Artificial intelligence, machine learning, business intelligence and cybersecurity – these technologies will significantly affect the world of IT and engineering in 2020. Based on many years of experience in the IT and industrial engineering services market and a great passion for technology, the Sii Poland experts have identified four main technological trends that will dominate in the coming months.
The technological revolution is changing our world faster than ever before. Investing in the solutions using Artificial Intelligence (AI) or Business Intelligence (BI) class systems provides enterprises with completely new opportunities for business development. So what will 2020 be in the area of modern IT solutions and broadly understood technologies for engineering? We asked this question to the Sii Poland experts who selected four leading trends.
The AI revolution is gaining momentum
Although artificial intelligence is not a new idea, it has only recently started to be used on a large scale in all sectors of the economy, starting from business through transport ending up with tourism, being one of the main factors of so-called digital revolution. The common point of each of the AI-based solutions is intelligent automation of operations and increase in productivity. It is estimated that the areas that will achieve the highest increase in gross value added, thanks to the use of this technology, are communication, finance, production (among others due to the development of Internet of Things).
– Based on our experience and market forecasts, we can say with confidence that it is worth investing in AI projects. Sii Poland is currently implementing a number of projects for clients from sectors such as banking and finance, telecommunications and healthcare – says Krzysztof Krężel, Chief Operating Officer at Sii Poland. – Our teams create solutions that enable building effective marketing campaigns or preparing a product offer exactly tailored to the group of recipients, which allows you to achieve a return on marketing investment of up to 90% – he adds.
Machine Learning supports decision-making processes
Nowadays, running a company means continuous decision making, which in a rapidly changing business environment, is a very difficult and complex process. The use of machine learning models, in many companies, optimizes the process of solving business problems, significantly reducing the time needed to make decisions, as well as increasing their accuracy.
Automation is one of the elements of ML development. Technological giants such as Microsoft or Google are introducing solutions that enable the entire data analysis process and subsequent prediction to be carried out with virtually no programming required. It is certainly a big step towards conducting advanced analyzes by people with no experience in the field of Data Science.
MLOps (DevOps for machine learning) is an increasingly used term in the context of ML. This idea, assuming the cooperation of Data Science and IT teams, is widely used and developed on a large scale in projects related to artificial intelligence, which is also connected with the need for comprehensive management of machine learning life cycle.
– We see interest in this area among our clients, for whom we implement projects using the latest AI and ML technologies. We create innovative, secure and, above all, scalable solutions located in the Microsoft Azure cloud. We are currently working on topics such as fraud risk assessment and the use of ML models in the debt collection process for the banking sector, as well as predictive analysis of maintenance in the production sector – says Małgorzata Chanczak, BI Competency Center Director at Sii Poland.
An example of a solution implemented by Sii Poland is HRSiiPro – a platform created by the Business Intelligence Competency Center, enabling the creation of forecasts regarding employee rotation and the discovery of advanced correlations, allowing a better understanding of the reasons for an employee leaving the company. Although this tool is technologically very advanced, it allows for easy data analysis performed by HR department employees who have access to modern and intuitive visualizations and dashboards in the Power BI tool. This solution uses Azure Machine Learning Studio and advanced analytical models written using R and Python.
Machine learning is not limited to a cloud
Machine learning is much more than just a cloud. Another application of artificial intelligence regards the field of embedded systems. Intelligent devices that can make decisions independently play an increasingly important role in our lives, starting with autonomous cars stopping in front of a pedestrian crossing, through intelligent washing machines choosing the appropriate length of washing, and ending with refrigerators that do the shopping.
Characteristic for the embedded world are limitations regarding the size of devices, available memory resources, computing power, and often also the battery capacity. The response of such a system often has to take place within a specified time frame, which cannot be done without the right equipment. Typical machine learning solutions use the computing power of graphics cards, whereas in the embedded area dedicated hardware is required.
An interesting example of such solutions is the EVAA (Ecological Veritical Agriculture Assistant) project implemented by the Embedded Competence Center at Sii Poland. Its purpose is to teach the intelligent agent how to optimize the plant breeding process.
– The project is very demanding, because it requires the integration of various sensors and actuators, robot control, camera image processing, as well as data collection. The intelligent agent learns based on dedicated algorithms, thanks to which the plant breeding process takes place in an automated manner. In 2016, the machine taught in this way defeated the world champion in Go, and here it learns how to help solve the problem of world hunger – explains Paweł Czapiewski, Team Leader at Embedded Competency Center at Sii Poland.
Business Intelligence – a new quality of data processing
With the growing digitization, the biggest challenge for modern businesses is the proper management of data surplus. Companies that invest in the constant development of Big Data infrastructure, the use of Business Intelligence class systems and effective analytics will grow the fastest. However, companies that transform the acquired data into readable and useful business information will gain a real competitive advantage. The number of messages that modern managers have to face in 2020 will be 44 times higher than a decade ago.
The huge amount of data that the world provides can become a useful tool in everyday life. According to the Gartner Institute, in three years’ time the information collected through business analysis will transform 80% of processes and products. Proper analytics will turn them into practical instructions, allowing individual departments and decision-makers in the organization to take action on many business levels at the same time. Thus, the company’s management will have access to current analysis and the condition of the enterprise, the controlling department will have at its disposal tools that automate the preparation of detailed financial statements, while marketing will know everything about its customers and will be able to precisely plan subsequent activities, maximizing their effect.
– We have been involved in many projects in the area of Business Intelligence. One of them was the implementation for the global leader of IT solutions for pharmaceutical trials, which needed support in designing a prototype of modern approach to their flagship product: clinical data repository. The system collects a lot of important data (e.g. from conducted trials and experiments), which can further be subjected to various kinds of analyzes (mainly statistical). Our prototype not only met the client’s requirements, but will also help many pharmaceutical companies in developing more effective treatment methods – says Małgorzata Chanczak.
Cybersecurity is no longer an option but a necessity
The expenses of companies from around the world on products and services related to cybersecurity grow every year regardless of the industry. It is estimated that in 2019 they increased by almost 9%, to the value of USD 124 billion, and in 2022 they will increase up to USD 170 billion. For many large companies, a security breach is one of the basic threats to their business, as the consequences include not only financial losses. An effective attack can entail the loss of data, violation of confidential information and disruption of the entire organization’s business continuity.
Increasingly, not only giants but also smaller companies ask about cybersecurity services. Companies realize that regardless of industry and scale, they can become a target of an intentional or completely accidental cyber attack. Some of the projects implemented in this area by Sii Poland were initiated by the clients themselves and are a response to earlier security breaches. However, when it comes to data security, it is much better to counteract than deal with the effects of cyber attacks.
– Many of our clients are aware of the growing scale of the threat and adopt the right strategy. Frequently, they are thinking not about whether they will fall victim to an attack, but when this attempt occurs, how to protect against it and, above all, what to do when it turns out to be effective. Depending on the degree of organization’s maturity, we support them in all areas that make up the complete cybersecurity cycle – says Dawid Jankowski, responsible at Sii Poland for the development of the Cybersecurity Competency Center.
One of the largest projects implemented in recent years is the Security Operations Center for a large international financial company. As part of the Sii’s service, the company provides the client with support enabling quick response to a potential attack or attempt. The responsibilities of experts working on the project include monitoring network traffic and e-mail correspondence, analyzing potential security incidents and their consequences or running and analyzing malware in a separate environment.
Innovations change the job market
It is anticipated that artificial intelligence will eliminate, but also create new jobs, which will benefit mainly engineers specialized in AI – for each reduced 1000 jobs there will be 1280 new, says the Gartner Institute. According to a report by the Ministry of Digital Affairs, by 2025, 200 000 specialists in the field of AI will be needed in Poland. It is also forecast that by this time around 720 companies specializing in building AI systems will operate on the market. Therefore, the state plans large investments to support development in this area, the value of which is to amount to approx. PLN 9.5 billion.
According to Krzysztof Krężel, the demand for the specialists in the area of broadly understood Data Science will grow every year. Specialists from three groups will be needed to implement the projects: AI architects, data mining specialists and software engineers. Looking at the development of many technologies that allow us to solve problems using AI (Python, R, Azure ML, Amazon Sagemaker), the companies should strive to diversify the team so that it has the necessary competencies to deal with challenges using various tools. As far as cloud analytics development is concerned, Data Science teams will also need specialists who can use the cloud environment and the services it provides to create comprehensive AI solutions.
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