Navigating the Data Seas: 15 Trends Shaping Business Strategies

Arvind Mehrotra
7 min readMay 10, 2024

Data has become the cornerstone of modern business strategies. The evolution of data platforms shapes how organisations collect, process, and leverage data to drive innovation and gain competitive advantages.

However, defensive and protective actions have been on the increase, impacting the decline in data exploitation due to the following factors and measures:

  • Legislation and Regulations: Stricter data protection laws and regulations have been enacted globally. These legal frameworks penalise organisations that fail to safeguard data adequately. Compliance with these regulations has forced companies to take data security seriously.
  • Technological Advancements: Advances in cybersecurity technologies, such as intrusion detection systems, firewalls, and behavioural analytics, have made it more challenging for attackers to exploit data.
  • Improved Security Measures: Organisations have become more proactive in implementing robust security measures to protect their data. These measures include encryption, access controls, and regular security audits. As a result, it has become harder for threat actors to exploit data.

However, common gaps exist because organisations often need more resources for insider threat programs, leading to gaps in monitoring and response. Due to competitive and margin pressure, employees wearing multiple hats may inadvertently create conflicts. Finally, the increase in remote and distributed work is making a gap in enabling support for remote workers who resort to self-help or third-party help, leading to exploitation.

  • Insider Threat Mitigation: Both individuals and organisations are now more aware of the risks associated with data breaches. The need for tailored procedures and working with generic security procedures may not effectively address insider threats. Customised approaches are essential. Finally, inadequate supervision of employees can allow insider threats to go undetected.
  • Social Engineering Awareness: Educating employees about social engineering tactics (such as phishing) has minimised successful attacks. People are more cautious when receiving unsolicited emails or messages, reducing the chances of data compromise. However, not all training programs have been effective, leading to a gap in the desired impact. Integrating resistance against persuasion (based on social psychology) must be addressed. We can see an increase in this trend of employees under pressure for performance and thus seeking any help or support. The lack of digital literacy in aged individuals is also causing increased data exploitation.

Remember that while data exploitation is declining, it’s essential to remain vigilant and implement best practices to protect sensitive information. Let’s look ahead; several trends are poised to redefine the landscape of data platforms, empowering businesses to unlock new opportunities and address emerging challenges.

Here are my top most influential data trends that will define enterprise operations for the rest of this decade:

1. The normalisation of AI-driven automation

In the coming years, data platforms will increasingly harness the power of artificial intelligence (AI) to automate routine tasks and streamline processes. From data ingestion to analysis and insights generation, AI-driven automation will enhance efficiency, reduce errors, and accelerate decision-making across various business functions.

2. Edge computing integration becoming commonplace

The proliferation of the Internet of Things (IoT) devices is generating the rise of real-time analytics, which demands data platforms to integrate seamlessly with edge computing infrastructure. By processing data closer to its source, organisations can minimise latency, improve scalability, and extract valuable insights in near real-time, enhancing operational agility and responsiveness.

3. The widespread use of blockchain for data security and trust

Blockchain technology will enhance trust and transparency within data platforms in an age of heightened data privacy and security concerns. By leveraging blockchain for immutable data records and secure transactions, businesses can fortify their data ecosystems against cyber threats and regulatory compliance risks, fostering greater stakeholder trust.

4. Hybrid and multi-cloud deployments are the default

The future of data platforms lies in hybrid and multi-cloud deployments, allowing organisations to leverage the strengths of different cloud providers while mitigating vendor lock-in risks. By adopting a flexible and scalable infrastructure, businesses can optimise cost efficiency, improve resilience, and seamlessly orchestrate data workflows across diverse cloud environments.

5. Emergence of data democratisation initiatives

Empowering users with self-service analytics capabilities will be a key focus area for data platforms in the years ahead. By democratising access to data and analytics tools, organisations can foster a culture of data-driven decision-making, empower employees at all levels, and drive innovation across the enterprise.

6. A stronger focus on real-time data processing

The ability to process and analyse data in real-time will be instrumental in unlocking actionable insights and capitalising on fleeting opportunities. Data platforms that prioritise real-time data processing capabilities will enable organisations to gain a competitive edge by responding swiftly to market dynamics, customer preferences, and emerging trends.

7. Growing attention towards privacy-preserving technologies

With regulatory frameworks such as GDPR and CCPA imposing stringent data privacy and protection requirements, data platforms will increasingly integrate privacy-preserving technologies. Techniques such as differential privacy, homomorphic encryption, and federated learning will enable organisations to anonymise sensitive data, safeguard individual privacy rights, and comply with evolving data regulations.

8. New possibilities in augmented analytics

The convergence of analytics and artificial intelligence will give rise to augmented analytics capabilities within data platforms. By embedding machine learning algorithms and natural language processing interfaces, augmented analytics will enable business users to quickly uncover hidden patterns, derive actionable insights, and make data-driven decisions.

9. Adopting containerisation and microservices architecture for data platform agility

Containerisation and microservices architecture will emerge as foundational elements of modern data platforms, offering scalability, agility, and portability across heterogeneous environments. By containerising data workloads and decoupling services, organisations can accelerate deployment cycles, optimise resource utilisation, and facilitate seamless integration with DevOps practices.

10. Ethical and responsible data usage driving enterprise programs

As AI technologies become increasingly pervasive, ensuring ethical AI and responsible data usage will be paramount for organisations across industries. Data platforms that embed principles of fairness, transparency, and accountability into their algorithms and workflows will earn the trust of customers, partners, and regulatory bodies, fostering sustainable growth and societal impact.

11. A shift to DataOps for agile data management

Adopting DataOps practices will redefine how organisations manage and deliver data pipelines and analytics workflows. By embracing principles of collaboration, automation, and continuous integration/continuous deployment (CI/CD), DataOps enables cross-functional teams to iterate rapidly, improve data quality, and accelerate time-to-insights, driving innovation and agility at scale.

12. Exploring new data monetisation strategies

In an era where data is the new currency, organisations will increasingly explore data monetisation strategies to unlock new revenue streams and business models. Whether through data-sharing partnerships, insights-as-a-service offerings, or monetising proprietary datasets, businesses can capitalise on the intrinsic value of data assets, driving growth and competitiveness in the digital economy.

In Summary

As we journey towards 2030, the evolving landscape of data platforms presents boundless opportunities for organisations to innovate, differentiate, and thrive in an increasingly data-driven world. Here are a few ways you can start preparing today:

● Evaluate your organisation’s readiness to embrace AI-driven automation across data workflows and processes

● Assess the feasibility of integrating edge computing infrastructure into your data platform architecture to enable real-time analytics and decision-making.

● Establish governance frameworks and protocols for responsible data usage and ethical AI practices within your organisation.

● Explore opportunities for data monetisation and partnerships to unlock the untapped value of your data assets.

● Invest in upskilling your workforce and cultivating a data-centric culture to drive adoption and proficiency in data analytics and decision-making.

By embracing these trends and charting a strategic roadmap for your data initiatives, you can harness the transformative power of data to shape the future of industries, economies, and societies. To discuss data platforms in detail, email me at Arvind@am-pmassociates.com.

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Arvind Mehrotra

Board Advisor, Strategy, Culture Alignment and Technology Advisor