Operationalizing Large Language Models (LLMs) is the next big opportunity in AI. Any organization…
Enable Non-Technical Users to Access and Use Data Effectively
Building a robust, unified data solution is only the first step in creating value from data and analytics. The users are just as important, as those with access are the bottleneck through which all data must move. Therefore, by increasing the amount of users with access to the data they need, the speed at which data becomes valuable increases.
However, hiring new employees or providing technical training is expensive and time-consuming, even when the job market supports growing a team. Imagine, instead, that current employees across business units, even without technical backgrounds, could be given access to the data they need, in the format they need it in, without having to submit requests to data engineering teams or requiring new pipelines to be built.
By providing non-technical users the ability to access and request data as needed, the bottlenecks on processing are decreased, the value of data is increased, and decisions are more often informed by current, accurate data and analytics. That’s the beauty of a unified data solution powered by automated data engineering and a low-code/no-code interface–it enables everyone to become experts on the data they use, regardless of background.
Two elements combine to allow non-technical users to access and use data effectively: low-code/no-code interfaces and automated data engineering through data products.
Data products are the foundation of automating data engineering, and data mesh is the framework in which it happens. Nexla, as a unified data solution, processes data into Nexsets, which are logical entities encapsulating data into a product that can be easily tagged, managed, sorted, transformed, delivered, or otherwise used. Nexsets abstract data heterogeneity so users have a consistent interface no matter the format or velocity. Having this consistent interface is one of the key elements to increasing the approachability of data for non-technical users.
By packaging data into data products, it becomes easier to decouple storage from set structures and processes. Data can be accessed across departments, teams, and business units without having to build new pipelines. They also minimize resource usage and competition to increase time-to-value for data and lower data costs.
Low code is quickly becoming one of the foundations for hyperautomation and business automation and according to Gartner, is projected to grow extensively by the year 2027. This is credited to the self-service features that enable cross-specialty teams to access data accurately, promptly, and without having to wait for specific reports or data engineering teams.
While low code increases the access, no code is the standard for non-technical users. Drag-drop or form interfaces are the easiest way to encourage those without coding experience to try a self-serve interface. No-code interfaces, however, remove all possibility of custom coding.
Nexla’s low-code and no-code interfaces
While the interface is the most important aspect to the non-technical users, it works in conjunction with the automated data products to allow users to search for tags, data, and metadata or let data engineering teams create and share data sources or credentials securely while maintaining governance and security oversight. Without the concern of non-technical users accessing code or data that may cause issues, users are encouraged to explore and play with data to find not only what they need now but also what may help them grow in the future.
Enabling users to access the data they need without requiring extensive education or training is an effective way to grow data value without increasing the resources needed to run or maintain it. By making better use of existing teams and experts, data costs are lowered, time to value is decreased, and people get the data they need when they need it, giving more power to teams to get sophisticated tasks done.
A low-code/no-code interface is the first step in democratizing data like this, and it is most effective when paired with automated data engineering that empowers even the most non-technical users to request, access, transform and use data. If you’re looking to speed up time to value while enabling non-technical users, get a demo or book your free unified data solution strategy session today. For more on data and data solutions, check out the other articles on Nexla’s blog.
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