Data Management Is Just for IT? Assessing Traditional Code, Low-Code, and GenAI
Discover how businesses can benefit from LC/NC solutions and why democratizing data access is essential for agile decision-making.
Imtiaz Mohammady, CEO of Nisum, explores how leveraging low-code/no-code solutions and generative AI can empower business units to manage their data pipelines and automate tasks, fostering agility and enhancing decision-making processes.
In 2023, a triple squeeze of economic pressure and tech talent with a high price tag led Chief Information Officers (CIOs) to focus on tidying up operations for maximum returns: 60% of CIOs opt to get more out of existing data with advanced analytics—makes sense, right?
The rise of AI and evolving digital capabilities are tripling IT workloads. However, the talent pool isn’t growing at the same pace. CIOs must democratize data access to empower business units to maximize their data value without lengthy IT request queues. Low-code/no-code (LC/NC) and generative AI solutions can alleviate this pressure by enabling business users to build basic applications and automate tasks without extensive coding expertise.
Shifting to a data-driven culture requires buy-in from all levels. When CIOs and Chief Experience Officers (CXOs) unite, they can align communication and training to support employees through the transition. Combining budgets and resources helps democratize data practices across staff, bringing access to data insights closer to the teams who need them.
While large enterprises have already incorporated a data expert into each business function, many team members are still data novices. Here’s how LC/NC solutions and generative AI can take some of the heavy lifting — if used correctly.
The Challenge for CIOs
Each department has its own budget, applications, and data. These data silos can lead to inconsistent formats, missing values, and inaccuracies, misleading results. In some cases, CIOs assign data analysts to each business unit, who fulfill their department data preparation and analysis tasks. Nevertheless, this can be a costly hierarchy, with analysts often feeling isolated and undersupported — making them easy targets to poach. It is not ideal when 32% of CIOs are also hiring for vacated roles.
Moreover, most business processes require cross-functional data. This is why many companies opt for a central data team with training and mentorship opportunities. However, if each department must queue its requests, such as advancements to customer relationship management (CRM) tools or upgrading stock trackers, this can limit the speed of response. Not to mention, there is reduced domain knowledge as data analysts are separated from business functions.
Organizations looking to stay competitive must harness data swiftly and effectively, an increasingly challenging endeavor as data volumes and process complexity rise. Traditional data practices where departments rely solely on IT teams for data-related tasks lead to bottlenecks, delays, and limited agility.
Bringing Agility into Business Functions
Designing, modeling, and implementing robust, scalable data environments and pipelines that obey regulatory, workflow, and labeling standards is the work of an engineer. However, LC/NC solutions with user-friendly interfaces, drag-and-drop options, and data governance features mean business users, or citizen developers, can manage their own data pipelines while retaining data trustworthiness.
LC-NC uses visual and graphical tools, enabling citizen developers to build, implement, and operate routine programming tasks with little to no coding skills, closing the skills gap. Generative AI’s ability to communicate with applications using human language also breaks down coding barriers, democratizing data management tasks.
When business units implement LC/NC solutions with generative AI, they speed up data-driven decision-making with more autonomy over their data. For example, a marketing specialist wants to know how their latest product campaign performed across website, paid ads, email, and social media. Rather than asking an analyst to pull the report, they can simply ask the virtual AI assistant.
Citizen developers can adapt LC/NC solutions with large generative AI models to their needs with little development effort or programming expertise. These tools enable them to focus on the specific use case using their domain knowledge, with faster time to market and reduced costs — using existing central processing units (CPUs) or AI accelerators instead of draining resources to build a foundational model from scratch.
These solutions enforce data consistency with common dimensions, definitions, and logic, enabling departments to create speedy, agile analyses. In addition, standardized pipelines and formatting make cross-functional integration more seamless.
See More: Why CIOs Are Leading Business Development for Life Sciences
Governance and Training
Although LC/NC tools require little to no programming skills, training on basic concepts of LC/NC application development and best practices is crucial to ensure these tools are used properly and safely. As business units increase their data independence, a large part of the central analyst expert’s role becomes governance and training-focused.
The benefits and downfalls of AI are that it’s the greediest data consumer, with huge processing power and the capacity to digest vast amounts of data in seconds. This adds to the data management challenge as it can gobble up sensitive personal data (PII) and reproduce it to the wrong audience.
This is why CIOs and CXOs must work together to ensure every team member is well-educated on data protection rights and the risks of not following policy. They can do this with attendee-monitored, company-wide training courses and annual refreshers. IT leaders could offer company-wide training events or hackathons to deepen employees’ knowledge and challenge them to maximize their new skills.
Similarly, central analysts must know any LC/NC vendors acting on business units’ data. They should ensure all PII stays on internal systems with legal and regulatory control. Analysts can guarantee business units comply with regulations by using LC/NC solutions that incorporate data anonymization tools for data sharing, along with continuously monitoring internal and external data usage; by analysts.
In the hands of an IT professional, more complex tasks can also be completed, meaning AI can help with security functions, too. Many LC/NC platforms can automate security workflows such as user provisioning and de-provisioning, vulnerability scanning, and access control audits. This streamlines security processes and reduces manual effort, allowing developers to focus on more strategic tasks. However, experienced developers should perform thorough security testing to eliminate unforeseen vulnerabilities.
For agile and secure data management, all employees need to shift their mindset to prioritize data protection and understand non-compliance risks. LC/NC solutions and generative AI help data teams build business intelligence quickly, aligning applications with regulations. The bottom line is that data is each business unit’s most valuable asset for growth and market adaptation, which is why faster integration cycles are key to competitiveness. Collaboration features promote cross-functional teamwork and a holistic view for data analysts to govern and improve platforms easily and quickly.
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