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Changes in technology are happening faster and faster. According to the CIO Dynatrace 2022 report, 77% of organizations say their IT environment changes every minute or less.

The year has already started with news and trends that are here to stay, such as the popularization of Artificial Intelligence through tools such as ChatGPT. In the job market, teams come to depend on a wide variety of solutions to ensure efficiency and security in the technology area, increasingly distributed across segments.

While new technologies bring agility and innovation to IT teams, they also bring challenges in terms of complexity and risk. As a result, teams may find it difficult to drive Digital Transformation at the required scale and speed required to meet customer expectations.

See below what will be the 5 main challenges for the technology area in the second half:

1. Cybersecurity

Cybersecurity is an extremely relevant subject these days, as technology is increasingly present in our lives. Increasing digitization increases the risk of cyberattacks – which have become increasingly sophisticated and pervasive as cybercriminals develop more advanced techniques to exploit vulnerabilities in systems, networks, and applications. Some of the most common attacks include:

Ransomware: A type of malware that encrypts user files and demands a ransom to restore access to data. Ransomware attacks are increasingly targeting businesses and government agencies.

Phishing attacks: Phishing attacks involve using spoofed emails or fraudulent websites to trick users into obtaining sensitive information such as passwords and banking details.

Social engineering attacks: In this case, criminals manipulate people to obtain sensitive information or access to systems.

Distributed Denial-of-Service (DDoS): In these attacks, criminals overload a server or network with excessive traffic, making it inaccessible to legitimate users.

Cybersecurity governance is essential to ensure organizations are prepared to protect their data, systems, and infrastructure from cybercrime. This involves implementing policies, procedures, controls, and guidelines to mitigate risk and effectively respond to security incidents.

Furthermore, it is crucial for companies and organizations to comply with the General Data Protection Act. The LGPD is legislation that seeks to guarantee the privacy and security of citizens’ personal data and establishes rules on the collection, storage, processing, and sharing of information.

To meet LGPD requirements, organizations need to adopt appropriate cybersecurity practices, such as encryption, access control, security audits, and employee awareness training.

Faced with increasingly sophisticated cyber attacks, it is essential for companies to be prepared to face these challenges and ensure the privacy and security of customer and user data.

2. Digital Transformation as a continuous process  

Digital Transformation is the process of incorporating digital technologies into all areas of an organization to drive significant changes in its processes, culture, products, and services. Although Digital Transformation can bring countless advantages and opportunities for companies, it also brings significant challenges, such as the difficulty of adapting to the evolution of technology and the presence of legacy systems.

New digital solutions, trends, and tools are constantly emerging, making it challenging for companies to effectively apply these innovations to their operations and business strategies. Resistance to change and lack of adequate technical knowledge are some of the factors that make adaptation difficult. In addition, investing in new technologies often requires significant financial resources, which can be a barrier for some companies, especially smaller ones.

For example, legacy systems were developed with older technologies and are often not easily upgradeable or integrated with new tools. They are kept in use because they still perform essential functions, but they can pose a drag during Digital Transformation.

This is because the integration of legacy systems with new platforms and solutions can be complex and demand additional effort. Moreover, these systems often exhibit security issues, scalability limitations, and lack of support, rendering them less efficient and prone to failures. Overcoming challenges in Digital Transformation necessitates careful planning and an approach that encompasses strategies such as:

Assessment and Planning: Conduct a comprehensive assessment of the organization’s needs and goals, identifying areas that require technological updates and defining a Digital Transformation strategy aligned with business objectives.

Empowerment and Training: Invest in employee empowerment and training to ensure their readiness to adopt new technologies.

Modernization of Legacy Systems: Aim for the modernization of legacy systems, making them more flexible, secure, and compatible with new digital solutions.

Partnerships and Collaborations: Seek partnerships with technology-specialized companies, startups, or digital solutions providers.

Organizational Culture: Foster an organizational culture that is open to innovation and experimentation, encouraging the adoption of new technologies and the pursuit of improvements.

In summary, Digital Transformation is a complex challenge that demands a strategic and open approach to adopting new technologies. Overcoming the difficulties of adapting to technological evolution and dealing with legacy systems is essential for companies to harness the benefits and opportunities offered by the digital era.

3. Dealing with increasingly complex clouds

The complexity of clouds, especially in a scenario of multiple services and multi-cloud environments, is a growing concern for many organizations. The migration of applications and services brings numerous advantages in terms of scalability, flexibility, and cost reduction, but it also presents significant challenges.

As companies expand their operations into the cloud, it’s common for them to utilize a combination of different cloud service providers such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and other regional or specialized providers. Additionally, applications and services might be deployed in hybrid environments, involving both public and private clouds.

Dealing with this multi-cloud complexity can be a challenge, as each service provider has its own management interfaces, APIs, and performance metrics, making uniform management difficult. Each environment may require different tools and approaches, adding to the complexity.

The lack of standardization in metrics and logs, as well as the difficulty of correlating data from different services and providers, make observability more complex. This can result in slower response times to resolve issues and difficulties in detection and possible failures.

Cost management is also a concern in cloud environments, especially when dealing with multiple services and providers. Each provider has its own structure and organizations need to understand how resources are being used, as lack of control can lead to overspending and waste, resulting in blown budgets. To face these challenges, it is important to adopt practices and tools that can facilitate management in complex cloud environments:

Automation: Utilizing automation to deploy and manage cloud resources can enhance operational efficiency and reduce human errors.

Observability Tools: Investing in monitoring tools that provide a holistic and unified view of the multi-cloud environment, facilitating issue detection and performance analysis.

Cost Analysis: Implementing cost analysis solutions that allow tracking cloud resource consumption and identifying areas for optimization and cost reduction.

Policies and Governance: Establishing clear policies for cloud resource usage and ensuring proper governance to prevent unnecessary expenses.

Strategic Partnerships: Considering the possibility of forming partnerships with managed service providers or cloud-specialized consulting firms to assist in the implementation and management of complex multi-cloud environments.

In summary, the complexity of clouds in environments with multiple services and multi-cloud setups poses a challenge for many organizations. However, with a strategic approach, adoption of appropriate technologies, and efficient management practices, it’s possible to overcome these obstacles and reap the benefits of the cloud more effectively.

4. Efficient data management

Efficient data management is crucial in a complex application environment. As organizations embrace the cloud and deploy distributed solutions, the volume of data generated, stored, and processed increases significantly. Connecting and aggregating this data cohesively is essential for gaining valuable insights and making well-informed decisions. Some strategies to achieve more efficient management include:

Data standardization: Define standards for the structure and formatting of data, regardless of the storage source. Standardization facilitates integration and further analysis.

Data Integration: Using data integration tools that can connect and combine information, whether stored in public, private, or on-premises clouds.

Unified Data Platform: Invest in a unified data platform that can centralize data management from multiple sources and provide a comprehensive view of the data environment.

Data Lakes and Data Warehouses: Implement data Lakes or Data Warehouses to store and process large volumes of data in a structured way, allowing advanced analysis and insight extraction.

Business Intelligence (BI) tools: use BI tools to visualize and analyze data in a more accessible and intuitive way, facilitating the extraction of insights and decision-making.

Data Streaming: Implement real-time data streaming solutions to gain instant and continuous insights into critical events.

Security and Compliance: Ensure that data management is carried out with a focus on security and compliance with data protection regulations.

Machine Learning and Predictive Analytics: Utilize Machine Learning and predictive analytics techniques to identify patterns and trends in data, generating valuable insights for decision-making.

Automation and Orchestration: Implement automation and orchestration to simplify data management tasks and reduce manual intervention.

Monitoring and Metrics: Deploy monitoring systems to track data performance and usage, ensuring the environment remains optimized and operates efficiently.

As we can see, efficient data management in complex and distributed environments is essential to make the most of the data generated by applications and gain insights. By connecting data from multiple sources with modern technologies and an integrated approach, organizations can overcome challenges and turn data into a competitive advantage.

5. Operationalize Artificial Intelligence

Artificial Intelligence (AI) has garnered significant attention in recent years due to its potential to transform various industries and enhance efficiency across various aspects. However, bringing this technology into the realm of business presents several challenges that demand careful and strategic approaches:

Technological Complexity: Implementing AI solutions can be complex and requires specialized knowledge. The lack of skills and expertise within teams can hinder the effective adoption of this technology.

Quality Data: AI relies on large volumes of high-quality data to learn and provide accurate insights. As addressed in the previous topic, collecting, processing, and preparing data can be challenging, especially when data is scattered across different systems.

Integration with Existing Systems: Many companies already have legacy systems and established infrastructures. Integrating AI solutions into these systems can be both a technical and organizational challenge.

Costs and Initial Investments: Implementing AI projects may require significant investments in hardware, software, and specialized human resources.

Acceptance and Cultural Change: Adopting AI can involve changes in organizational culture and how tasks are performed. Convincing stakeholders of the importance and benefits of the technology is not always easy.
Ethics and Responsibility: The use of AI raises ethical and responsibility concerns regarding data treatment, automated decision-making, and user privacy.

To overcome these challenges and make AI a reality within organizations, it’s essential to plan and define a strategy aligned with business objectives, identifying the expected impact. It’s worthwhile to consider partnerships with AI experts to assist in implementation and provide additional technical expertise, as well as investing in employee training. Prioritizing the quality, relevance, and reliability of data is also essential.

While implementing AI in businesses may pose challenges, overcoming these obstacles provides a competitive advantage, enhancing operational efficiency and decision-making. With the right approach, artificial intelligence can become a thriving and transformative reality for companies.
The year 2023 has been filled with challenges, but also opportunities. To achieve your goals and attain remarkable results, BRQ is your ideal partner. Learn more about how we accelerate businesses with intelligence by clicking here.