TDWI | Training & Research | Business Intelligence, Analytics, Big Data, Data Warehousing

How to Leverage 2023’s Top Trends: Consolidation, Automation, and AI

Today’s business leaders are on a quest to become more data-driven; taking advantage of these three trends promises to generate greater business benefits that improve processes, security measures, and the bottom line. Here are best practices to consider for each of these trends.

• By Yotam Segev
• January 16, 2024

In 2023, consolidation, automation, and artificial intelligence (AI) topped key trends across industries. Faced with ongoing pressures to do more with less, businesses are leveraging these trends to become more agile, competitive, and capable of delivering innovative solutions by taking advantage of new technology advancements to meet the demands of an ever-changing market landscape. Today’s business leaders are on a quest to become more data-driven, and together, these three trends promise to generate greater business benefits that improve processes, security measures, and the bottom line.

For Further Reading: The Age of Enlightenment in Cybersecurity The Future of Data Science Lies in Automation Application and Data Observability Explained

Trend #1: Tool and technology consolidation unleashes innovative tech investments

Teams are being asked to do more with the same or fewer dollars or resources than they were allocated last year. This leaves business leaders struggling to balance staffing and skills shortages and the proliferation of data and usage across the enterprise with the need to maintain data security and privacy -- all while evaluating the state of the art in new technology. Leaders must prioritize platforms and consolidate technologies to fund new investments that power the next generation of projects.

A case in point is the emergence of data security posture management (DSPM) technology. According to Gartner, DSPM provides visibility into where sensitive data is, who has access to that data, how it has been used, and what the security posture of the data stored or application is. It does that by assessing the current state of data security, identifying potential risks and vulnerabilities, implementing security controls to mitigate these risks, and regularly monitoring and updating the security posture to ensure it remains effective. As a result, it enables businesses in maintaining the confidentiality, integrity, and availability of sensitive data.

This innovation improves observability, insight, and remediation, and enables a truly composable zero trust security architecture. Adopting DSPM technology requires businesses to invest in this nascent but rapidly developing market to overcome gaps in their existing security investments.

Tool and technology consolidation will be possible over time, but DSPM offers value both directly as a solution for building broad and deep knowledge of the valuable data you have and for improving the performance of any system that relies on an understanding (classification, tagging, labeling, or identifying security and compliance risk) to apply controls. Additional investment is required upfront, but the integrated business value is apparent when considering the efficiencies, cost savings, and audit/fine avoidance that DSPM makes possible.

Advice/best practices to consider in 2024

• Understand the business outcomes you want to achieve.


• Identify the scope of the projects that will enable you to achieve those outcomes and address the risks present in the data, access to that data, and the applications that use it.


• Challenge your teams and vendors to produce a total economic impact assessment of existing and potentially new technology investments. This will help you identify how an investment can result in cost optimization or synergies that can create a business case for additional investments that will result in cost savings and tool consolidation.

Trend #2: Enterprises recognize the need for speed -- and especially automation

Generative AI dominated the headlines in 2023. The potential and the risks of the technology moved from discussions in tech-savvy circles to the mainstream. For data and analytics pros, the cloud long ago introduced a new era of productivity and agility. However, the permissive nature of the cloud and the emergence of microservices and composable architectures resulted in sprawl, unsanctioned applications, and data proliferation that challenged human-initiated processes.

To enable the business benefits of automation, security and data professionals must also invest in automation. Automation is critical for deriving insights due to the rapid pace at which data is being created, consumed, and shared. Automation is also critical to identify what data a business has, where it is located, who has access to it, how it is exposed to risks, and how to remediate those risks.

Advice/best practices to consider in 2024

• Perform a risk quantification, trying -- to the extent possible -- to factor in the unknowns in your environment. Marry the results to an overall business risk assessment to understand your tolerance for the risks your business faces.


• Identify the total cost -- in people and time -- and the aggregate financial impact of both human-initiated processes and the opportunity cost of potentially eliminating them. This must include the exposure you face from business opportunity costs, regulatory fines and penalties, and the financial impact that data misuse or breaches can have on your business.


• Finally, determine how automating elements of your data discovery, classification, risk quantification, and remediation can impact those risks to prioritize investment.

Trend #3: Data sharing and observability meet AI

In 2023, business leaders continued their quest to become more data-driven. The promise is that by consuming, analyzing, and extracting insights from data, every business can unlock the value present in patterns and predict how to maximize the value of interactions with customers or new revenue streams that their existing business can create. To achieve this, data sharing is essential to understand the organizational ecosystem.

Similarly, every business is investing in observability to trace the flow of data and extract insights from that ecosystem. Today's businesses are composed of various data elements that culminate into a practical data fabric that enables them to derive those insights. However, the data and workflows are so complex that today’s environments now require AI to extract transformational insights.

Advice/best practices to consider in 2024

• Focus on how to optimize value for your business. Focus on use cases: What are you attempting to use data for? What new processes, optimizations, or critical insights are you looking to derive with a data-driven project or process? From there, compose the ecosystem of data and people necessary to successfully complete the project.


• Once a use case and project are identified, evaluate how emerging AI and machine learning technologies can accelerate time to value or overcome the inherent challenge of human-initiated activities. This will enable the management of AI risks and rewards and guide the adoption of new technologies.


• Implementing observability tools is necessary to identify whether any issues or errors are being introduced into your processes. Governance and policies must be established to maintain ethical, business, and compliance alignment as the project matures.