# A Survey on Video Big Data Analytics: Architecture, Technologies, and Open Research Challenges
## 3 VBDA Architectures and Core Technologies
### VBDA Core Technologies
#### 3.2.5 Visualization and Interpretability  
Table 7 describes an overview of the key visualization tools adopted in VBDA systems from 2018 to 2025, highlighting their integration scopes, functional roles, and typical application contexts. These tools support tasks ranging from real-time monitoring and operational oversight to statistical analysis, model debugging, and interactive system feedback. Among enterprise solutions, Tableau and Power BI are widely used to deliver interactive dashboards for performance tracking and system health assessment [149]. Alternatives such as Qlik Sense and Apache Zeppelin ([[https://zeppelin.apache.org](https://zeppelin.apache.org)]([https://zeppelin.apache.org](https://zeppelin.apache.org)), ac \begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline
**Reference** & **Year** & **Tableau** & **Power BI** & **Zeppelin** &
\begin{tabular}{c} **Qlik** \\ **Sense** \\ \end{tabular} & **Grafana** & **Kibana** \\ \hline [PERSON] et al. [108] & 2024 & ✓ & & & & & \\ [PERSON] et al. [147] & 2024 & ✓ & ✓ & & & \\ [PERSON] et al. [148] & 2022 & ✓ & ✓ & & ✓ & & \\ [PERSON] et al. [112] & 2022 & & & & & & ✓ \\ [PERSON] et al. [149] & 2022 & ✓ & ✓ & & & ✓ & ✓ \\ [PERSON] et al. [113] & 2022 & ✓ & ✓ & & & & ✓ \\ [PERSON] et al. [117] & 2020 & & & & & & ✓ \\ [PERSON] et al. [100] & 2019 & & & ✓ & & & ✓ \\ [PERSON] et al. [123] & 2018 & ✓ & & & & & \\ \hline
**Total** & & **6** & **3** & **2** & **1** & **1** & **5** \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Technologies for data visualization and interpretation. cessed on 14 May 2025) are favored in scenarios requiring associative exploration and research-oriented debugging [112]. For time-series data and system logs, Grafana has gained popularity due to its flexible dashboarding, alerting features, and integration with Prometheus and InfluxDB [100], while Kibana remains prevalent in Elasticsearch-based environments [113]. In experimental and academic settings, Python libraries like Matplotlib, Seaborn, and Plotly enable customizable visualization of detection outputs, performance metrics, and training dynamics. Emerging visualization interfaces, including AR dashboards and 3D spatial renderings, are also being explored in high-risk domains such as disaster response and urban surveillance [117]. Although still limited in adoption, these immersive tools hold promise for improving spatial awareness and situational interpretation. Moving forward, the integration of explainable AI (XAI) elements such as heatmaps and semantic overlays into real-time dashboards is expected to enhance interpretability, human-AI interaction, and trust in automated VBDA systems. Figure 2 illustrates the most commonly adopted technologies across VBDA platforms between 2018 and 2025, highlighting a clear progression toward scalable and intelligent video analytics. At the data processing layer, Apache Kafka and Apache Spark stand out as dominant frameworks, each adopted by approximately 11% of of the 24 surveyed systems, owing to their robustness in managing distributed stream and batch workloads. In the AI-driven analysis layer, YOLO (9%) and LSTM (8%) are widely utilized for object detection and activity recognition, while emerging approaches such as CLIP and Transformer-based models are increasingly applied to multimodal video understanding. At the edge-cloud orchestration level, the use of FL with FedAvg (6%) and deployment via KubeEdge (6%) reflects a growing emphasis on privacy-preserving, low-latency computation at the network edge. For data management, Elasticsearch (6%) and MongoDB (3%) are frequently employed to support scalable indexing and semantic retrieval. Visualization remains a critical component, with tools like Tableau facilitating real-time dashboards for informed decision-making. Notably, the most prevalent technologies in these layers, including Kafka, Spark, YOLO, LSTM, FedAvg, and Elasticsearch, collectively appear in more than 50% of the surveyed platforms. This reinforces their foundational role in the current VBDA ecosystem.