Data Visualizers are experts in creating insights and visualizations from raw data. They have a deep understanding of data visualization techniques, which is crucial for understanding audience preferences and viewing habits and making strategic decisions based on visualized insights.

The blank should be filled with "YARN." YARN (Yet Another Resource Negotiator) is responsible for resource management and workload monitoring in Hadoop clusters. It plays a crucial role in managing and scheduling jobs across the cluster.

Apache Kafka is more suitable for real-time data processing. It is a distributed streaming platform that can handle high-throughput, fault-tolerant, and real-time data streams, making it a popular choice for real-time data processing and analysis.

Semantic segmentation is an advanced computer vision technique that involves classifying each pixel in an image into a specific class or category. It's used for tasks like identifying object boundaries and segmenting objects within an image.

The role of a hidden layer in a neural network is to extract and transform features from the input data. Hidden layers learn to represent the data in a way that makes it easier for the network to make predictions or classifications. They are essential for capturing the underlying patterns and relationships in the data.

Data Scientists are typically proficient in advanced statistical modeling. They use statistical techniques to analyze data and create predictive models. While Data Analysts may also have statistical skills, Data Scientists specialize in this area.

A formal review is a structured evaluation process aimed at identifying inconsistencies between a work product and its input criteria, which can include requirements, standards, or specifications. It helps ensure the quality and correctness of the work product.

The "right to explanation" is important as it promotes transparency in AI decision-making. In ethical AI, users should have insight into how AI algorithms arrive at their decisions. This transparency is vital to prevent bias, discrimination, and unethical decision-making, making it a critical aspect of AI ethics.

To combat the vanishing gradient problem in RNNs, a common approach is to use Long Short-Term Memory (LSTM) units. LSTMs are designed to alleviate the vanishing gradient issue by allowing gradients to flow over longer sequences.

Standardization is the process of transforming data to have a mean of 0 and a standard deviation of 1. This helps in making data more interpretable and suitable for various machine learning algorithms, as it removes the scale effect.