Data integration can take up to 30-40% of total development time, complicating developers' workflows and compromising the reliability of data. Learn how a Data Hub integrated with a low-code platform can provide the ideal solution to build applications with always-available, up-to-date data.
Companies invest significant time and resources in integrating data dati during development of business applications, but often fail to fully leverage it for informed decision-making. This issue stems from a combination of technical, organizational, and strategic factors.
Business data is often distributed across silos, such as ERP systems, CRMs, legacy databases, or spreadsheets. This fragmentation makes accessing the right information at the right time challenging. Additionally, thelack of standardizationacross systems, with , with varying formats, structures, and logic, further complicates data usage.
Developers are often forced to spend a significant amount of timeretrieving, reconciling, and transforming dataThis process, which includes creating connections between systems, building custom APIs, and configuring data pipelines, requires advanced technical skills, considerable effort and ongoing maintenance to keep integrations functional.
Another complication arises the lack of real-time data: many systems rely on batch updates or manual synchronizations, leading to delays and producing outdated or incomplete data—unsuitable for applications requiring immediate insights.
Each new application adds further layers of complexity to the company’s data infrastructure. Even when data is integrated, it often lacks the context neededto generate actionable insights. Ambiguous field names, complex calculations, and inconsistent formats pose obstacles for developers, while business users require contextualized informationdirectly linked to the problems or opportunities at hand.
Without a clear and contextualized framework, seemingly significant data—such as a drop in sales—can be misinterpreted, especially if not compared to historical trends or market benchmarks. The combination ofmissing contextand and growing system complexity limits the value of generated insights, undermining the company’s ability to make effective, informed decisions.
The development of business applications increasingly revolves around data, but as previously highlighted, the integration and management of fragmented information across silos represent a significant challenge.
Developers must identify relevant data, understand itsoften complex context due to non-standard structures and logic, and integrate it by building connections and transformations that require time and advanced expertise.
In this context,A Data Hub is a centralized platformrepresent revolutionary opportunity. They combine the ability to unify and manage enterprise data with the simplicity and speed of low-code development, enabling the creation of data-driven applications without the technical complexities of traditional methods.
What is a Data Hub? A Data Hub is a centralized platform designed to simplify the access, discovery, and utilization of distributed data within an organization by leveraging metadata. Metadata provides a structured description of dataincluding its meaning, structure, relationships with other entities, and governance rules. Within a Data Hub, metadata helps developers and business users quickly understand the context of data, track its ownership, and manage access permissions. For example, metadata might describe the "Customer ID" field as a as a unique identifier in the CRM linked to transactions in an ERP system.
Integration with ow-code platforms further amplifies the value of a Data Hub, allowing developers to treat external data as if it were “local” to the application. This means that even if the data resides in external systemsit can be utilized in the application as if it were already integrated into its database. Metadata provides a clear interface for exploring and using data, enabling developers to query and use it directly within applications.
At WEGG, as consultants specialized in process digitalization, our goal is to ensure that developed applications not only support business operations but also deliver immediate knowledge for informed decision-making. For this reason, we avoid traditional solutions like ETL or complex integrations, focusing instead on development technologies that providesimple, direct, and contextualized access to enterprise data.
Sull’We’ve already discussed how low-code development how low-code development improves project efficiency compared to traditional methods. here, quello che spesso viene trascurato sono sia la qualità dell’integrazione dei dati sia il tempo necessario per garantirla. Per questo la nostra scelta ricade su Mendix, una piattaforma che combina la potenza del low-code con un Data Hub integrato.
Un elemento fondamentale del Data Hub di Mendix è la capacità di utilizzare connettori predefiniti per accedere ai dati provenienti da sistemi esterni come ERP, CRM, piattaforme cloud o database legacy. Questi connettori non solo facilitano l’accesso diretto alle fonti, ma, integrati con il Data Hub, catalogano automaticamente i metadati e rendono disponibili informazioni contestualizzate, utilizzabili in tempo reale. Questo consente di trattare i dati esterni come se fossero locali, semplificando l’integrazione e garantendo applicazioni affidabili e aggiornate.
Per quanto riguarda la gestione dei dati basati su aggiornamenti manuali o asincroni, la tecnologia di Mendix adotta un approccio event-driven. Grazie alla gestione degli eventi aziendali, è possibile monitorare i cambiamenti nei dati o nei processi aziendali, attivandoli come trigger per eseguire automaticamente azioni e flussi di lavoro. Questo garantisce che le applicazioni rimangano sempre allineate ai processi aziendali in corso, eliminando inefficienze e interventi manuali.
Per questo consigliamo di adottare fin dall’inizio pratiche di sviluppo già allineate all’evoluzione aziendale. Usare soluzioni di questo tipo a supporto della digitalizzazione dei processi consente di realizzare sistemi flessibili e reattivi, capaci di fornire informazioni utili e tempestive per decisioni informate.
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