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API Management: Apply the Power of APIs to Business Challenges

Apply the Power of APIs to Business Challenges

The report “API Management Market” shows the potential of APIs economical growth.The API management market is estimated to grow from USD 606.8 Million in 2016 to USD 2,665.3 Million by 2021, at a Compound Annual Growth Rate (CAGR) of 34.4%. Major growth drivers of this market are:

 

  • Increasing demand for private and public APIs
  • Growing popularity of Web APIs
  • Growing number of mobile devices

 

What is an API?

In the debate on digitization, which has been going on for years, APIs offer a concrete opportunity for many companies to expand their own business at a manageable expense.  Modern APIs are flexible ways of projecting your capabilities to an audience outside of your own team. If done right, APIs enables enterprises to quickly reform the legacy architectures, add value to existing IT assets, and creates new product opportunities or revenue streams.

 

In other words, an API is a communication channel to an application, built with set of customs and protocols that makes a website’s data digestible for a computer. Through it, a computer can view and edit data, just like a person can by loading pages and submitting forms. Depending on their needs, APIs can be used internally, with partners, or made available to the general public.

Making data easier to work with is good because it means people can write software to automate tedious and labor-intensive tasks. What might take a human hours to accomplish can take a computer seconds through an API.  Therefore, sophisticated API management makes it possible to successfully build up coverage and additional business – without having a direct, direct connection to the new target groups.

 

How An API Is Used

When two systems (websites, desktops, smartphones) link up through an API, we say they are “integrated.” In an integration, we have 2 sides, each side have a name. 1stone is the server that provides the API, a program running on the serve. It may be part of the same program that handles web traffic, or it can be a separate one, sitting, waiting for others to ask it for data.

 

The 2ndside is the “client.” This is a separate program that knows what data is available through the API and can manipulate it, typically at the request of a user. A great example is a smartphone app that syncs with a website. When you push the refresh button of your app, it talks to a server via an API and fetches the newest info. The same goes for the websites that are integrated. When one site pulls in data from the other, the site providing the data is acting as the server, and the site fetching the data is the client.

 

APIs Enable Businesses

APIs have emerged as a key element of tech modernization at many businesses. Banks and insurersand also companies such as UBER, eBay, PayPal and Amazon, are using the growth driver API management for a long time. For many, they are the key competitive advantage or even thebusiness foundation. With their ability to link systems and data, they play a crucial role in making IT systems more responsive and adaptable.

 

APIs are programming interfaces that companies use to make information or entire business processes accessible to outsiders. Properly implemented, they significantly reduce the technological and organizational entry barriers for communicating and establishing new business-to-business relationships. Technical interfaces and automated processes simplify what hitherto hierarchically organized sales structures have handled. This is particularly interesting for small and medium-sized businesses that do not have it.

 

Successful API management

The introduction of APIs is often reduced to the use of middleware with different technical features. However, if you want to successfully establish APIs, you need to be fully involved with API Management. It requires profound organizational and technical adjustments, both in IT and in specialist areas. A successful API management architecture is built on three functional components:

 

  • The Management Portal
  • The Developer Portal
  • The API Gateway

 

  • Management Portal

The Management Portal is the hub of internal API managementthat allows administrators to define APIs, deploy APIs, and promote APIs through the environments. Authorization management determines which content users can see and use to what extent. In this way, contractual relationships can be made simpler – they can be partially standardized and automated.

 

  • Developer Portal

 

The developer portal is the face of your API program, providing everything that internal, partner, and third party developers need. Via this portal, App Developers are able to connect with the resources necessary to learn about the enterprise’s APIs and collaborate with peers and with the enterprise.

 

  • API Gateway

Is to secure and mediate the traffic between clients and backends, and between a company’s APIs and the developers, customers, partners, and employees who use the APIs

 

 

APIs is becoming, more than ever again, a requirement for building digital businesses. They enable companies to quickly develop new approaches to serving the needs of a varied mix of users with a whole new set of expectations. Therefore, companies must think of them as central to the application development process and key to competing in the digital economy.

With the new requirements of the digital world, customer- centric IT organizations, and the ever-present need to connect disparate internal systems, managing APIs and API-driven businesses becomes increasingly challenging, companies must ensure developers and partners to be productive and manage, secure, and mediate their API traffic in a best possible way.

 

Sources:

  • The API Management Playbook – CA Technologies
  • The Definitive Guide to API Management – apigee
  • API Management Market by Solution (API Portal, API Gateway, API Analytics, Administration), Service (Training and Consulting, Integration, Support and Maintenance), Deployment Type, Organization Size, Industry and Region – Global Forecast to 2021 – MarketsandMarkets
  • Image – CA Technologies

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A Data Analytics Roadmap

Components of The Data Analytics

The volume of data that governments, businesses and people around the world produce is growing exponentially, animated by digital technologies. Organizations are changing their business models, building new expertise and devising new ways of managing and unlocking the value of their data.

 

Businesses around the world have recognized that data is a hugely important part of their organization. While every organization is at a different stage of “data travel,” whether it’s cutting costs or pursuing more ambitious goals, such as improving the customer experience, there is no way back. In fact, many companies are currently in the phase where data defines and drives corporate strategy.

 

Infosys recently completed a study of more than 1,000 companies with sales exceeding $ 1 billion in 12 different industries covering the US, Europe, Australia and New Zealand regions. The aim of the survey was to obtain a comprehensive overview of the data travel undertaken by the surveyed organizations and to see how they are analyzing their data to achieve more succes.

 

The study found that more than 85% of surveyed companies have an enterprise-wide data analytics strategy. This high percentage is not surprising. However, having a strategy is not everything: there are more aspects that organizations need to consider to successfully exploit the potential of their data. First of all, companies need a defined strategy that covers several areas. Second, according to the strategy, execution must be seamless, and that is the challenge.

 

Developing a sound strategy is the foundation. However, in terms of data, it is no longer about identifying metrics and KPIs, developing management or operational reports, or improving technology. Rather, it should cover all areas of the company. In short, the data strategy is now an important part of the business – this is heralding a shift away from traditional approaches.

The survey also highlighted that surveyed enterprises across different industries are meeting challenges that blocking them from implementing a right data analytics strategy. 44% of them stated integrating multiple datasets across sources as their biggest challenge and 43% are facing the biggest challenge to understand the right analytics technique to be deployed.

 

data analytics

 
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What are the characteristics of a good data strategy?

To begin with, it must be ensured that the data strategy aligns with the overall corporate strategy and is closely aligned with the business objective, it can be increasing growth or profitability, managing risks, or transforming existing business models. In addition, a flexible data strategy is important so that regular reviews and updates can keep up with changes in the business and marketplace and drive innovation – faster, better, and more scalable.

Organizations need to create data strategies that match today’s realities. To build such a comprehensive data strategy, they need to fulfill current business and technology commitments while also addressing new goals and objectives. A good data strategy must be bidirectional to track current business trends and to provide helpful insights for the future. This approach is only possible if companies pursue a multi-level data strategy that includes people, technology, governance, security and compliance, and finally a suitable operational model.

The data strategy must define a value framework and have a revenue tracking mechanism to justify the investments made. About 50% of the study participants agreed that a clear, pre-determined strategy is essential for smooth execution.

 

The best strategy is useless if the execution falter

There are some hurdles that can stop proper implementation of a data strategy. Technology-related challenges can already arise in choosing the right analysis tools, the availability of people with the skills they need, next gen capabilities, and so on. Most of the challenges identified in the study occurred during the execution phase. Although they seem enormous at first glance, they can be addressed with a careful planning. Preparing for multiple regions, locations, suppliers, and talent acquisition and training are a few ways to pave the way for smooth execution.

 

What role do external technology providers play in this?

An experienced external technology vendor can contribute at multiple levels, from helping define business and data strategies that work together, identifying loopholes in existing business models, transforming business and technology solutions to developing, implementing, and maintaining of best-in-class technology solutions.

 

In a world based on data, businesses need to do everything they can to adapt to a customer-centric strategy. Partnering with a high-performance technology provider can help companies better meet their business goals.

 

Digital Trust 2019: Trends in The Artificial Intelligence Era

Artificial intelligence (AI) has rapidly developed in recent years. Today, AI tools are used widely by both private and public sector organizations around the globe. The capabilities of AI now and in the near future are creating extensive and significant benefits for individuals, institutions and society.

The foundation of AI is data and understanding the patterns in these data to make a smarter automated task. The collection of these data is increasingly controlled by regulations and user preferences. Organizations must answer questions such as how to deliver practical compliance with data protection laws and norms when building and implementing AI technology and on the tension between AI and existing data protection legal requirements.

 

If the AI ​​service cannot provide an appropriate level of trust, this data may not be available over time. Without trust, there is no data. Without data there is no AI. As a result, organizations have both an opportunity and an obligation to develop principles, best practices and other accountability tools to encourage responsible data management practices, respect and even reinforce data protection, and remove unnecessary barriers for the future development of these innovative technologies. However, in2019, trust will be essential for success. Below are five forecasts of tensions related with data protection.

 

Trust becomes the new currency

Shakespeare wrote, “Love everyone, trust a few, do no harm to none”. Those vendors who can build long-term trust with their customers have unique added value. Very few will be able to achieve this and thereby increase their enterprise value. Trust will be given a monetary value in 2019 and we will move towards a trust-based economy.

 

Data ethics will become more important as a discipline

The foremost practical question for data ethics is whether there is anything special about data such that collecting, manipulating, and applying it requires a distinct code of ethics. On 20 November 2018, the United Kingdom founded the Center for Data Ethics and Innovation, the first public body to address the “new ethical issues arising from the rapid development of technologies such as artificial intelligence”. The way data is used today is more than just a technical phenomenon. It’s a political, social, and even mythological phenomenon that has consequences for how we organize our lives and express our values. Whatever ethical principles are developed in connection with data, they should account for dynamics that extend beyond technical limitations. Data analytics should be viewed as a phenomenon with consequences beyond technology, and the community should demand that data scientists and practitioners consider those consequences.

In 2019, data ethics as a discipline will become increasingly important in both governments and academia. Most discussions so far about AI ethics have focused on the results of the AI, not the data inputs fed by the AI. These new institutions will focus on inputs and should be taken seriously by providers as they are both a source of best practices and a pioneer for future legislation.

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Everyone will shout, “Trust me!”

‘Trust’ will stand in the slogan or marketing message of all AI and modern technology providers. Although consumers place a high value on trust and integrity, they will only find a few useful landmarks in marketing noise. “Who should I trust?” May not be so easy to answer in the blink of an eye.

 

Surprisingly, consumers will give dubious providers a second chance

Given the hurly-burly and lack of an objective, easy-to-use test of trust, consumers will not really know how to value trust and what action to take when it’s lost. As a result, consumers will not drop these providers in 2019 due to a first breach of trust, which unfortunately continues to support negative business practices. However, these second chances will gradually disappear as consumers learn to answer the question “Why should I trust you?”.

 

Often, data will disappear

This year, some providers that collect data improperly, will get caught and go through legal or/and economic consequences. Others will slip through. But in both cases, nobody will know what actually happened with his data. Many are expected to land in the black market. But on the basis of regulatory requirements of GDPR, industry will be forced to adopt sever guidelines for the use and processing of data.

 

These are all big challenges, as they occur in many technologies with disruptive potential in the early stages. But can the technology industry really talk about trust? As Albert Einstein said, “Anyone who does not take truth in small matters cannot be trusted in large ones”. In 2019, we will see the first generation of AI startups trusted by credible, sustainable, deep-rooted value and not a marketing slogan. Only then will Artificial Intelligence be able to assert itself in a sustainable way to truly change life.

2019: The Year of Data-Driven Management Revolution

Benefits of Data Management

Data is at the heart of the digital transformation, which will accelerate, ever than before, in 2019. Businesses are moving from monolithic legacy infrastructures to modern distributed hybrid cloud infrastructures. Therefore, the protection and management of data must undergo alterations and evolution.

 

So far, we all know that data management is all about managing the data, regardless of the underlying infrastructure.

It includes all aspects of data planning, handling, analysis, documentation and storage, and is present in each department of an organization. By managing data, the objective is to create a reliable data base containing high quality data by:

  • Planning the data needs of an organization
  • Data collection
  • Data entry
  • Data validation and checking
  • Data manipulation
  • Data files backup
  • Data documentation

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Each of these processes requires thought and time; each requires painstaking attention to detail.

 

The main element of data management are database files. Database files contain text, numerical, images, and other data in machine readable form. Such files should be viewed as part of a database management systems (DBMs) which allows for a broad range of data functions, including data entry, checking, updating, documentation, and analysis.

 

Traditional data systems, such as relational databases and data warehouses, have been the primary way businesses and organizations have stored and analyzed their data for the past 30 to 40 years. In traditional storage management, the task is to manage storage hardware and the data it contains in a single system or cluster.Butwith Information Technology becoming more and more Cloud based nowadays (due to industry demanding reliability and scalability in their infrastructure), the Cloud storage system has become a very feasible solution. Various organizations are migrating their data to cloud storage, as they want data to be easily accessible, cost effective and reliable.Storage is today in public / private clouds, in the IoT, at the network edge, as well as on mobile devices and new media using new protocols. There is a new variety of data structures, containers, and interfaces that support data-driven use cases such as analytics, self-service multi-tenancy, artificial intelligence, and machine learning.

 

If we take a look back to 2018, there was not a single data management solution that would combine all of the required core components in one product. To keep pace with evolving business needs and fallow digital transformation, data management solution providers are turning to the open source community in order to provide new tools and capabilities to expand their products. However, as there is a lack of interoperability between products, multiple products still need to be purchased to fully manage and protect data in modern hybrid clouds and new digital environments. This can be a nightmare for administrators in terms of monitoring, reporting, managing, protecting and backup the data.

 

2019 is a year in which data management vendors will expand their capabilities through alliances, acquisitions and native development to offer these key components in one product and to fulfil every business requirements. This will in future simplify data management for administrators and provide the ability to intelligently manage, secure / protect and document everything under one management roof. This will also provide real data management solutions for all data requirements and data usage scenarios in 2019.

 

Data backup & business continuity

Downtime is real and it’s costly. How costly exactly? Depending on the size of the organization, the cost per hour of downtime is anywhere from $9,000- $700,000. On average, a business will lose around $164,000 per hour of downtime. The numbers speak for themselves.

With that being said, ransomware and other malware attacks will continue to increase and evolve to smarter attacks. Along with new data protection policies and strategies, the number of natural disasters and other events that sometimes destroy entire data centers will continue to grow in 2019. This means that data protection and data management will have to evolve towards smarter and more efficient ways to avoid business interruption. All these are reasons why the importance of a good backup strategy and a disaster recovery plan as an integral part of business continuity will increase.

Conclusion,thinking about data backup is a good first step. Business continuity is equally important to consider as it ensures your organization is able to get back up and running in a timely matter if disaster strikes.

 

Archives

The long term “cold” storage will continue to grow as more data is used and produced than ever before. The idea of ​​storing long-term archive information requires innovations from the use of cheap magnetic media to media that are less prone to losing bits over time. As semiconductor technology becomes cheaper and cheaper, it could become an alternative for long-term storage to make it more efficient.

 

Compliance & Data Governance

Vulnerabilities and regulations affecting data will continue to increase in 2019 as evolving regulatory requirements demand constant attention. Privacy concerns push organizations to implement data governance — well beyond legal demands. You need to identify sensitive data, benchmark controls, and assess risks. And move quickly to restore protection when compliance drifts.

 In addition to complying with the GDPR regulations adopted on 25 May 2018, companies must be able to prove compliance or otherwise face heavy fines. The ePrivacy Regulation will be implemented in the second half of the year. It aims to track the advances in electronic communications and related data in e-mail, news, blogs, websites and IoT devices. There will be some overlap between the ePrivacy Regulation and the GDPR, but the main difference is that the ePrivacy Regulation is only about electronic communications and the GDPR is about all kind of personal data. Data management solution providers will need to provide simple, innovative ways to help companies demonstrate and maintain these new compliance and regulatory measures.

 

Capacity optimization

Capacity management is the practice of planning, managing, and optimizing IT infrastructure resource utilization so application performance is high and infrastructure cost is low. It’s a balancing act of cost vs. performance that requires insight into the current and future usage of compute, storage, and network resources. Optimizing resources such as storage capacity is critical to cost control. The use of new applications such as analytics, machine learning and artificial intelligence is increasing. This means that the need for capacity optimization for cost control will increase, otherwise the IT budgets will get out of control for companies using this digital transformation as part of their business initiatives.

 

Visibility

Access to real-time analytics is crucial for business decision makers. Whether you’re streamlining workflow, resource forecasting or just trying to get a grip on what’s going on, you need some metrics to work with which you can trust.

Today, more than 320 million workloads are active in data centers worldwide. It is estimated that there will be over 450 million workloads worldwide by 2020, with at least half of them active in the public cloud. This increased use of the public cloud in the hybrid cloud infrastructure increases the complexity of data management. Data transparency will be the key to improving and lowering the cost of hybrid cloud environments.

Data Protection and Back-up Strategies For SME

 

 

Every small and medium-sized business needs a back-up strategy if the technology fails, is defective, or even cyber thieves makes important files disappear. A disaster recovery plan, as well as optimal, continuous and automated backup is a must for any business! Because 78% of the companies that were the victims of cyberattacks, had difficulties to restore their business data after a huge data theft. (Source: bitkom Research 2017).

 

Back-ups are no longer an option, they are mandatory! Entrepreneurs who believe that data backup is not necessary are mistaken. Hardware failures or blackmail Trojans make life difficult for small and medium businesses and cause serious business damage.

 

Although basic technical protection – such as password protection, virus scanners and firewalls – is available almost everywhere in the corporate landscape, the implementation and management of data storage is often undeveloped. Important business information, data and workflows must be protected, accessible and recoverable in all times. Because the analog and digital business processes are getting faster and faster and can bring heavy financial losses in case of disruptions caused by technical failures.

 

There are two types of entrepreneurs in the digital world: those who have already lost data and those who are about to lose it. For backing up corporate data, the 3-2-1 rule is recommended. In short, the 3-2-1 rule of backup means you must:

 

  • Have at least three independent copies of your data.
  • Store the copies on two different types of media.
  • Keep one backup copy offsite.

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Three methods of data backup:

 

 

  1. External storage drives (USB stick or hard disk)

The handling of copying data from A to B is simple, but this backup is just a snapshot and not an optimal solution. One must avoid an exclusive data backup on a medium. If one hard drive breaks down, then all the back-up data is gone. “

 

  1. Software with local back-up system

Continuous data storage automatically backs up data locally. This solution also covers multiple corporate sites and collects all the data in one system, making recovery simple and effective. However, this is also the crux – because a central storage location is usually confusing, maintenance-intensive and therefore error-prone. Software with a local back-up system is divided into:

 

  • Full backup: All data is stored together and regularly – the storage takes a long time.
  • Differential backup: Saves data that has been modified or recreated since the last full backup – saving storage time is slow.
  • Incremental backup: A reference to the changes since the last backup is made – the storage is even shorter.

 

  1. Cloud-based back-up

Central management of all data is possible with just a few clicks, eliminating the need for high maintenance on this solution. Restoring individual data across entire virtual processes to databases and servers takes just a few minutes.

 

There is constant development for back-up solutions in the market. Especially in the cloud sector, systems that take care of data traffic and encrypt transmitted data establish deduplication to reduce bandwidth usage. They also provide a local cache that provides instant access to recent backups.

 

The loss of data always doubles the economic damage, because the time any money spent in reconstructing the data cannot be invested in new projects. The right strategy saves time, optimizes the workforce and ultimately saves a lot of money.

 

It is important to know that not all back-up solutions are the same and some are definitely easier to use than others. In any case, companies should have more than one copy on a different medium than the server and never rely on just one method. IT security should be a high priority in the digital world. This includes the correct data backup. Correct data protection protects companies from data loss.

 

In any case, a consultation with our IT experts is advisable for a tailor-made back-up strategy to your own business processes.

 

 

Intelligent Leadership In 4.0 Work-Place

Intelligent Leadership In 4.0 Work-Place

Leadership must be believed and lived. If we want to shape the digital future, we also need people to realize new business models, processes and (AI) systems, who not only can live this thinking in their “minds”, but also realize it.

 

To achieve this goal, we need a new systematic education in (high) schools, families, administration and economics that empower people to move away from the current one-way street to a permanent growth thinking mindset. And for that, the radical confusions must be first understood with a leadership learning program in our heads. Lifelong learning with others, knowledge about climate change, health and simulation work with computers / machines / robots is becoming a “must”.

 

The Transformative Problem

 

Cooperative, interdisciplinary teamwork, responsible and autonomous work design are becoming increasingly important. So that the leadership needs to strengthen cooperation, identification and trust. Short innovation cycles and personalized products require tailor-made qualification measures. New forms of work such as shared / part-time leadership, virtual and networked teamwork can then be tangibly experienced.

Responsibility and control are shifted to where the work is done – even if it can be done by robots. In this way, networked communication, fluid form of project work in networks along the value chain is becoming increasingly important – both analogue and digital.

 

Managers not only have to master the tools of the “old world”, such as KPI orientation, top-down communication and control, but they must have flexible skills that enable them to lead in both organizational worlds. Self-control skills, holistic thinking and acting, self and other perception and the defence of our culture of values ​​are in the foreground.

 

Risk-seeking leaders are highly wanted

 

Most companies are run by risk avoiders rather than those ready to plunge into an uncertain digital future. We cannot deny that with investments in new (digital) business models, companies / organizations continue to struggle very hard. On the one hand, they do not want to attack their existing business model themselves, but on the other hand, they also have problems identifying new, high-yield models. Often, the assistance of upper management is lacking, not only to force the necessary cultural change but also to be able to try out potentially risky models. Established companies at this point have a disadvantage compared to digital innovators who neither have to change a traditional leadership culture nor defend an established business model.

Many companies are finding that there is a lack of appropriate leaders who have the transformational leadership key skills for the future. They need leaders who no longer think and act one-dimensionally, but multi-dimensionally. Hierarchies then become much flatter, the processes and services faster and more meaningful.

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Leadership in the 4th Industrial Revolution is defined by the ability to rapidly align & engage empowered, networked teams with clarity of purpose and fierce resolve to win.

 

Digital transformation is not without inspiration

 

According to a study by the World Economic Forum Davos, “Digital Transformation Initiative” companies are the most successful with the business model of the “Digital Platform”. But how is that supposed to work? How do you come to a “new” thinking and acting? In “ancient Rome,”, they all ended up sitting in their mansions on their infinite wealth – but in their heads they were poor. This is how the kingdom went down.

So, it is only with an interdisciplinary cooperation and with a cross-industry cooperation that you can go further. Working together with intelligent information and innovation platforms, high standards and clear rules (Code of Conduct) is essential to enable the interaction of users and suppliers (best practices) of machinery and automation components, suppliers and competitors.

 

Employee and customer cantering at eye level are the magic word. Customers or partners have to be involved early on in the development of a new product or a new service and network with it. Many companies are missing strategic opportunities here.

Thus, it is necessary not only to improve the employees’ professional competences, but above all their social / emotional competencies, so that they can understand the different views and ideas of the stakeholders, such as: Operators, manufacturers, suppliers, IT / cyber specialists and can handle the cross-functional interaction compliant.

 

Conclusion

 

One thing is for sure: If we want to shape our future successfully, then change must not only bring about the fastest possible (digital) technological solutions for customers and the environment, but also the radical change in the mindset of the management team and skilled workers. This requires “inspirational” leaders in the workforce who intelligently network, support and develop the right creative minds across all departmental, hierarchical and national boundaries. The future viability of an economy and society is therefore determined by whether the companies and public administrations want to master this so-called value-based double digital transformation.

 

Source: Oxford Leadership Research – Leadership 4.0 : A review of the thinking

 

Ready, Set, Create: A Guide To Finding The Digital Balance Of Company 2019

Digital Transformation Trends For 2019

The turn of the year invites us to reconsider old structures and processes – and that also applies to the IT departments. Almost three-quarters of executives believe they are outperforming competitors in innovation, according to a new study by consulting firm PwC.

 

There will be a number of innovation hurdles to overcome in 2019. Many companies continue to worry about data security, data protection and compliance, as they lack a holistic solution. Elsewhere, proprietary legacy systems and processes prevent data from being used profitably. How exactly and where the journey goes is difficult to predict. In principle, however, here below major core areas are already emerging, which will be the priority for companies also in 2019:

 

  1. Data security and availability:

As early as 2018, British Airways, Cathay Pacific and Ticketmaster had to conclude that insufficient data security has serious consequences. That will not change in 2019 either. Ever more complex IT environments and applications are becoming more and more under pressure from day to day: patches, enhancements and cloud migrations are a constant burden on IT teams and resources. Even hackers know that disrupting a business can be just as profitable as a data theft. Ransomware and malware have already demonstrated how they can paralyze businesses and entire communities.

Plus, underGDPR regulations, customers will start catching on to which companies actually care about protecting their data. So, companies will start recognizing how important it is for the customer’s experience and audience that they protect their customers, or at least show that they want to. Misuse of personal data will impact brand identity, marketing and selling – all business-critical initiatives to keep the customer happy and coming back.

 

  1. Speed:

In 2019, financial services providers and the banking sector will make important progress on their path to digital transformation. With fully digital, pure mobile banks such as N26, which are becoming increasingly popular, we are already experiencing enormous changes in the industry today. Being flexible, 24×7, and mobile in the first place, while complying with regulations and data protection laws, can be a daunting task. But this is precisely where the expectations of the new generation of customers in financial services lie.

 

  1. Compliance:

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The scale of new data security regulations is not fully predictable for businesses. Since data is constantly exchanged between all business units and with external service providers, a simple external hedge is not enough. The internal data streams must also be protected with the right technology. These technologies are the key to holistic risk management across the data supply chain, so that even in the AI-based and near-real-time future-oriented applications, developers and data scientists can be confident that their processes will protect their privacy and compliance directives do not affect regulations.

 

  1. People and technology:

Humans are interacting more and more directly and personally with their own technology, resulting in completely new datasets and application fields, e.g. the diagnosis of neurological diseases using speech patterns. Businesses need to access this data to improve their digital services and customer care. We’re counting on technology to take personalization and automation to a whole new level.

 

  1. Data scientists on the rise:

In terms of agility, startups are already performing better than legacy applications. The introduction of data technologies and analytics in developing and emerging economies will create even more opportunities and further enhance competitive conditions for data-driven companies. That’s why a data science team should be high on the business wish list, as well as the right data management and virtualization tools. Because the analysis of each is only as good as the data that is analysed.

 

  1. CEOs – More Than Just a Face of the Company:

2019 will see the rise of the CEO who will take the reins of digital transformation at businesses worldwide. Digital transformation is no longer looked at as just a fad, but rather a means of staying relevant in today’s business-world. Hiring those in digital transformative efforts will become a top priority as each CEO recognises the critical need for building cultures that can evolve, as well as the value of reskilling employees and hiring for an agile workplace. For CEOs leading a transformation, no single model guarantees success. But they can improve the odds by targeting leadership functions: making the transformation meaningful, modeling the desired mind-sets and behavior, building a strong and committed team, and relentlessly pursuing impact. Together, these can powerfully generate the energy needed to achieve a successful performance transformation.

 

The goal for 2019 is clear: digital balance. Businesses need to be sure that their data is securely stored, and their processes are automated around the clock. The way to achieve this goal is often bumpy and difficult by nature. It will cost companies time and perseverance to reach the digital balance, but the inner peace and inherent benefits of a sophisticated data strategy are definitely worth it.

AI IN CUSTOMER COMMUNICATION – 5 PRELIMINARY QUESTIONS

 

AI is set to be a game-changer for businesses across every industry. Artificial intelligence is undoubtedly changing the way companies address and interact with their customers.  Pluq, the increasing adoption of digital language assistants such as Alexa and Co., Siri and Amazon Echo, in private households is leading-edge.

 

A new study by Bitkom and Deloitte on the future of consumer technology showed that, in addition to 13%, who already had an intelligent virtual assistantin 2018, 4% of those surveyed are planning a purchase a voice assistant in 2019 and 27% can imagine controlling devices by voice in the future. The fact that, according to Gartner, 30% of companies will use AI for at least one key sales process in 2020, which encourages AI adaptation. Companies are faced with the huge task of adapting to the increasingly complex communication needs of their customers. Therefore, language assistants are being integrated into more and more devices.

 

Study highlighted the rapid rise of intelligent language assistants in 2018 and in the coming years we will control more and more devices with our voice. Which opens gates to a new billion-dollar market.

 

Despite all the forward-looking tips and statistics, many companies are still wondering how they can ideally use AI for themselves. Also, the costs that result, the impact on employees and customer satisfaction is not really measurable for many.

To get an overview here you should ask the following basic questions:

 

  1. What do customers really want?

Often, when answering this question, it helps to have a closer look at the customer database. Age structure, nature and complexity of incoming requests provide a clear direction. For example, an airline can quickly and efficiently handle the query of travel times with the help of artificial intelligence. But customers still preferer a human contact when questions about insurance details or specific health problems rise.

 

  1. How is automation currently being used?

Automation is not just a topic for companies since the introduction of artificial intelligence. Many have already integrated automatic systems such as IVR (Interactive Voice Response) for telephone inquiries and automated e-mails or SMS into customer communication – systems that have proven themselves so far. Implementing artificial intelligence here is not necessarily the way to go. Rather, one should analyze how existing systems can be improved to meet evolving customer needs. For example, an automated language solution with machine learning in the background could complement an existing solution and offer the customer an improved contact experience.

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  1. How will the employees react?

The biggest fear among employees is that artificial intelligence makes them redundant in the foreseeable future, for example through chatbots, and as a result they lose their jobs. The fear since the beginning of the industrial age, that machines will take over humans and jobs, is the biggest communications challenge. This is further aggravated by; a lack of understanding of AI compounded by confusing communication by various players during the current hype cycle. There is a need for constant communication and increasing awareness to improve the understanding and applications of AI. One just needs to look at history to conclude that every technological change created an explosion of new jobs and services and, overall, generated more wealth for all.

 

  1. How to find the right AI solution and how should an implementation work?

There are already a variety of AI solutions for various functions, including, for example, Natural Language Processing (NPL). You should basically get an overview of the solution providers – especially those who have a platform with interfaces to different AI solutions in their portfolio. It is essential, however, that there is a precise idea of ​​the existing communication infrastructure and the improvements to be achieved in customer communication. For example, cloud-enabled contact center vendors and specialized integration offerings with an end-to-end AI package can bridge the gap between existing functionality and the AI ​​skills needed to meet existing needs.

 

  1. How is one prepared for the future?

AI will inevitably play a major role in the future of customer contact. But there are many details to consider when planning implementation – even though the customer base is not yet fully receptive to this technology, the rapid development of AI and the ability to address more complex issues can lead to that acceptance which will increase significantly in just a few years. Also, the increasing adaptation of consumers to these types of interfaces will increase their acceptance to, and expectation of, this technology. Long-term planning should therefore always leave room to introduce new innovations as soon as they can offer defined added value.

 

This is precisely why Cloud-based contact center and integration technologies are available that are inherently capable of adapting flexibly to new developments and introducing new third-party connectors. This open technology has the advantage of reducing the risks for future AI and contact center planning and provides the ability to introduce functionality as needed. This avoids being late for a new innovation and losing valuable competitive advantages.

 

The Advances of IT Sector in 2018

 

2018 came with a lot of challenges in IT sector. Three topics kept IT departments on their toes: the GDPR with all its legal refinements; the race of IT security with cyber-attacks and data thefts and the search for the best strategy for the digital transformation.

 

Again, and again it concerns the data protection basic regulation (GDPR)

 

Since May 25, 2018, the EU General Data Protection Regulation (GDPR) is required – but many companies are still struggling with the implementation of the new regulations. In particular, data protection in the cloud requires special measures. Here are five tips on how a Cloud Access Security Broker (CASB) can help.

 

Nobody can pass cloud computing. Especially the combination of different models and providers, keyword Multi-Cloud, offers a highly flexible infrastructure to access the resources and advantages of different cloud models. However, in vision of the Data Protection Regulation (GDPR), new security and compliance requirements apply to companies. How can the complexity of a multi-cloud environment also be managed with security in terms of data protection and what should companies pay attention to when choosing their cloud provider? Here below are some recommendations on how companies can use the added value of the multi-cloud and at the same time ensure their compliance with GDPR.

 

  • Having a short guideline of the minimum requirements for companies to comply with the GDPR
  • Structure data management – personal data must be quickly locatable
  • Comply with the documentation and keep directories
  • Respect a short deadline for reporting violations of data protection – it threatens sensitive fines
  • Implement compliance management system for privacy
  • Raise awareness of data privacy and GDPR in your own company – train employees and establish new processes
  • Include external / internal employees and service providers in compliance strategies
  • Take privacy requirements already in software development and product design into account
  • Anonymise or pseudonymise data for testing and development purposes – or obtain explicit consent of the customer for the use of their real data
  • When migrating data to cloud, avoid vendor lock-in and clarify procedures for eventual return transfer
  • When using multi-cloud environments, choose a service provider that provides all components and their control completely GDPR-compliant from a single source

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In search of the magic formula for the digital transformation

 

The focus of the digitized company is the ability to integrate with customers and partners in an Internet-based manner, as simply and as quickly as possible, so that they can achieve high levels of automation on demand, which are used to quickly place products on the market.

 

The integration of appropriate processes in the company, on the one hand, creates advantages through automation. On the other hand, integration with partners, customers and other stakeholders means that company can market their products better and faster. Being a digitized company goes far beyond the simple use of software. Just because a company uses CRM software is far from digital. It is more about the complete integration of the customer and his needs into the internal company processes.

 

Every business has to find its right level of digitization. There will not be a universal recipe

for that. However, there are many criteria that influence. The key to digitization ultimately lies in understanding customer needs and the ability to integrate at all levels – from a purely technological to a sociological level of integration. Who can and who controls this, will be successful in the end.

 

Race of IT security with cyber attacks

 

Cyber risk is becoming increasingly international. Cyber losses are now being reported in almost every country of the industrialized world. Criminal attacks hit industrial companies particularly hard: Through sabotage, data theft or espionage, the average cost of a malware attack on a company is $2.4 million in the past two years. Above all, insecure IoT devices invite hackers to DDoS attacks. These “smart” devices are then very well suited to become part of a huge botnet. Thus, DDoS attacks have nearly doubled in the last six months.

 

But numerous other types of attacks also caused damage. Such as, file-less threats with “CactusTorch” use trusted Windows executables to penetrate systems and break through corporate networks. Cryptojacking has become a massive threat, with deep-fake attacks unlikely to be well-developed, and financial breach an increase in cyberattacks by hidden tunnels.

 

Although the cyber threat has increased in past few years, efforts to combat attacks and improve security are also escalating. Security spend is reaching unprecedented levels, international cooperation among cyber protection organizations is improving, and there are initiatives to catch and deter cyber criminals.

 

Minimize business-critical downtime

 

To quickly get back to business after a ransomware attack and to minimize mission-critical downtime, a multi-layered data management strategy with easy automation and fast recovery is essential. When a system is validated and can be restored quickly and easily, companies benefit in two ways. Not only can they avoid paying the ransom, they can also resume regular daily business in no time.

 

Endpoint Detection and Response (EDR) can also be a powerful tool against sophisticated enterprise IT attacks that help prevent threats that security solutions can not block in advance.

 

Companies only successfully digitize themselves when information and data can be securely and reliably exchanged. On one hand, this requires secure identities. On the other hand, data and documents must remain confidential and protected against manipulation. So you can protect yourself with a technology concept from cyberattacks.

Why Financial Institutions Can Not Allow Data Breaches

Why Financial Institutions Can Not Allow Data Breaches

The global banking sector is considerably healthier now than it was 10 years ago, at the start of the global financial crisis. The largest banks in the world have significantly improved their capital position in the years since the crisis. Furthermore, competition in the banking sector has become tough. While FinTech are primarily conquering the young target group with innovative business models, established banks must make an effort to maintain their market position. However, they also have a great advantage over the newcomers: the trust that has grown over many years of their customers.

 

Consumers feel safe at recognized banks. This is shown by the banking customers experience report. As a result, banks and savings banks occupy the top spot when it comes to customer confidence in data protection. Three quarters of respondents (72 percent) believe that their data is safe with their bank. In second place are health insurance companies with only 40 percent.

 

In contrast, however, there are other numbers. According to the Ponemon Institute’s study, sponsored by IBM “Cost of Data breach 2018” the financial industry is most often affected by data breaches or data theft. Given the nature of data held by financial institutions, including banks, credit unions, credit card companies and brokerage firms, it’s no surprise they are the most at risk of cyberattacks. The cost per lost dataset is $ 206, the second-highest in the industry, fallowing by the healthcare sector. Overall, the cost of a data breach increased from $ 3.62 million in the previous year to $ 3.86 million. In such data breach, the most importance is the loss of reputation caused by such an incident.

 

The biggest risk is data beyond the productive environment

Banks cannot afford to lose the trust of their customers. Because this is precisely their competitive advantage over the FinTech. The term “FinTech,” which is the short form of the phrase financial technology, represents companies that combine financial services with modern, innovative technologies. FinTechs generally aim to attract customers with products and services that are more user-friendly, efficient, transparent, and automated than those currently available in traditional banks.

 

Therefore, traditional banks should do everything possible to reduce the risk of data breaches and to close any weak points. Looking at past data protection incidents in the financial sector it seems that most of the time the productive data was not affected. Productive systems are usually well protected against hacker attacks with the latest technology. What is at risk is data that is copied from the production environment and circulates around the house – for example, for development or data analytics. These account for about 80% of the data in the company. In large companies, thousands of employees access the data. In this environment, data protection officer must ensure that sensitive information does not fall into the wrong hands.

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This is how DataOps provides more security

DataOps (data operations) is a new approach to data management which brings together data workers, the individuals who collect, clean and prepare data, with data analysts to help enterprises make data-driven decisions at the moment of opportunity.

A DataOps platform can be helpful in increasing the security of data inside the organization. It enables central data management and creates virtual copies of the productive data so that they can be distributed quickly and above all safely in the company. For example, central policies can be used to specify how the data should be protected. With role-based access rights, administrators control who can use which data and how.

 

An important method to protect sensitive data is also by masking it. This information is anonymized, so that no conclusions on the respective persons are possible. For developers and data scientists, the data is still meaningful enough. The General Data Protection Regulation also expressly mentions anonymization as a suitable means of data protection. With a DataOps platform, masking can be automated before the data is copied and redistributed from the production environment.

 

Conclusion

Data breaches can have lasting harmful effects for any business, regardless of its industry. The financial impact of a loss of brand reputation and trust after a cybersecurity incident can be significant across all industries. And when it comes to the cybersecurity threats financial institutions face every day, there is only one guarantee: hackers will continue to find new ways to infiltrate your organization’s network.

 

Data protection and data security are playing an important role. Still, established banks and savings banks enjoy great trust from their customers. But this advantage over Fintechs can quickly disappear due to data breakdowns and the associated loss of reputation. Particularly vulnerable are data beyond the productive environment. With masking, centralized policies and access rights management, a DataOps platform can help to better secure them.

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