Cloud Computing: Trends for 2022 and beyond

 

Cloud Computing Trends for 2022

Although cloud computing isn’t a new concept and the benefits of the cloud are well known for a long time, cost optimization, security, data protection, and automation remain top concerns for some organizations. However, during 2020 and 2021, cloud computing exploded with the COVID-19 pandemic as more and more organizations moved most of their applications to the cloud. This decision has been motivated by the urgent need for flexibility within a very short time in order to be able to react to changed framework conditions. We will also witness the growth of rapid adoption in 2022. According to predictions from Gartner, global spending on cloud services is expected to reach over $482 billion in 2022, up from $313 billion in 2020. This shows how cloud technologies are one of the most important pillars of modern IT infrastructure today and will continue to gain importance in the future.

 

For very different reasons, companies decide to migrate their digital business processes to the cloud. According to the Flexera 2021 State of the Cloud Report, performance and scalability are among the main reasons, alongside easier data access and management and lower overall costs. Accordingly, 61% of businesses migrated their workloads to the cloud in 2020, from which 92 percent of enterprises have a multi-cloud strategy; 80 percent have a hybrid cloud strategy. But regardless of where they are at in their journey  towards the cloud, organizations should keep an eye on the following trends:

 

The public cloud is gaining in importance within hybrid scenarios

Moving to the cloud is complicated and deciding which cloud type is the right one for an organization depends on multiple factors, such as the requirements for computing, storage, and services. Each cloud model has its own advantages and disadvantages that companies have to weigh up. Hybrid cloud scenarios (i.e. an environment made up of on-premises and a cloud) have established themselves as the de-facto standard for cloud deployment – according to the Flexera study, public cloud adoption continues to accelerate as 36 percent of those surveyed already spend more than $12 million per year on public clouds and 55 percent of enterprise workloads are expected to be in a public cloud within twelve months. The reasons given for this were data protection-relevant applications and business-critical processes.

 

Real-time analytics and IoT are on the rise

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Companies make use of a number of cloud services to solve the different business requirements. Analytics and infrastructure services still comes first, followed by data for machine learning (ML) and artificial intelligence (AI). The Global Connected Device Analytics Market is estimated to be USD 14.9 Bn by the end of 2021 and is expected to reach USD 40.7 Bn by 2026, growing at a CAGR of 22.3%. This huge need for connected devices in the different industries has been motivated due to remote monitoring of employees working from home during the Covid-19 crisis. Additionally, IoT analytics is becoming a core investment strategy for various organizations to leverage analytics as a core competency to deliver better outcomes and to drive differentiation for their product and service offerings. The more intensively and consistently companies use the cloud, the more benefits they can derive from it. This trend will continue in the next year and more advanced use cases such as ML / AI analyses, IoT, but also stream processing will continue to increase.

 

Companies are increasingly lacking cloud skills

As businesses rapidly transition their processes and data over to the cloud, the demand for digital experts is increasing but the skill gap in this area can make it an unrealistic goal for some companies. There is a huge skills gap in cloud computing, both within organizations’ current workforce and in the hiring pool and the situation will worsen in the near future. Organizations are facing the issue of finding skilled IT professionals to cover core missions with critical skill sets to be able to support their business objectives. They need specialist knowledge in handling and managing huge amounts of data in the cloud, as well as building a holistic data architecture. Reports show that missing or limited cloud skills is the greatest challenge in connection with cloud migration for almost a quarter of companies (24%). As more and more organizations are pushing their digital transformation, the need for data and cloud architects or cloud DevOps engineers and cloud system administrators is increasing, but it is becoming increasingly difficult to meet them. Its foreseeable companies will concentrate even more on training their existing employees in order to acquire the required cloud skills, while at the same time relying more on user-friendly self-service solutions in the coming years.

 

As said previously, the global spending on cloud services is expected to reach over $482 billion in 2022, up from $313 billion in 2020 – the next coming years will therefore primarily be about getting the maximum benefit from cloud integration. For this purpose, companies should, on the one hand, particularly tackle the development of the required skills and, on the other hand, consider specifically which IT & business requirements they can solve with the help of the cloud. This enables them to take their cloud usage and business to the next level.

 

Sources:

Top Strategic Technology Trends for 2022: Cloud-Native Platforms

Cloud Shift Impacts All IT Markets

Flexera Releases 2021 State of the Cloud Report

The role of Data Modelling & Prediction for Business Transformation

The role of Data Modelling & Prediction for Business Transformation

IT teams in small and medium-sized companies struggle with budget constraints and a shortage of skilled workers. When the demand for IT services increases, they are heavily overloaded and look for ways to increase efficiency. Additionally, organizations are reaching a point where their data storage and computing are unable to keep up with the growth of data and technological advancements.

 

As data, a critical asset for organizations continues to rise exponentially, business executives around the world are heavily investing in IT automation. Also, the digital transformation is pushing the boundaries, enticing businesses entities to invest in technologies that can predict possible outcomes, and to gain a competitive advantage. One of the emerging and appealing technology that businesses can benefit from in many ways is Predictive analytics. By definition, predictive analytics is a mathematical principle that uses algorithms and artificial intelligence (AI) to derive probabilities from historical and current data. It is currently one of the most important big data trends. The predictive analysis leverages statistical techniques such as predictive data modeling, machine learning, and even artificial intelligence to uncover patterns in big data.  It helps organizations to make data-driven decisions and get useful, business insights that can help them increase company profit.

 

It is a process that uses data mining and probability calculations to predict results. It includes the collection, analysis, and interpretation of data from various operational sources. The method uses structured and unstructured data, for example from internal and external IT systems (big data/data mining). Predictive Analytics collects this information using text mining, among other things, and combines it with elements of simulation processes. Thanks to machine learning, the algorithms automatically draw findings from their own data processing and use this as a basis to automatically develop predictions. The aim is to predict complex economic relationships and future developments based on the analysis of the existing data in order to make better decisions and gain a competitive advantage. Each model consists of a number of predictors, which are variables that can influence future results.

 
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The underlying software has become more accessible and user-friendly over time thanks to user interfaces that are suitable for specific departments. The goal is to identify trends, announce disruptive industry changes, and enable more data-driven decision-making. Such predictions serve to optimize the use of resources, save time and reduce costs. Optimized timelines for the introduction of new products or services can also be created. The models developed in the process are intended to help achieve or support the goals set.

 

Any area in which data is being collected is suitable for predictive analysis as there are many uses for it. These include detecting data misuse, improving cybersecurity, optimizing marketing programs, and improving business processes. Predictive analysis can use adaptive algorithms to examine systems, applications, and network performance by allowing companies to take a more proactive approach to IT operations management. With this technology, IT security experts can identify potential vulnerabilities, determine the likelihood of cyber-attacks and work on improving the company’s security structure.

 

Adapting to advanced analytics will allow your organization to stay on top. Just as technology is constantly innovating, so should companies adapt. Predictive analytics focuses on improving profitability, productivity and reducing costs through process optimization.

Do you have areas of the company in which you want to improve prediction/reporting?  If you answered yes, please contact us directly, our experts will gladly support you.

2021: Ensure Your Business Growth by Becoming Data-Driven Company

ensure Your Business Growth by Becoming Data-Driven Company

 

In 2021, government agencies and businesses will need to be able to make decisions based on current/real-time data faster and more accurately than before. Because: due to COVID-19, markets, supply chains and customer behavior have changed in recent months, only data-driven businesses are able to respond quickly and effectively in a rapidly changing world. In order to transform into a data-driven business, it’s not only important to understand the importance of data quality and governance. But it’s also key to drive a data strategy that is aligned with your business strategy. By integrating analytics into business strategies, businesses can transform data into decisions that improve lives and results.

 

A study of more than 3,500 business executives and senior IT decision-makers across the UK, France, Germany, and the Netherlands found a gap between companies using data to inform decisions during the pandemic and those who are not. The YouGov survey, commissioned by Tableau, asked executives of small, medium, and large businesses about their use of data during the pandemic, lessons learned, and confidence in implementing long-term business change. For executives in data-driven companies, a majority (80%) believe they had a key advantage during the pandemic.

 

These leaders are also deeply committed to the important role data plays in the future of their business. A large majority of 76% plan to increase investments in data literacy; especially after the long bumpy ride we have all been on since the start of 2020. Additionally, 79% are confident that they will ensure business decisions are supported by data. The results show that non-data-driven companies are slower to grasp the meaning of data in these uncertain times. Only 29% see this as a key benefit and 56% say they will reduce or stop investing in data skills. Additionally, only 36% are confident that the data will support business decisions.

 

“This year has accelerated change for businesses and ushered in a fully digital world faster than anyone could ever have imagined. Data is at the heart of this digital world,” said Tony Hammond, Vice President Strategy and Growth EMEA. at Tableau. “In this age of data, our research shows that data-driven companies see clear benefits and are more confident about the future of their business. As a result, they really rely on the power of their data. Companies that haven’t woken up to it run the risk of falling behind. But businesses big and small can rest assured that it’s not too late to harness the power of data – the time is now.”

 

When asked how it helps to be data-driven during the pandemic, company leaders recognized several benefits. At the top of the list are: more effective communication with employees and customers (42%), the ability to make strategic business decisions faster (40%) and improved collaboration between teams for decision making and problem-solving (36%).

 
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“We started building data skills in our company in 2013, and due to the pandemic, we have definitely benefited from these functions,” explains Dr. Dirk Holbach, Senior Vice President and CSCO Laundry & Home Care at Henkel, one of the world’s leading consumer goods and industrial companies. “For example, within a few days, we were able to record all of our personal protective equipment controls so that each facility can see how we are equipped in this regard so that our business can continue to operate. I am confident that we will take some good lessons with us in the future, especially when it comes to working together. “

 

For all respondents, the key takeaways from the pandemic are: the need to be more agile (30%), prioritize and implement projects faster (26%), and access to more accurate, up-to-date, and cleaner data (25%). Jay Kotecha, the data scientist at full grocery brand Huel, said of his data strategy: “Our data-driven strategy helps the company respond to consumer behavior and enables us to pivot and react faster and more clearly. It’s about empowering the entire organization through data. Employees examine data from across the company and turn it into insights we can act on, whether it’s sales projections, sales effectiveness, or marketing spend. “

 

Across Europe, the results show that just over half (56%) of business leaders consider their companies to be data-driven, while one in three (38%) think they do not. These results indicate a clear way for organizations to leverage data to support business resilience and decision making during this time. German companies are taking the lead with 62% as their business is data-driven, while the UK lags behind with just 46%.

 

The promise of digital change is based on the ability to harness the power of technology to grow your business, open up new markets, and acquire new customers. It also means that you need to understand all of the data (the digital exhaust – the trail of data left behind by browsing the Internet) that new customer experiences create. A data governance strategy as well as information and data quality management as an integral component of management systems significantly supports the achievement of the organization’s goals, ensures compliance conformity, increases throughput, and supports organizations in the transformation to a data-oriented culture. Organizations thus secure their competitiveness and can expand this further through increased data intelligence.

 

Sources:

Data-driven companies are more resilient and confident.

Data-driven businesses vastly more optimistic – research

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