many Systems Without A Direct Connection

Anyone who is not confronted with the processes in retail daily usually imagines entry into the world of e-commerce to be straightforward. After all, what is problematic about getting the right software for setting up an online shop from the many reasonable solutions available on the market, adding the related products, and then simply starting online trading?

Well, for smaller companies, this picture is at least partly accurate. Even if the entry has its pitfalls here too. But access is much more complex, especially with larger dealers. In most cases, the difficulty lies in the fact that many different software solutions are already in use in the company. Although these autonomously serve their purpose well, they are not automatically networked with one another.

As a result, data from third-party systems such as ERP, PIM, or CRM systems are often integrated manually into the online shop using Excel tables. The disadvantages of this manual approach are apparent:

Valuable working time is required for this
The data is not available in real-time
The source of error is much higher than with automatic import

The larger and more complex the system architecture, the stronger the effects mentioned. But what options do retailers have today to meet this challenge efficiently and thus operate efficiently in contemporary e-commerce?

The Solution: A Digital Ecosystem

The expectations of customers when shopping online are very high these days. The prominent players in the industry, such as Amazon, are responsible for this. With these, everything works smoothly, from selecting the products to the delivery to the eventual return of the items. Customers therefore no longer understand if this is not the case with another retailer.

You can expect detailed information on the individual products that you see in the online shops. In addition to basic information such as size, weight, color, and price, images and, increasingly, videos also contribute to the purchase decision. In addition, they want to be recognized as customers in the online shop and expect features such as printing out a label for return shipping or an overview of the items they have purchased so far.

This information is available in some software solutions in the company, for example, in its web development for the preparation of images and videos or in a cloud-based CRM system. Still, the merging prepares those responsible for sales, marketing, and IT gray hair.

The solution is to build a digital ecosystem in which all the different information and data sources from the most varied channels can be brought together and subsequently output in real-time. Because only with automated synchronization of the data from the different systems is it possible to optimize the internal workflows and processes accordingly and thus exploit the full potential of the individual software solutions fully. So far, these ecosystems in retail have mainly been built up through the use of appropriate middleware. But now, so-called iPaaS solutions are moving more and more into the foreground.

IPaaS Enables Complex Connections With Little Effort

The abbreviation iPaaS stands for “Integration Platform as a Service” and is thus a modification of the already known SaaS (Software as a Service). State-of-the-art platforms enable data consolidation from the different systems to be set up via a simple web interface.

The software solutions in use, such as ERP, PIM, or CRM, are linked via plug & play connections or web interfaces or file transfers. Thanks to the low-code approach, even complex relationships can be implemented with minimal effort.

A significant advantage of iPaaS compared to previous middleware solutions is primarily the lack of maintenance. The operator makes necessary adjustments and updates to the software. This means that the system is always up to date. Another advantage is the scalability of iPaaS solutions. A flexible expansion is possible at any time without great effort.

iPaaS is particularly interesting for retailers who, on the one hand, want to design their sales processes themselves, but on the other hand, do not want to burden their team with the time-consuming tasks associated with it. Since critical issues such as data protection and security are in the hands of the respective iPaaS provider, the crew can concentrate fully on their core tasks.

For Automated Data Integration In Just A Few Steps

Anyone who has long been a thorn in the side of manual data consolidation in the company can change this situation very quickly. Usually, only the following six steps are required:

Analysis of exactly where the individual data comes from, i.e., from ERP, PIM, CRM, etc.
Clarify which structure the respective data is available, such as Excel, Edifact, SAP, etc.
Define the desired target structure: data mapping
Select the appropriate iPaaS solution and obtain reasonable offers
Carry out data integration in the iPaaS solution
Begin with the data transfer according to the set specifications for the data integration

The complexity of the current system landscape determines the period on the way to automated data integration. In austere software environments, the changeover can be accomplished within a few days. With more complex solutions, it usually takes several weeks for all systems to communicate with one another smoothly.

ALSO READ: IIoT Is Driving Industrial Innovation With 5G And Edge Computing

IIoT Is Driving Industrial Innovation With 5G And Edge Computing

Techno Rumours

October 6, 2021

Even if the number of connected IoT devices in the consumer goods sector exceeds the number of devices in the industrial sector, investments in industrial IoT (IIoT) are growing strongly, especially in cross-industry solutions and customized machines.

Ripley’s new report “Industrial IoT: A Reality Check” examines two key areas driving the growth of IoT in the industry: intelligent factories and intelligent solutions in transport & logistics. IIoT enables manufacturers to improve production transparency by networking machines and tools in real-time. The enormous amounts of data that devices generate at IIoT drive the optimization of production and the improvement of delivery quality. In addition, the implementation of systems for predictive maintenance or the automation of the supply chain.

“Without Industrial IoT, Industry 4.0 is not possible. Data is the fuel for all intelligent use cases in the industry. IIoT is the crucial infrastructure element for data collection, its transfer to the cloud, and analysis. Companies benefit from many advantages here,”.

IIoT: Markets On A Growth Path

The study was carried out using the data collected on the Trend Sonar platform and with the support of Technology. She explores the significant markets for both intelligent factories and intelligent solutions in the transportation and logistics industries.

Despite the challenging economic climate in 2020, both clusters recorded slight growth in investments in smart factories and the area of transport & logistics. However, analysts forecast much more substantial growth until 2025. Overall, the market for intelligent factories of the “Big 5” cluster – led by the USA with high investments in appropriate platforms, predictive solutions, and remote monitoring – is expected to contain more than 86 billion euros by 2025. The market for intelligent solutions in transport & logistics is expected to be more than 15 billion euros.

In the “Europe 5” cluster, on the other hand, the market for intelligent factories is expected to almost triple in all countries and reach a total of over 23 billion euros in the five countries, with taking the top position. The platforms are growing exponentially, and the companies are investing in improving quality management and reducing costs. remains the leader in the field of transport & logistics. The other countries in the cluster are also recording considerable growth. According to the forecast, this group will generate a total volume of 3.6 billion euros in 2025.

Growth Spurt Through 5G And Edge Computing

The introduction of low-cost sensors and 5G networks, in which telecommunications companies are investing heavily, contributes to the spread of Industrial IoT. Experts expect that the improved communication between autonomous vehicles/robots, artificial intelligence, and machines in connection with increased computing power and very low latency will improve the efficiency of the systems and increase their safety.

In addition, the establishment of private, high-density networks enables the broad use of Industrial IoT and the connection of numerous sensors, machines, vehicles, and robots. This is supplemented by increased use of augmented and virtual reality to support “networked employees.”

Cybersecurity Is Critical To IIoT

The constant increase in networked devices and their heterogeneity require good security management, especially with devices and networks’ setup and maintenance guidelines. Companies need to set up robust and micro-segmented environments (local and cloud-based). These can react to threat scenarios with suitable technologies and techniques. This reduces the chances of success for new types of cyberattacks.

The analysis of IoT architectures, industrial components, and entire infrastructures helps companies eliminate gaps, weak points, and threats in advance. This is far more than just a technical question: training programs for employees and continuous testing of all equipment used are also crucial.

IIoT: From The Factory To The Consumer

In recent years factories and logistics centers have introduced IIoT technologies to optimize efficiency. Investments during the pandemic were primarily aimed at improving worker safety. The success of so-called “networked products” accelerates investments in solutions in which the collection and processing of usage data affect production and the finished products. The redesign of the design, display and sales processes for IoT-networked products enables new value-added services. In addition, IoT makes it easier to update and maintain household appliances, cars, robots, electronics, and entertainment devices without being on-site.

The study “Industrial IoT: A Reality Check” is part of the Reply Market Research series, which already includes the following reports: From Cloud to Edge, New Interfaces, Zero Interfaces, and Beyond Digital Marketing.

Reply specializes in the development and implementation of solutions based on new communication channels and digital media. Consisting of a network of specialized providers, Reply supports European industrial groups in the fields of telecommunications and media, industry and services, banks and insurance companies, and public administration in the development of business models made possible by technologies such as AI, big data, cloud computing and the Internet of Things.

ALSO READ: Metadata: How This Can Secure Messenger Services

Metadata: How This Can Secure Messenger Services

Techno Rumours

October 6, 2021

Crime fans know the scene from many films: suspects are caught with the tracing of telephone calls. The investigators use metadata for this, which provides information on who is communicating with whom and when. These are more easily accessible for secure communication than expected.

Metadata is structured data that describes other data – in a sense, data about data. They contain important information about websites or even pictures and videos, including the place and time of a recording. Metadata is also used in software development, for example. There you can describe various processing rules and programming instructions, which can be used to implement more complex applications. In the example of telephone usage, metadata describes who communicated with whom and when. It is important to note that they alone do not provide any information on the exchanged content.

No Protection Through End-To-End Encryption

Depending on the area of application, it can make sense to capture metadata. In the case of messaging services, among other things, they secure the functionality. Many therefore assume that the services can be encrypted and thus protected to a similar extent as the message content itself. However, this is often a fallacy since the end-to-end encryption often used does not cover metadata. Therefore, both messaging providers and, in some cases, third parties can read and analyze them.

Such analyzes can be interpreted in many ways, for example, to reconstruct groups of friends and acquaintances. Daily routines can also be traced. The time of the first sent message of a day provides information about when to get up. If a messenger logs in from Monday to Friday via the IP address of the same company, this is almost certainly the employer. This is no illusion, but backed up with scientific evidence: In a study, researchers from Ulm reconstructed daily routines, including deviations, from the presence status on WhatsApp alone, and at the same time disclosed who was in contact with whom at what time.

The obvious question is: How can such conclusions be prevented from the outset? Specific critical data in chat messaging are essential. This includes the sender, recipient, and the times for sending and receiving. Can metadata be dispensed with here? No, but the amount of metadata can be reduced. Furthermore, access to them can be limited, and their combination with other (meta) data can be prevented.

Approaches To Protecting Metadata

There are several approaches to protecting metadata. First and foremost, “Sealed Sending” should be mentioned here. Messages can be sent without the sender being identified – practically a digital equivalent of a letter with an empty sender address. However, even with this method, metadata can be read out under certain circumstances – conclusions about the person cannot be completely ruled out. If the IP address is read out, it can be traced to who is communicating with whom. For example, if IP 1 sends 5,372 bytes to a messenger server and forwards 5,372 bytes to IP 2 directly at the connection, IP 1 is likely in contact with IP 2.

But this is not the only reason why IP addresses are problematic. In addition, they can often be assigned to a fixed geographical area and thus restrict the potential whereabouts to a certain extent. Messenger services pass this information on to the provider – possibly also to service providers.

If the metadata protection provided by “sealed sending” is insufficient, further measures can be taken. These include messenger services that anonymize the IP address involved when exchanging messages. However, this variant does not offer absolute security either but instead harms the user experience. The reason? To communicate with each other, both the sender and the recipient must be online simultaneously with this method.

The Key: Shredding Metadata

So-called metadata shredding is recommended if neither content nor metadata is to be recognized. This procedure protects by mixing metadata in “anonymity sets” and makes them unrecognizable. As a result, service providers and third parties can neither analyze activity patterns nor connect senders with the respective recipients.

In this way, the privacy of both sender and recipient is fully protected. Conclusions about the respective persons are no longer possible due to the anonymity sets. So far, providers have mainly implemented this concept for messenger services. Potential future application scenarios can also be payment systems. In any case, this technology has the potential to prevent conclusions from being drawn from metadata finally.

ALSO READ: Digital Marketing: This Is How SMEs Implement Effective Measures

Digital Marketing: This Is How SMEs Implement Effective Measures

Techno Rumours

October 5, 2021

Small and medium-sized companies, in particular, can use digital marketing to their advantage because digitization offers new ways, to advertise to customers effectively. Maximilian Model explains how to do it correctly and what needs to be considered during implementation.

It is now widely known that digital technologies are the key to economic success. Digitization optimizes processes, increases efficiency, and can make marketing more individualized. Large companies have relied on digital marketing for a long time, while many smaller retailers and medium-sized companies still find it difficult. The reasons for this vary from person to person. Some companies lack staff resources or IT specialists, while others lack technical know-how or information. Still, others are unsure where to start with digitization.

Understand Digitization – And Use It Correctly

Many companies are wondering why they should digitize in the first place. Digitalization brings you three main advantages: process optimization, increased efficiency, and customer-specific individualization. The last point, in particular, individualization, is essential in marketing and customer communication today. Nobody can – or should! – afford to send a generic monthly newsletter because the customers themselves are usually very heterogeneous. Personal contact is what counts; a customer must have the feeling that they are being addressed personally.

Start Digital Marketing At The Push Of A Button

The most significant advantage of digital marketing lies in its automation: modern marketing tools enable newsletters to be sent automatically under certain conditions. Companies can trigger the sending of newsletters with their actions, for example, by clicking on a specific product in the online shop. For this purpose, the marketing software is connected directly to the company’s online shop. With this type of personalized advertising, target groups can be reached much more precisely than before. Modern marketing is therefore individually tailored and exactly filled with the content that is also relevant for the contacts – a win-win situation for buyers and retailers.

Digitally Networked – Everywhere

By the way, nowadays it is no longer enough to communicate with your customers via one channel. Today, consumers use a variety of digital media on which products and services are advertised. Small and medium-sized retailers often do not have the resources to be present wherever the customers are – unless they use digital marketing. Because these allow a much broader distribution, not only via e-mail or SMS but also on all known social media channels, the best thing about digital marketing tools is that information and content can be spread widely. At the same time, there is no lack of personal and individual approaches. It is not an either-or, but both are possible with digital marketing.

Digital Marketing – Cheap, Simple, Secure

The advantages of digital marketing offers are apparent: They are cheap, easy to use, and guarantee data security. It must be clear that retailers who switch to digital marketing tools are reducing costs and, at the same time, demonstrably increasing sales through the added value described above. In addition, such devices reduce the complexity of the applications – this also saves employees’ time, which can be used profitably elsewhere.

Last but not least, one should never forget the data protection factor in marketing activities. While large companies often have their legal departments, small companies do not. Digital marketing providers can also help here. When choosing the right tool, GDPR compliance and the server location should always be taken into account. European providers offer the most outstanding possible security here. Just as consumer habits have changed, so must marketing. In particular, small and medium-sized companies benefit from all-in-one marketing solutions because these give them all the tools they need for personal and efficient customer communication today.

ALSO READ: Sales: New Level Of Digital Development Due To The Pandemic

Sales: New Level Of Digital Development Due To The Pandemic

Techno Rumours

October 5, 2021

Sales New Level Of Digital Development Due To The Pandemic

During the corona crisis, companies had to use the digital turbo, especially in sales. Because in times of social distancing and remote work. face-to-face is a thing of the past. Technology now takes on administrative tasks – and determines the value chain in sales.

Attributing the digitization success of companies exclusively to the Covid-19 pandemic does not fully reflect reality. Many companies have been investing in digital business models and the corresponding infrastructure for years. And yet: Digital tools have seen a quantum leap in cross-company and cross-functional acceptance in the past fifteen months. Even industries that live and benefit primarily from human contacts have developed into true pioneers of digitization due to lockdowns and social distancing. Sales are particularly affected by this development.

Sales Is A Pioneer In Digitization

The “State of Sales” survey conducted by CRM provider Pipedrive on the status quo of the sales industry also shows that sales are one of the pioneers in digitization. In total, the company surveyed over 1,700 sales employees worldwide. Only four percent of sales employees stated that they use pen and paper to track sales. Instead, spreadsheet programs predominate in 17 percent of cases. And four out of five salespeople use a CRM solution. In addition, the study shows that technologies are not only purchased by employers but are also increasingly used and accepted by employees. Three-quarters of those surveyed are happy about the existing CRM tools to support their work.

Sales: New Understanding Of Digital Tools

Digital tools have long been seen and used in sales – as little helpers for tedious or repetitive administrative tasks. But that falls into the “nice-to-have” category and, if so, indirectly creates value. However, during the pandemic, there was no alternative to integrating software into integral parts of the sales value chain.

Even old-school salespeople, who have always sought customer contact and visited customers face-to-face for face-to-face meetings across the sales territory, had to consider new exchanges and product demonstrations options. Because face-to-face doesn’t work if personal customer contacts are not allowed.

The same applies to lead generation: If trade fairs and networking events no longer occur, business cards can no longer be exchanged. Lots of canceled or postponed face-to-face events, reduced budgets, and office closings suddenly determined the everyday life of sales employees worldwide in the pandemic.

Virtual Product Demos Instead Of Face-To-Face Meetings With Customers

The alternatives are online product demos or zoom calls instead of personal customer appointments and lead-gen software instead of trade fair visits. What sounds striking at first but quickly led to the conclusion that with the help of technologies, sales can scale significantly better:

More video calls can be made every day than booking appointments with customers, including travel time.
The software flushes more leads into the databases than a fair trade date.
Potentially interested parties can be better qualified if the artificial intelligence has checked beforehand whether the right contact person is at all or whether there is any interest at all.

Of course, sales remain a face-to-face business – and appointments with customers come back, of course. But sales have learned that digital tools can take over routine activities and create value if used well. Technologies and automation tools for generating and qualifying leads will be used eleven percent more often in 2021 than in the previous year, at 63 percent. The sales results confirm this trend.

Competitive Advantage Through Digital Technologies

And so, in the past year, virtually the entire value chain in sales was digitized. Many decision-makers created technological alternatives to the analog processes and thus kept sales going. Because of the positive consequences, even the last refusal to digitize should slowly run out of arguments. Because of the sales employees who were able to fall back on automated technologies for lead generation and qualification, 63 percent achieved their sales targets despite the problematic framework conditions.

In contrast, just over half of those who did not have technology and automation tools at their disposal fell short of expectations in the same year. These numbers fill many salespeople with confidence that they will be able to increase sales further. Nine in ten salespeople believe their professional skills will positively impact the economy this year, not least because of a new digital understanding.

ALSO READ: Process Optimization: Techniques And Tools

Process Optimization: Techniques And Tools

Techno Rumours

October 5, 2021

Process Optimization Techniques And Tools

Discover how process optimization allows the company to be more efficient and effective. We live in a highly changing market. New technologies and changing consumer tastes mean that companies must have agile organizations to cope with these changes. To achieve this, businesses must have good process optimization.

What Is Meant By Process Optimization?

Process optimization is a technique by which the company can analyze all business processes to eliminate errors and, most importantly, make these more efficient and effective by reducing time.

It is possible that, without your knowing it, you can optimize processes within your company that are considered routine. It is essential to carry out an in-depth analysis that we will deal with later in the text. This study can help us see points where the company is ineffective and wastes a lot of time and, therefore, money.

Thanks to this type of work, companies will integrate external and internal information more quickly. In such a way that the analysis capacity will be improved, they will act more rapidly, and, consequently, the business losses produced from the loss will be minimized. Time and unnecessary mistakes.

How To Work On Process Optimization

Once you know the importance of optimizing processes in the company, it is time to understand how to carry out this task. The steps to follow would be the following.

Step 1: Identify Problems Or Weaknesses

Now is the time to ask yourself all the doubts you have. Where is the company failing? Where do you spend the most time? Are our customers, suppliers, or workers unhappy with a specific process? These and other questions of this nature are necessary to know where to start the analysis. In addition to asking yourself these questions, you must list all the processes, rank them based on their importance and objectives within the business process and estimate the time used in each one of them.

Step 2: Reframe The Situation

Now it is your turn to think about how you could rethink the processes in which you have detected points of improvement. Do you think there is something that can be improved? Brainstorm with all the parties involved in the process so that you will achieve objective points of view that will provide you with good ideas for improvement.

Step 3: Implement

Once you are clear about what to improve and how it is the process of implementing these changes, it is possible that, at this point, you can use process automation tools to generate greater agility.

Step 4: Control

As always, you can’t just stay on implementation. It is essential to keep track of the processes and the changes that have been made to them. Ask yourself if the changes you have made really meet your objective and, if not, go back to step 2 and rethink the situation again.

Valuable Tools To Carry Out Process Optimization

Depending on the processes you want to optimize and automate, you will have a series of tools or others on the market at hand. However, we want to recommend some that can be very useful to start carrying out this optimization:

NSA Auto Store: The ideal tool to transition from paper documents to the electronic plane in an agile way and without wasting time.
ABBYY FineReader: The ideal tool to transform documents into editable documents, thus saving time and the possibility of implementing modifications continuously.
Smart Fax: The ideal way to use fax and scanner, minimizing sending errors.
Document management programs to manage all documents from the same platform.

ALSO READ: Enterprise Cloud Index : Healthcare Industry Relies On The Hybrid Cloud

Enterprise Cloud Index : Healthcare Industry Relies On The Hybrid Cloud

Techno Rumours

October 4, 2021

For the new study “Enterprise Cloud Index ” by Nutanix, companies in the healthcare sector were asked whether they use private, public or hybrid cloud. Seventy percent of surveyed people confirmed that the Covid 19 pandemic has given the IT infrastructure a strategically important role and accelerated their digital transformation projects.

With the pandemic outbreak, the healthcare industry was looking for ways and means to effectively master the essential technical requirements triggered by the Covid 19 crisis – from setting up home workplaces to supporting telemedicine procedures to coping with the growing number of patients. Against this background, the digital transformation in the healthcare industry has top priority. The healthcare sector is showing the most significant interest in an IT model based on a hybrid cloud. Ninety-five percent of those surveyed see this as the model of their choice.

Hybrid Cloud: Replacement Of Traditional IT Architecture

More than half of respondents in the healthcare industry have increased their use of the public cloud and the hybrid cloud , while 46 percent have increased their investments in private cloud environments. The industry aimed to give the newly arrived teleworkers access to IT resources in the shortest possible time. Before the crisis, 77 percent of the companies surveyed had employees who worked from home. At the time of the survey, it was 93 percent.

The future of the healthcare industry depends on the replacement of traditional architectures: 27 percent of those surveyed only use standard, non-cloud-enabled data centers. That is more than in any other industry with an average of 18 percent. But the gap will become smaller: The share of traditional data centers in the industry will decrease by 21 percentage points by 2025, while the share of hybrid cloud implementations will increase by 32 percentage points.

Hyper-Converged Infrastructures As The Basis For Hybrid Cloud

To support the modernization of IT and pave the way towards the hybrid cloud, the healthcare industry is turning to hyper-converged infrastructures: Hyper-converged infrastructures (HCI) are often viewed as the basis for hybrid cloud infrastructure, the HCI of the next decade. Because hyper-converged infrastructures massively reduce the time required to set up a software-controlled infrastructure necessary to support a private cloud. At the same time, they offer the scalability of cloud technology. Around 64 percent of respondents in the healthcare industry said they have already introduced hyper-converged infrastructures or are in the process of doing so. Compared to the global average of 50 percent, this is a significantly higher proportion.

Security And Compliance As The Most Significant Challenges

Security, data protection, and compliance, in general, represent a significant challenge for the digital transformation of the healthcare industry: 58 percent of respondents from the healthcare industry see the issue of security as a significant challenge compared to 51 percent on the global average. In addition, 45 percent of respondents from the healthcare industry named the issues of cost control and business continuity as significant challenges more often than their colleagues from other industries.

In the healthcare industry, cost advantages are increasingly becoming a decisive factor influencing the provision of IT infrastructures: the healthcare industry sees the respective strengths of technology solutions concerning security, data protection, and compliance as essential factors influencing the decision-making process for specific infrastructure. On the other hand, in the health sector, cost advantages were cited as a decisive criterion more often than the issue of safety. A similar finding was otherwise only found in the services for consumers and the energy industry.

Hybrid Cloud As A Critical Factor For Digital Transformation

“The healthcare industry is in a critical phase. It needs to accelerate its digital transformation to meet the needs of patients and staff better. The powerful trigger for this acceleration was the pandemic. IT decision-makers agree that the hybrid cloud is a critical factor for digital transformation, “.

“Now, it is important that companies and organizations in the healthcare sector identify the IT solutions that will help them on this path. They need to invest in private cloud environments based on hyper-converged infrastructures and find ways and means to connect their private and public cloud environments. With all this, the issues of safety and costs must never lose priority,”.

ALSO READ: A Turbo For Artificial Intelligence In Production

A Turbo For Artificial Intelligence In Production

Techno Rumours

October 4, 2021

A Turbo For Artificial Intelligence In Production

Artificial intelligence (AI) in Industry 4.0 has a lot of potential – but there is technology barriers that make the use of AI more difficult. Researchers at Fraunhofer IKS are developing a framework that supports and optimizes the data and AI life cycle. This significantly increases the added value through AI.

Industry 4.0 describes the advancing digitization in production – machines and processes are intelligently networked, which means that more and more data can be generated. Artificial intelligence (AI) can yield information from this data to improve products and services. Possible application scenarios are predictive maintenance, optimization, and automation of processes and quality checks. However, this potential cannot currently be fully exploited in Industry 4.0 because several technical barriers restrict the generation and processing of information.

The first obstacle is the multi-vendor landscape in today’s production facilities: machines from different manufacturers from different technology generations with other – and often proprietary – communication interfaces and protocols. Due to this heterogeneity, uniform data access is not possible. Instead, there are many technology-specific island solutions for which domain knowledge is required.

Incomplete Data Sets Cause Problems

The second obstacle is the lack of support for the data scientist. He has no domain knowledge, which is why he needs help in obtaining real-time or historical data. There is also the problem of incompatible, inconsistent, and incomplete data sets and missing metadata. As a result, the data processing process is often tedious, lengthy, manual, and complex in coordination.

The third obstacle is the inflexible AI operation. AI applications are often operated rigidly in the cloud or on a local server. As a result, the applications do not have the opportunity to make optimal use of the available resources. In addition, updates of the AI applications are necessary – to react appropriately to changes in the production facility or the processes – for which, however, there is still no general solution.

The Solution:

A Framework For The Data And AI Lifecycle

To overcome these problems, researchers at the Fraunhofer Institute for Cognitive Systems IKS are working on an open, interoperable, and technology-neutral project as part of the project “REMORA – Multi-Stage Automated Continuous Delivery for AI-based Software & Services Development in Industry 4.0″Framework that supports and optimizes the data and AI lifecycle. The aim is to ensure an automated, continuous, and dynamic process that consists of

Data acquisition
Data aggregation
Data preparation
AI development
AI training
AI integration
AI operation

Data analysis
AI monitoring
AI update

In detail, the framework should achieve the following goals :

Support of the data scientist,
automated and flexible AI integration as well
Automation of AI processes.

It all starts with developing an interface for the data scientist to support the AI development process. This interface makes it possible to query data easily and uniformly without considering technology-specific aspects such as communication interfaces and protocols. The interface then takes on – internally – the mapping to the technologies and the required data transformations. In addition, the interface provides an overview of the topology, the metadata, and an interface for training and operating an AI model. This interface can be used not only by a data scientist but also by a layperson in connection with, for example, an Auto ML framework.

An application management component enables automated and flexible AI integration – from the component level to the cloud-based on the required resources and optimization goals. In addition, the AI application manager, together with the data interface, ensures that the AI applications are networked to provide the flow of data.

Finally, an AI management component should enable the automation of AI processes, i.e., the automatic retraining and redeployment of an AI model to ensure the continuous improvement of the data analysis. For example, new training data can be automatically collected to train a new AI model when machines are exchanged. Furthermore, automated operations can be carried out in response to the data analysis (e.g., cooling down in the event of overheating) or to increase the efficiency of the real-time AI analysis (e.g., adjusting the sampling rate).

For the production of the future, this means: With this framework, the potential of AI in Industry 4.0 can be better exploited – through simplified and technology-neutral data access, support for AI development, flexible and automated AI integration and updates – and thus efficiency can be increased in AI operation.

ALSO READ: What Is The Security Of Cloud Services?

What Is The Security Of Cloud Services?

Techno Rumours

October 4, 2021

In this overview, you will find – without claiming to be exhaustive – introductory information about the Security of cloud services.

General

Cloud computing offers numerous potentials in terms of flexibility, cost advantages, and other factors. The possible uses range from simple data transfers to data backup in the cloud to the use of software as a service, where an external IT service provider operates software and IT infrastructure. In this way, depending on the constellation, costs can be reduced, for example, by requiring fewer local IT resources.

In addition to the pure IT infrastructure, the cloud also forms the basis for entirely new process designs or business models. A typical example is collaboration tools, applications that enable various actors to work together on specific data or projects stored “in the cloud.” Further examples can be found in faster image processing in the medical field, more efficient order processing in agriculture, or in logistics – the possible uses are ultimately virtually unlimited.

As with any IT application or infrastructure, cloud services are associated with various security issues. In addition to technical and organizational aspects, these also include legal issues such as protecting personal data. In the public discussion, the range of cloud security assessments ranges from blanket rejection to the consideration that a single company can only achieve the high level of Security of a specialized cloud provider with great effort.

Cloud Security And Standards

Accordingly, cloud providers are also required to monitor and implement existing and changed legal requirements continuously.

In recent years, various approaches have developed on this basis, detailing the security requirements for cloud services and providers. The typical requirements range from compliance with basic IT security standards such as the ISO / IEC 2700x series to the use of state-of-the-art encryption methods and protection against, for example, DDoS attacks to ensure availability.

The basic idea behind the corresponding standards is, on the one hand, the definition of state of the art, to which reference is made in various legal bases and which can thus be relevant as a benchmark concerning questions of liability or decisions on fines. On the other hand, standards can also be contractually agreed upon between the provider and user if required, which is particularly common for projects in the B2B area.

Labels And Certification

In areas ranging from product quality to organic food, numerous certifications and labels are intended to increase customer confidence in certain products. In most cases, these are awarded by private-sector organizations based on previously defined catalogs of requirements. Corresponding offers also exist concerning the Security of cloud services.

However, in cloud services, in particular, the security requirements are comparatively extensive and complex. Therefore, in connection with labels, it should be noted that providers or services without a specific brand are not automatically “unsafe.” A title can be the first indication, but the actual security requirements and measures require an in-depth analysis on a case-by-case basis for all cloud projects that go beyond standard applications.

In this respect, the respective standards and catalogs of requirements can be used in several ways, for example:

For cloud providers as a basis for implementing and documenting security measures according to the state of the art
As a basis for a corresponding certification or the receipt of a label as a cloud provider
Independent of labels in the sense of a checklist for the consideration of security aspects in the context of cloud project.

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What Is Artificial Intelligence?

Techno Rumours

October 4, 2021

Artificial intelligence is already one of the most critical technologies of the future. But what is it explicitly about, what benefits does the technology bring for companies, and where are possible application areas?

What Is Ai

When artificial intelligence (AI) is mentioned, so-called weak AI is usually referred to: Individual human capabilities – such as recognizing text, image content, or specific patterns – are transferred to machines. One sub-area is “machine learning”: Mathematical techniques enable a device to independently recognize relationships based on large amounts of data and project the knowledge gained onto future work steps. However, these methods usually require large and high-quality data sets and can only be used to a limited extent in many areas. In addition, machine learning processes have only been able to make predictions and not provide any explanations for relationships.

Vital artificial intelligence aims to create an intellect capable of anything that a human would also be capable of. So far, this form of AI is still a vision of the future. Algorithms have long been part of mathematics, and artificial intelligence has been worked on for 20 years. But only today’s enormous computing power makes it possible to understand vast amounts of data, draw conclusions from data patterns, learn and change results, and, last but not least, interact with systems or customers. However, whether a strong AI can ever be created from this is controversial.

What Can AI Do?

Swarm Intelligence

A population of autonomous software programs cooperates to solve problems. For example, based on this principle, a swarm of autonomous robots can be developed that has collective perception. This means that the individual swarm robots collect their data about their environment and have access to the data of other swarm members. In this way, the swarm has collective knowledge, and tasks can be solved through cooperation between the swarm members.

Language Understanding

Machine learning enables software programs to read from a spoken sentence what language it is and the content of the sentence. In addition, the speech recognition algorithms allow the creation of answer sentences and thus dialogue with the technology used. Such applications of artificial intelligence are often used in everyday life for voice control of technical devices.

Emotional Skills

Systems that are developed to recognize and interpret human emotions fall into the research area of affective computing. Based on factors such as the pitch of the voice or the facial expression, such systems can conclude a person’s emotional state. The purpose of such applications is that machines develop a better understanding of humans and become capable of social interaction.

Artistic Creativity

In art, too, patterns can be recognized through machine learning processes, among other things. These can then be automatically assembled into entirely new works of art. By analyzing the results of an artist, contemporary pieces can be created in his style. In the meantime, artificial intelligence works have already won poetry competitions and raised large sums of money at art auctions.

Image Understanding

AI is also suitable for recognizing patterns in image material if enough images are made available as a reference in the machine learning process. This enables visual quality control to be automated in logistics, for example. Artificial intelligence now usually achieves better results in this area, and this has been constant over time.

Robotics

Robots can use artificial intelligence to learn independently to solve new tasks and to react to their environment. This means that more complex tasks can be automated. Other application possibilities for AI listed here, such as image or speech recognition, also come into play in robotics. Artificial intelligence enables robots to better support people outside of a controlled environment, such as private households or public facilities.

Logical Reasoning

As soon as human knowledge has been formalized and thus made readable for machines, logical conclusions can be drawn from the lowdown based on algorithms. Such procedures are used, among other things, to automate mathematical proof procedures. Some mathematical laws could only be proven with such methods and the high computing power of modern computers.

Automatic Planning

Planning and optimization problems can be solved by artificial intelligence based on collected data. The procedures are used, among other things, in logistics, production planning, or the automated setting of prices. The AI makes its decisions based on optimization algorithms and predicts future events.

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