Data Automation In Documentation: Greater Agility For Data Architectures

September 28, 2021

Data Automation In The Documentation Greater Agility

Documentation is part of every sustainable data architecture. However this is often neglected by developers still work with manual processes. Because developers are judged more by their code than by the correct documentation. One solution lies in data automation.

Pseudo-agile strategies are common in data warehousing today. Teams often work in sprints with scrum meetings and the like. However, most developers are still typing every line of code by hand, using ETL technology from the 1990s. While the deadlines and iterations they must meet are aligned with agile timeframes, the tools and methods they use are not elegant, which is a disadvantage. This is rarely used when defining print. Adequate attention is paid to the documentation. With these restrictions, developers are always pressed for time and take shortcuts to deliver their code. The documentation is always the first thing that is neglected or dropped entirely. Tools for data automation offer a way out.

Data Automation: Documentation Reduces Developer Productivity

The need to write the documentation is a drag on productivity in several ways. When developers take regular breaks to document what they’ve done, they have to disrupt their workflow and write less code. If they postpone the documentation, for example, to confirm last week’s code on Monday, they will forget a lot of what they did. And the more productive developers were, the more they forgot.

In a work culture designed for the short term and where the key is to deliver code on time, the documentation is viewed as a nice-to-have and may not even be checked by those responsible for data governance. Only in retrospect, when the architectures are unclean and challenging to maintain, or when one of the developers leaves the company, and a new specialist comes to replace him, does the value of precise, standardized documentation become apparent.

Sustainability Of Data Architectures

Current tools for data automation allow more flexibility and a much easier chance of the target database than before. The choice of database is no longer a ten-year decision. This also means developers no longer have to start from scratch if the modeling style needs to be changed. The code that developers write now can be modified as required and will last for many years. Because of this, it must be reliable to stand the test of time and how it is documented. Architects have to outlast people and databases; So when a developer leaves the company, the code has to be seamlessly passed on to a colleague.

Advantages Of Documentation With Data Automation

With modern software for data automation, the documentation problem is wholly removed from developers’ schedules so that they can concentrate on higher-value tasks and meet agile deadlines without compromising. All they have to do is click a button, and all of their work will be documented in a level of detail that would otherwise take them hours to complete.

Data automation software is metadata-driven. This means that the user interface is a simplified manifestation of all the metadata behind it and ensures that the data warehouse functions as it is presented. This out-of-the-box documentation means that every action by users as well as every element and structure within the architecture is saved, such as:

the program code itself
Lists of columns and objects, who created them, whether they are in specific jobs, and so on
Transformations
Data lineage backward and forwards: where did the data come from, and where did it go after this point?
Data types and all information about the current object that is currently being viewed
Interactions between the various things within the architecture

In-Depth Insight And Quick Troubleshooting

Documentation through Data Automation is like a roadmap going back through the project developers were working on. It provides hyperlinks to each stage of the process so developers can click in and see the code and structure. It maps everything that developers should create manually but often not do for the various reasons just mentioned. So deep that creating it manually would be too time-consuming to be productive while writing code.

Developers would need to create a detailed spreadsheet and then use Visio tools to develop appropriate flowcharts. Doing this for an entire architecture would take months of work without an automation solution. Such extensive documentation means that errors can be found and corrected much faster. Instead of going through poorly documented code by hand to find the fault, the automation solution highlights incorrect code in red. This not only helps you find the problem quickly. It also prevents one from working on good code that has been mistakenly diagnosed as faulty.

Data Automation: Eliminate Banal, Redundant Tasks

When discussing the pros and cons of data automation, it’s essential to remember that human creativity still comes first. It is complemented by automation tools that eliminate repetitive, manual work. This enables developers to be tireless and is more creative. In many areas of data warehousing, however, creativity and sensitivity are undesirable and even harmful. Documentation is precisely the kind of mundane, redundant work that is ideal for automation.

ALSO READ: Digital Asset Management: How Companies Choose The Right System

Digital Asset Management: How Companies Choose The Right System

Techno Rumours

September 28, 2021

Digital Asset Management How Companies Choose The Right System

Republishing and adapting content requires little creativity but is often associated with a lot of effort. The question is, therefore, no longer whether but which solution companies need for digital asset management to support their employees in marketing and sales.

Digital Asset Management (DAM) systems are essential tools for any marketing, creative, or sales team today. The software helps to optimize the content processes and improves the flexibility of the groups in the long term. More and more companies are therefore opting for a DAM system to better support their employees. But you are faced with a difficult decision when choosing the suitable DAM model: on-premise or a SaaS solution.

Digital Asset Management: On-Premise Model

An on-premise DAM is an internal system usually available from third-party providers for a flat rate and is operated on the company’s hardware. It offers more control and is particularly interesting for companies that use digital asset management to manage data subject to very high-security requirements. While this is rarely the case, given the type of materials a marketing, creative, or sales team typically works with, it can happen.

In addition, on-premise systems offer more options for customization on average. This is particularly beneficial to companies that want to implement particular requirements and rather unusual functions in their DAM. However, this also means that onboarding and training in using the system must be organized and carried out internally. At the same time, there is only limited support from the provider, who is often limited to the essential functions of the software itself.

The initial costs of an on-premise solution are relatively high compared to SaaS solutions. In addition, in the long term, the working time that IT staff spend on the administration and maintenance of the system must also be taken into account. The need for additional data storage capacity can also result in additional costs. The system’s scalability is correspondingly inflexible, whereby scaling upwards can become expensive very quickly, depending on the size and storage medium.

Digital Asset Management: SaaS-Based System

A SaaS-based DAM, or called a cloud DAM, is managed by a third-party provider. Essential things such as onboarding, training, administration, updates, and the provision of support and flexible scaling options are often already integrated. Various package options allow users to book and pay for precisely the functions they need. The system is then pre configured based on these requirements and made available as a plug-and-play solution. Procedures can also be flexibly adapted to changing conditions, with the service provider offering additional support with its expertise and advice. This flexibility also extends to the scalability of the system.

Also Read: IT Trends 2022: Companies Will Rely On These Technologies In Future

Comply With The Guidelines Of Digital Rights Management

Collective security measures to protect data help ensure that companies always follow the strict guidelines of Digital Rights Management (DRM). A media database software provides an overview of the user rights for all existing digital media and supports the introduction of efficient access rights for every user.

The fees for SaaS-DAM are usually charged monthly, sometimes quarterly, depending on the cost model or contract. The price depends on the services included and the scope of use. This allows companies to scale up and down quickly and easily, depending on the project situation. Conversely, this means that the costs can be reduced accordingly if there are fewer active projects.

Which DAM Model Suits Which Company

For whom, which model is best suited depends heavily on the requirements and the basic technical requirements. When choosing a solution, companies must ask themselves the following questions:

What adjustments are required? How far do they differ from the standard options?
Which compliance guidelines do users have to observe? Can the existing solutions cover the procedures?
Who will need access from where?
How flexible and scalable does the system have to be?
What resources are available?
How well is your own IT department set up?

Companies can use these questions as guidelines in the decision-making process. Based on these guidelines, it can generally be said that on-premise DAM is ideal for companies that, for example, require non-standard adjustments concerning product integrations and are bound by strict legal compliance standards concerning digital assets. In this way, access guidelines and authorizations can be managed and controlled independently, with the company can precisely regulate external access.

However, you need to understand that having a dedicated IT department is critical when choosing an on-premise DAM. This must have the appropriately trained staff and the time required to configure and manage a DAM system. Sufficient internal resources such as computing power and storage capacity must also be available to handle this resource-intensive system. Upward scaling is always associated with costs and time since additional resources usually have to be procured first.

Last but not least, on-premise DAM systems are physical systems. At the time of purchase, they are new and competitive. However, they rarely age with dignity in competition with new technological developments. As a result, companies will at some point have to grapple with the cost of replacing them – and the inconvenience, if not downtime, that this transition period will cause in their business.

SaaS-Based DAM Systems Meet Compliance Standards

In contrast, companies that do not have the necessary IT know-how for self-administration benefit from automated updates. On the one hand, this means less work for the company’s own IT teams, and on the other hand, the solution itself has a longer runtime. This is regularly brought up to date with the latest technology employing system updates from the providers. Sound SaaS-based DAM systems meet basic compliance standards such as GDPR and DPA and are certified for essential security standards. In this way, you guarantee continuous data protection in the DAM system and compliance with security requirements.

Especially in today’s world of remote work and home office, SaaS-DAM is particularly suitable for companies that have to guarantee continuous access to assets for their employees. Since it is a cloud-based solution, anyone inside or outside the company can access the holdings with permission, even external stakeholders. At the same time, thanks to its cloud properties, SaaS-DAM offers the ideal prerequisites for those who act in a highly flexible manner and want and need to scale efficiently.

ALSO READ: Supplier Management: How Manufacturers Identify Risks In Supply Chains

Supplier Management: How Manufacturers Identify Risks In Supply Chains

Techno Rumours

September 28, 2021

Supplier Management How Manufacturers Identify Risks In Supply Chains

In many areas, the pandemic disrupted what was already fraught with risks – including logistics. Suppliers could no longer deliver or provide to the usual extent, and supply chains collapsed. The effects on production were devastating. Supplier management allows the dangers to be identified in advance.

The effects of the corona pandemic on supply chains were felt on all sides. The crisis only revealed what was already there: the vulnerability of supply chains. companies that purchase their goods from a few suppliers in the same region have suffered massively from the pandemic. The imposed lockdowns – the dependency on individual suppliers, became apparent. Supplier management offers a solution for this. “Such chains, which are susceptible to failure, could have been identified in advance through analyzes,”. The management consultancy is active worldwide and specializes in strategy and process consulting and factory, production, and logistics planning.

Supplier Management: Analyzes Reveal Susceptibility To Failure

For manufacturing companies in the industry, the supply bottlenecks caused by crises led to production downtimes and a drop in sales – especially in companies that rely on the just-in-time principle and thus designed their supply chains on redundancies. To prepare as best as possible for incidents caused by the Corona crisis, companies should ensure transparency in the supply chain. For this, the establishment of systematic supplier management is essential.

“Such an organization plays an essential role in the risk assessment of supply chains,”. As early as the supplier development phase, the managers can identify risk areas and run through possible failure scenarios with the help of the Failure Mode and Effects Analysis (FMEA). In production, the FMEA is already a standard method for identifying possible disruptive processes. However, the way can also be easily transferred to logistics chains. Potential risks and bottlenecks in the delivery can be identified and eliminated in advance.

Early Warning Systems And Cockpits: Tools For Supplier Management

Early warning systems and cockpits as tools can also be helpful and support supplier management. Various criteria and key data can be implemented in these critical figure systems – tailored to the industry and the company. With the tools, tolerances can be taken into account and differentiated according to the forms of delivery.

The critical figure systems provide crucial data on the demand side, giving companies an overview of the delivery performance of their logistics chains. “The automotive industry has come a long way here and serves as a pioneer,”. Still, they can also be used for other sectors, primarily since suppliers supply car manufacturers and other companies. These then benefit from standards that have been established and which they can apply to other areas.

The Flexible Design Of Internal And External Networks

In addition, it is also essential to make networks more flexible. Suppose goods can be obtained from different suppliers, and suppliers can be changed quickly in bottlenecks. In that case, companies can react to fluctuations in good time and avoid production downtimes. Continuous network monitoring provides an overview of changes in performance and shows how individual parameters are changing. In addition, unique procurement platforms offer a high degree of flexibility, as they use different networks. Instead of relying on one supplier or one region, production companies have access to a whole network of suppliers. In this way, companies can create redundancies and switch to multiple sourcing.

In addition to this external supply network, i.e., the cross-location exchange of inventory and delivery data. If companies have an overview of the stocks at all locations, they can move goods internally and thus react to fluctuations at short notice and without great effort.

Supplier Management And Flexible Networks Increase Stability

The systematic supplier management and the flexibilization of the networks guarantee companies a high degree of stability, which is the basis of any production security. “If companies can ensure this stability, customers are even willing to pay a higher price,”. If customers order an article online, for example, and receive a selection from different manufacturers, they would usually opt for the more expensive product delivered to them faster.

In the pandemic, the supply chains were massively disrupted by imposed lockdowns. This led to supply bottlenecks, production losses, and a collapse in sales. However, if companies have supplier management in place, they can identify potential risks and incidents in advance and counteract them. Early warning systems, cockpits, and monitoring are supportive means here. In addition, the flexible design of the external and internal networks is crucial to react quickly to fluctuations.

ALSO READ: AIoT – Is This The Future Of The Internet Of Things?

AIoT – Is This The Future Of The Internet Of Things?

Techno Rumours

September 27, 2021

AIoT - Is This The Future Of The Internet Of Things

According to Statista, there were 30 billion IoT devices in 2020 and 75 billion in 2025. All of these devices generate huge amounts of data. However, due to stringent processes, outdated data processing tools and faulty analysis methods, around 73 per cent of the data remains unused.

To get the most out of IoT systems, companies need AI. Only then can specialists interpret this data and derive insights and forecasts. The solution that tech experts are currently seeing is Artificial Intelligence of Things (AI + IoT = AIoT ). IoT is still hype. This means that the potential of AIoT cannot yet be properly classified. In the short term, the possibilities of AIoT tend to be overestimated – but underestimated in the long term. Here you can find out what you should bet on if you are considering using AIoT.

AI + IoT: The Perfect Symbiosis

IoT solutions are multi-level sensor devices that collect large amounts of data and send them to the cloud via wireless protocols. Artificial intelligence is the ability of a machine to interpret data and make intelligent predictions. IoT devices use AI to analyze and react to the collected sensor data. AI and IoT go together perfectly. Neither AI without IoT or IoT without AI make sense: IoT data alone doesn’t say anything, and AI always needs data for food.

Gain Additional Insights

If companies equip their IoT systems with AI functions, they can gain additional insights into IoT data that would otherwise be lost. In this way, they increase the benefits of existing IoT solutions. IDC compared two groups of companies – the first used the AI + IoT combination, the second only IoT. The companies were asked about these six goals: Acceleration of internal processes, improved employee productivity, quick reaction to risks and failures, rationalization of processes, new digital services and innovations, and cost reduction.

The result is not surprising: AIoT companies appear to be more competitive than IoT companies because they are more likely to achieve each goal, with differences in the double-digit percentage range.

AIoT: Status And Risks

The AI focus of European countries on IIoT is partly because the AI area is currently overregulated. While US and Chinese companies are working on sensitive applications such as automated facial recognition, European companies face data protection issues. On the other hand, there are open legal questions about liability and intellectual property. This unsettles companies because they do not know who data belongs to and what they can do with it.

One danger of this over-regulation is that foreign companies, which have more options, develop AI solutions in all value chain stages (from marketing to production to service). At the same time, German providers can only offer AI services for IIoT to a very limited extent.

Marco Junk, Managing Director of the Bundesverband Digitale Wirtschaft, describes it as follows: “As a country of mechanical engineering, we have to realize that in the future, added value will no longer lie in the machines alone, but in the AI-based services on and with our machines.” Now I will decide “whether in future we will only be suppliers of our machines for the providers of AI services or whether we will integrate these services ourselves”.

Slowly, however, the ball is rolling: the European Commission has taken the first steps. In the White Paper on Artificial Intelligence, she presented proposals for designing a European legal framework for AI applications and political options for action to promote AI because AI is a technology that, in practice, often cannot yet do as much as one thinks. Regulations and uncertainty, at least in Europe, meaning that it is unclear where and how AI can be used. Therefore, AI is currently overrated in some places. However, especially at AIoT, it is the perfect technology to generate added value. Here are a few examples of where AIoT works and why you shouldn’t underestimate it.

ALSO READ: The Advantages Of Networks – An Overview

How IoT Is Changing The World

Predictive Maintenance

Thanks to AI-based systems for predictive maintenance, companies can obtain usable insights from machines to predict device failures. According to Deloitte, such solutions lower per cent and increase equipment availability by 10-20 per cent. Many companies have been using this approach for years, including the German compressor manufacturer BOGE. Its products are used in areas where downtime can have fatal consequences, such as in the pharmaceutical and food industries or semiconductor production.

The company used software for predictive maintenance to minimize the risk of failure. The software can provide specific information on how many hours or even minutes it will still take before a technical problem arises on the machine, which makes maintenance work easier to plan.

Remote Monitoring Of Patients By AIoT

During the COVID-19 pandemic, more and more healthcare providers are turning to technology. They rely on remote monitoring systems to treat COVID-19 patients while reducing the risk of infection for medical staff. An example of such a system is an AI-based solution from Tyto Care. It diagnoses patients using data recorded by the Tyto Care-AIt and the mobile phone. The special AI algorithms detect problems such as swollen tonsils, sore throats and lung diseases. This allows doctors to make a diagnosis without touching the patient.

Self-Driving Cars

At the moment, only “highly automated driving” (or “piloted driving”, level 3) is permitted in Germany. In other words, the car can almost completely take over the journey, but responsibility remains with the driver. AI is currently used in autonomous driver assistance systems (ADAS) and fulfils several tasks: reducing the fisheye effect in videos from onboard cameras to monitoring the situation on the road. Technologically, on the other hand, the automotive industry has already arrived at autonomous driving – autonomous cars are being tested worldwide.

AIoT For Improved Business Models

Rolls Royce is best known as a car and turbine manufacturer. The company used to manufacture engines and then sell servicing services for those engines. If the engine failed, it had to be serviced for Rolls Royce, which was an additional business. Today they have completely changed their business model: they sell an hourly rate for the operating time of the engines. Based on the IoT sensor data of the motors, they optimize the performance to have as little maintenance time as possible and to intervene early so that the motors remain in operation for as long as possible. For the customer, this now means that he pays for exactly what he wants to pay for, namely the operating performance of an engine.

What do we learn from it? IoT is the future of the Internet of Things – if it is implemented and used correctly. A full-stack provider such as Softeq has the right expertise to turn data-poor devices into data-rich machines and transform data into insights.

ALSO READ: No-Code And NLP: How Cloud-Based Software Can Relieve Developers

Networks: Advantages Of Networks And Its Overview

Techno Rumours

September 27, 2021

5G is a real milestone in cellular technology. Companies can even set up their own 5G network for Industry 4.0 or remote working networks. Here is an overview of the advantages of campus networks and the solutions that telecommunications providers offer.

Up to 4G, the matter was straightforward: With earlier mobile radio technologies, voice communication was first in the foreground, then later the use of the Internet and many applications based on it. 5G is the first generation of mobile communications in which the use cases, such as campus networks, were already established in advance, beyond telephoning and surfing.

Industry 4.0 Provides A Boost To Digitization

The driver is Industry 4.0, i.e., the idea of the digitized factory with networked cyber-physical systems and the goal of manufacturing individualized products down to batch size one instead of millions of precisely identical products. Before 5G, there was no satisfactory solution for the flexible networking required for this. Cables do not allow the systems to be mobile. LLAN struggles with radio shadows and dropouts when transitioning from one radio cell to another. Earlier portable radio standards were too slow or had too high a latency, which prevented real-time applications.

All of that changes with 5G. It allows data transfer rates of up to 10 gigabits per second; the latencies should be close to a millisecond for future releases. And as a mobile radio technology, there are no interruptions when the handover to the following radio cell, which is essential for driverless transport systems, for example.

Faster In The Campus Network

Probably the most outstanding advance with 5G is not the faster technology, but the regulation by politics. Because with 5G, the legislature provided so-called campus networks from the beginning and kept frequency ranges free for them. Companies, universities, and trade fair organizers can apply for such frequencies and set up a self-sufficient 5G network on their premises. The data is processed on the edge, i.e., in computers on the premises. Such a network is highly available and extremely fast, which allows for entirely new applications.

For example, the Fraunhofer Institute for Production Technology IPT in Aachen uses 5G in a milling machine in which it produces prototype components for MTU Aero engines. A vibration sensor communicates with the device via 5G so that vibrations can be compensated for in a flash and damage to the components can be avoided.

Set Up Campus Networks In Slices

An utterly self-sufficient network is only one variant of campus networks. The operators of the cellular networks also offer network slicing. There, the campus network is set up in the public network but sealed off with guaranteed bandwidth, even if many people nearby are surfing with their smartphones simultaneously. This variant is interesting for smaller companies that shy away from investment. Still, the disadvantage is the more significant latency since the data runs through the data centers of the network operators.

Such scenarios are interesting for companies that want to network their locations worldwide, including with suppliers. Small campus networks are then linked together to form an extensive, virtual 5G network; the machine in a plant in China appears to be located directly in the plant. In the coming releases of the 5G standard, mechanisms are provided with which machines can even reserve more bandwidth on their own if they have to send more significant amounts of data.

Industry 4.0 and 5G are a perfect pair, which is why the first applications are coming from the manufacturing industry, above all from the automotive industry, where the first campus networks are also in place. So far, however, these are still based on 4G or combined 4G / 5G technology. However, this focus on the manufacturing industry is a narrow view. Many applications are just emerging, and there are tons of exciting ideas. For example, Airbus controls its unmanned airship Altair from a distance of up to 250 kilometers, and drones can also be controlled via 5G to inspect pipelines. Autonomously driving cars can communicate with a parking garage via 5G and are parked autonomously.

Use Of 5G: From Healthcare To Football Stadiums

The 5G standard is set to move in quickly in healthcare. For example, a doctor could remotely give instructions to an emergency aid worker in the event of an accident. In the future, data will be transported in hospitals instead of patients. The ultrasound is then recorded with a small hand sensor on the bedside, and the results are transferred to the cloud in the clinical information system.

New ideas are also opening up in the sport. VFL Wolfsburg has equipped the Volkswagen Arena with 5G to offer the audience a unique live experience. They can point their smartphone at a player and receive real-time information about it as augmented reality, such as their duel values. Live events and e-gaming are merging into a new form of sport. Viewers can expect other similar applications at the Olympic Games in Tokyo, postponed to 2021. Network operator NTT Docomo has already announced a firework of ideas with augmented and virtual reality.

Many people who are currently holding out in the home office are probably asking: What effects does 5G have on my work and office jobs in general? The cloud is essential for remote work, but fast data connections are also necessary. 5G will take mobile working to a new level and work in the company’s office. Where a lot of data is exchanged with the cloud, small 5G campus networks – for example, in a building or perhaps just within one floor – can replace the rigid network with LAN cables and offer more flexibility.

Virtual Campus Networks On The Advance

One technology that is likely to cause a sensation in the coming years is virtual networks. Specialized hardware and software were built from a single source in the earlier generations of mobile communications networks. A virtual 5G network, on the other hand, is just software that runs on standard servers. This has the same transmission properties, but it is much cheaper, and, especially with campus networks, it is also ready for operation more quickly. And it reduces the users’ dependence on the system suppliers. This technology is prevalent in Japan. One of the first cloud-native 5G campus networks has the co-creation space Ens? in Munich, the European innovation center of the NTT Group.

ALSO READ: Enterprise Software: How To Improve The Usability

Enterprise Software: How To Improve The Usability

Techno Rumours

September 27, 2021

Enterprise Software How To Improve The Usability

User interfaces are easy to use have become standard in consumer sector. there is still lot of catching up to do with Enterprise Software. Why this is so and how B2B companies can significantly improve the user experience for business applications.

Usability is a decisive criterion in the use of software and thus also in software development. But while the user interfaces of apps and online shops in the consumer sector are primarily self-explanatory, there is still some catching up with business software. Excel lists and faxes are still used for orders. In addition, the input masks on the web are often complex and confusing.

Enterprise Software And Business Software Is Characterized By Functionality

There is a simple reason why many business applications are not user-friendly: B2B Enterprise Software is traditionally characterized by its functionality. The software ergonomics came later. On the other hand, in the consumer area, the topic of usability was considered from the start. Because: The users are usually not particularly tech-savvy. If you use an app, its functionality must be immediately apparent via an intuitive interface.

However, approaches to optimization such as font size, color or buttons are not so easy to change with B2B software. Many applications map highly complex processes. Changes to the surface often affect the system architecture. The effort for improvements is therefore much higher than in the B2C environment.

The Boundaries Between B2C And B2B Enterprise Software Are Blurring

Despite these challenges, usability is also a must for business Enterprise Software today. Websites, apps, online shopping – everyone comes into contact with the software regularly. The private and business sectors are increasingly mixing up. The use of business tools alternates with personal purchases and the use of social networks. This direct juxtaposition of B2B and B2C applications increases users’ expectations: They want to be able to use business applications just as intuitively as they are used to in their private lives.

User-friendliness is also becoming more and more critical due to the increasing flood of information that users are confronted with today. The patience to familiarize oneself with company has noticeably decreased. Operating problems lead to frustration. With complex B2B applications – for example, payroll and financial accounting – it is, therefore, all the more important not to overload the user interfaces and menus.

Usability Leads To Cost Savings And Satisfied Users

Ultimately, an improved user experience saves time and money because users can complete their tasks faster. And it leads to higher user satisfaction – an aspect that should not be underestimated, especially in the cloud age. Companies can change Enterprise Software providers quickly and easily in the cloud if they are not satisfied with their user experience.

The transparency of the offers is also increasing. Intuitive systems that require neither training nor extensive tests are in demand. The user experience in the B2B environment always remains a compromise, especially when it comes to software for financial accounting with thousands of functions.

ALSO READ: Business Analytics: 5 Key Big Data Trends For 2021

Only Show What The User Needs Next

With systems that can be operated intuitively, it is always apparent what to do next to the user. This claim can also be implemented in complex Enterprise Software – in that, not all functions are displayed at once, but only the next step in each case. The surface becomes even tidier if it is tailored to the respective user. For example, if an employee only needs customer master data, this is displayed, including the corresponding operating elements. He can then use the settings to adapt the user interface to his way of working. This clarity saves time, as the user can concentrate better on his tasks and find the required functions more quickly.

Contextual Help With Business Software

Many B2B applications leave the user alone in the event of difficulties. Intuitive Enterprise Software, on the other hand, recognizes itself if there are problems. As soon as the user gets stuck at one point, the software offers contextual help that shows him how to proceed or that specific calculation processes are currently in progress in the background, and he has to wait. Explanatory texts or videos can be displayed in a context-sensitive manner that guides the next steps in the software – for example, how an invoice can be created or a booking can be made.

An analysis of user behavior is also functional. For example, if a user always navigates to the same area and never uses specific input masks, the software can hide these elements in the future. In addition, the company software can prepare settings that are used repeatedly, such as evaluations from data that the user regularly creates. Optimization options like this are possible through artificial intelligence, which practically evaluates telemetry, i.e. the recording of where the user often moves on the surface.

Chatbots Provide Interactive Help With Company Software

Chatbots, which meanwhile already support customer support on many websites, offer particularly timely user support. Often, speed is essential to prevent frustration for the user or customer. According to Forrester, 63% of customers leave a vendor after just one bad experience, and nearly two-thirds don’t wait more than 2 minutes for help. Chatbots can usually answer frequently asked questions automatically. This relieves the employees because customer support only receives inquiries that require human qualities. Speech recognition can also improve the usability of the software. Above all, the combination of chatbots with AI ensures better usability: Bots can learn to understand people and their problems with operation.

The Push Of User-Friendly Business Software

“In the past 20 years, user-friendliness in B2B software has often been neglected in favor of a variety of features. However, the developers are in a phase in which the software is taking the step into the cloud. In this step, the old desktop interface has to be adapted and modernized for use on the web,”.

“That’s why there is often a real boost in user-friendliness from B2B software: The step into the cloud offers an ideal opportunity to clean up, rethink and modernize. And it is time to update: Today, better usability is a necessity to survive the competition. Well-designed software ensures satisfied users who have also become more demanding with their expectations of the user experience of their work system. “

Sage is one of the market leaders for IT systems used in small and medium-sized companies. These enable more transparency and more flexible and efficient processes in the areas of accounting, company and personnel management. Millions of customers worldwide trust Sage and its partners regarding solutions from the cloud and the necessary support.

ALSO READ: No-Code And NLP: How Cloud-Based Software Can Relieve Developers

No-Code And NLP: How Cloud-Based Software Can Relieve Developers

Techno Rumours

September 27, 2021

No-Code And NLP How Cloud-Based Software Can Relieve Developers

Tools for no-code and natural language processing are becoming increasingly important in software development. Guest author Carsten Riggelsen from AllCloud explains how employees without programming knowledge can use it to advance their company’s digital transformation.

The interaction between man and machine often follows a pattern: At the beginning, new developments are complicated, expensive, and operation is a matter for experts. Innovations then continuously make them more accessible until laypeople can also use the latest technologies. The machine is adapted to the natural ways in which humans interact. We no longer interact with punch cards with a computer but with a mouse, keyboard, pen, touch or voice. New technological approaches such as No-Code and Natural Language Processing (NLP) can revolutionize the business world.

No-Code: Satisfies The Hunger For New Software

Startups developing tools for no-code are springing up like mushrooms and are being generously endowed with venture capital as they help satisfy the ever-growing hunger for software. Because no-code reduces the hurdles to developing new software: Easily understandable user interfaces serve as development environments within which, for example, individual applications can be created from prefabricated modules. Recommender algorithms also provide support with further recommendations, similar to “Apps that use this function also use …”

In the meantime, robots can even be programmed by using a particular solution that records the movements and actions of a person and uses them to create the code for the robot movement. A robot arm only needs training movements, for example, to solder, punch and screw in the proper order and the right places.

Make Data Queries Using Natural Language Processing

The well-known intelligent assistants have been working on call for a long time. They recognize and interpret simple verbal commands. With the computing power from the cloud, much more complex tasks can now be carried out, such as extracting information from complex amounts of data that would otherwise require queries in code. For example, there is an add-on to business intelligence software that runs in the cloud of a well-known hyper scaler that enables precisely that: users can query data in natural language.

You can’t just do this with ready-made questions and sentences or specific syntax. The add-on can process different speaking habits and industry-specific expressions and contexts because intelligent technologies convert natural language into queries that deliver the results that are searched for. So instead of waiting weeks for business intelligence analyzes, data-driven findings can be called up ad hoc and without prior technical knowledge.

NLP Paves The Way To Data Democratization

No-code and NLP are revolutionizing the way employees are involved in the digital transformation of companies. While no-code lowers the entry barrier for creating software, NLP paves the way to data democratization. This development is progressing rapidly, as the business mentioned earlier intelligence example shows: The interaction in natural language with the robust IT systems of a leading hyper-scale is an absolute game-changer. Because access to valuable information is difficult in the company, competitive disadvantages arise. This is where the Citizen Data Scientist enters the company’s internal stage. Now data analysis is also possible without much-asked and busy experts. In increasingly data-driven business models, this becomes more important with each byte stored.

No-Code And NLP: Smaller Budget And Faster Implementation

No-Code makes the toolbox of the developer access to users. A development team may need months to develop an application. On the other hand, an innovative citizen developer can use no-code tools with a small budget to set up applications that specifically address their daily pain points. Companies can leverage the innovation potential of their employees directly where the applications are used regularly.

But people will also be needed in the future for the most complex tasks. There is still demanding work involved in software and data analysis, as in training an algorithm. No-code and natural language processing relieve developers and data scientists of tedious, more straightforward tasks, and they can focus more on the important work that moves their organization forward.

No-Code And NLP Support Digitization Strategies

The advantages show that it is worthwhile for many companies to introduce No-Code or NLP as part of the digitization strategy. However, the solutions required for no-code or NLP are increasingly relying on cloud computing for hyper scalers. Cloud migration, therefore, lays the foundation for benefiting from these innovations. And then expertise in dealing with the solutions of the hyper scalers is required to operate the current applications and set up new ones. If there are no internal experts available for cloud migration, operation and setting up new apps, companies should look at cloud enablers. In today’s world, it is worthwhile to acquire such skills via outsourcing.

ALSO READ: Capital Group: 5G Will Change The World But In Phases

Capital Group: 5G Will Change The World But In Phases

Techno Rumours

September 26, 2021

Capital Group 5G Will Change The World But In Phases

When looking at telecommunications technologies and digitization trends that can change the world, 5G is usually mentioned as one of the first. “Once the new technology takes hold, it can revolutionize many industries,” says Andy Budden, Investment Director at Capital Group in Singapore. “It will take some time until then, and different companies will benefit at different times.” The expansion of the infrastructure and the time lag between availability and actual use made 5G a long-term issue.

Technology Changes The World

New telecommunications technologies are generally significantly faster than their predecessors – 5G is estimated to be around 10 to 100 times faster than 4G. However, the latest stage of development offers more than just quick downloads. Shorter latency times, more network capacities and longer battery runtimes, and the resulting possibility of allowing devices to communicate with one another – i.e., the Internet of Things – are the real potential.

However, it takes different lengths of time to set up 5G networks in different countries. While construction is just starting in the USA, it has already progressed further in China. Several physical obstacles need to be taken into account. “There will be no quick change, and to identify companies that will benefit from the development, you have to remain flexible, diversify and choose the right time,” says Budden.

Many Industries Benefit, But At Different Times

Companies that could benefit from 5G could be divided into three groups. On the one hand, there are the providers of the technology, primarily technology companies. Their sales will likely rise, but this will not be reflected in profits until the middle of the decade, as setting up the infrastructure will require high investments. In this sector, less attractive investments are currently to be identified.

The second category would consist of the facilitators of 5G – i.e., companies that set up the infrastructure and supply the necessary components. “The demand for cell towers, network equipment, devices, components, and data storage needs could grow dramatically over the next few years,”. “Companies in this area therefore currently appear more attractive than pure technology providers.” This category includes companies such as the cell phone tower provider American Tower Corporation and companies from the semiconductor industry such as ASML or Samsung, leading the development of 5G end devices.

The third group is the technology users – i.e., those industries that 5G could significantly change. Central areas of application could be the automation of factories or autonomous driving. There is also considerable potential in the health sector – for example, through computer-aided operations – or in the energy sector. “In the energy sector, 5G could enable remote control or repair of systems as well as intelligent networks,”.

Benefit Wisely Today

To benefit from the enormous potential of 5G at an early stage, investments have to be made with caution and planning – for a fund that largely relies on technology, and it is still too early. “The truly revolutionary opportunities are likely to be found among the companies that will end up using 5G,” says Budden. “But this area is still at the beginning. Flexible investments in various topics and the control of whether the investment theme and investment opportunities develop in the right direction over time guarantee a stable approach from our point of view. ”

This category includes companies such as the cell phone tower provider American Tower Corporation and companies from the semiconductor industry. However, the latest stage of development offers more than just quick downloads.

ALSO READ: Business Analytics: 5 Key Big Data Trends For 2021

Business Analytics: 5 Key Big Data Trends For 2021

Techno Rumours

September 26, 2021

Business Analytics 5 Key Big Data Trends For 2021 (1)

For the next year, the data analytics provider Qlik has identified five fundamental big data and data Business Analytics trends. The most important include comprehensive data, data ops, and self-service analytics, as well as shazam of data.

According to Qlik, five trends in business analytics, big data, and data analytics will determine next year. Developments include Wide Data, Data Ops, and Self Service Analytics, as well as Shazam of data.

Business Analytics: Big Data Becomes Wide Data

Thanks to scalable cloud solutions, the capacity limits of in-house IT infrastructures are no longer a limiting factor in big data environments. The challenge of the hour is “Wide Data.” Attention turns to the fragmented, widely ramified data landscapes that have arisen from inconsistent or incorrectly formatted data as well as independent data silos.

In the last five years alone, the number of databases available for various data types has doubled from 162 to 342. “Companies that succeed in combining this data in a meaningful way in the future will have a clear advantage,”.

Data Ops And Self Service Analytics: More Agility For Data Usage

While data analytics has long since found its way into the business level thanks to modern BI technology and self-service tools, there is still a lack of agile options for data management. The solution is called: “Data Ops.” This approach makes it possible to use automated and process-oriented technologies to increase the speed and quality of data management. For this, on-demand IT resources are used, tests are automated, and data are provided.

Thanks to Data Ops, 80 percent of the core data can be systemically delivered to business users. “With Data Ops in operational data management and self-service analytics on the business side, a flowing process can be achieved across the entire information value chain. Synthesis and analysis are intertwined. “

Business Analytics: Intelligent Metadata Catalogs As A Link

The demand for data catalogs is increasing to localize, record, and synthesize raw data in the distributed and diverse databases. The metadata catalogs will increasingly be equipped with AI to enable active, adaptive, and fast data provision in the coming year. This is the prerequisite for the agility made possible by the use of Data Ops and self-service analytics.

Development Of Data Competence As A Service

By linking data synthesis and data analysis, the use of data can be further advanced. “However,” .”no matter how good technologies or processes are, they will not be of any use if people are not on board. It is not enough to make the tools available to users and hope for the best. The key to success will be helping employees become familiar with reading, working, analyzing, and communicating data. “

Many companies want to promote their employees’ data knowledge in the coming year and are specifically looking for partners who offer software, training, and support in the SaaS model (Software as a Service). The goal: To improve data know-how so that Data Ops and self-service analytics can interlink and data-based decision-making can assert itself among employees in everyday life.

Business Analytics: Shazamen Of Data

The advances in data analytics have been enormous over the past few decades. However, experts see the biggest milestone still to come: the “shazam” of data. Most of us know Shazam, the famous app that can identify and provide information about playing songs. This concept is currently being expanded to include numerous areas. “In 2021, we will also experience ‘Shazamen’ for data in the company”.

“It will be possible to take a closer look at the surroundings of data: where do they come from, who has used them, what quality are they, and how have they recently changed?” Algorithms will help the analysis systems to recognize data patterns, Understand anomalies and propose new data for further analysis. This will make data and analytics leaner, and we can work with the right data at the right time. “

Business Analytics: New Ways Of Handling Data

“One thing is certain: In the future, the handling of data will go far beyond search, dashboards, and visualization. We will communicate with digital devices using alternative input techniques such as thoughts, movements, or even on a sensory level. The purchase of CTRL Labs, the start-up for neuro interfaces, by Facebook or Elon Musk’s Neuralink project, which is working on human-machine interaction, are the first harbingers of what is to come. In 2021, some of these breakthrough innovations will begin to transform the way we work with data. This presents enormous opportunities for all of us, but it harbors the risk of abuse. A sense of responsibility is required here,”.

“A holistic view of data competence and ethics is necessary so that people can make the right decisions when dealing with comprehensive data. Data Ops and self-service are the trends that help to properly use data scattered throughout the company to continue to be successful in the digital age.

1...53 5455Page 55 of 55