As the digital era continues to evolve, the significance of data is increasing exponentially with its volume, velocity, and utility reaching unprecedented levels. With data applications and analytical tools becoming staples in our everyday work lives, there's a growing need for a user-friendly, low-code, or no-code data platform for enhancing data-driven decision-making and streamlining daily business operations.
Metrics stores stand out as an ideal solution to serving as the core data servicing layer for modern day data platforms. Coupled with Natural Language Processing (NLP) and AI algorithms, these stores can significantly reduce, or even eliminate, the reliance on SQL for business users, making insights more accessible to a broader audience.
Although data engineering has come a long way, there's still a need to make valuable insights available to regular business users, not just power users adept at using SQL. An effective data platform must cater to the non-technical users like store managers, sales representatives, and marketers who may lack advanced SQL skills but need access to critical insights for their roles.
Low-code/no-code (LC/NC) data platforms aim to address this challenge by simplifying data access and analysis for citizen data analysts and scientists. Instead of relying on query languages like SQL or Python scripts, LC/NC data platforms allow users to focus on crucial business information and performance indicators rather than mastering technical skills.
To build an LC/NC data platform, businesses should leverage a Metrics Store as their main data service layer. By defining, calculating, and storing business metrics in a centralized location, end-users can easily utilize these metrics within their tools, such as Excel spreadsheets, BI dashboards, and web applications. This approach ensures that relevant data points are accurately defined, calculated, and made accessible to everyone across the organization.
Natural language capabilities provided by NLP can enable users to ask questions in plain English, making data platforms more user-friendly and interactive. Combining NLP with context awareness empowers these platforms to facilitate a conversational experience between the 'machine' and the users, allowing for improved responsiveness to follow-up questions and promoting better overall user engagement.
Integrating AI into data platforms paves the way for quicker and more efficient data and metadata analysis and enhances user experiences. AI algorithms can predict the questions users may ask and prepare the answers beforehand, making data interaction seamless and gratifying. In addition, AI-driven data optimization processes help eliminate waste and reduce costs.
When emerging technologies like metric stores, NLP, and AI come together, they pave the way for a low-code/no-code platform that modernizes and revolutionizes data handling. AppMaster.io is a no-code platform that incorporates these principles, enabling efficient backend, web, and mobile applications development in a code-free manner. AppMaster.io simplifies application development, making it more accessible to businesses and ensuring that vital insights are available to a broader audience, empowering their decision-making processes.
