'Chart junk' refers to unnecessary or distracting decorations in a chart that do not enhance understanding and can even mislead the viewer. It includes excessive gridlines, decorations, or embellishments that clutter the visual and divert attention from the actual data.

The blank is filled with "Exponential Smoothing." Exponential smoothing is a widely used statistical method in time series analysis to predict future values by assigning different weights to past observations, with more recent values receiving higher weights. This technique is particularly useful for forecasting when there is a trend or seasonality in the data.

Both Tableau and Power BI employ strategies like in-memory processing and data partitioning to handle big data scalability and enhance performance. This allows users to analyze and visualize large datasets efficiently.

Apache Hadoop is a distributed database management system specifically designed for handling large-scale data across multiple nodes. It is commonly used in big data processing. MongoDB, MySQL, and SQLite are database systems but are not specifically designed for distributed large-scale data.

Apache Kafka is a distributed streaming platform that is commonly used to handle real-time data streams. It allows for the processing and analysis of data in real-time, making it a suitable choice for analyzing social media data as it is generated.

The "UNIQUE" constraint in SQL ensures that all values in a column are unique, meaning no two rows can have the same value in that column. It is often used to enforce data integrity and prevent duplicate entries.

In business process improvement case studies, the Six Sigma framework is commonly applied to identify inefficiencies, reduce variability, and enhance overall process performance. Six Sigma focuses on data-driven decision-making and process optimization.

The output will be a list containing the characters of the string "123" in reverse order. The [::-1] slicing reverses the string, and list() converts it into a list of characters.

SQL is based on the relational database model. It uses tables to organize data and relationships between them, making it a powerful and widely used language for managing relational databases.

In scenarios involving large volumes of unstructured data, a NoSQL database management system (DBMS) is well-suited. NoSQL databases offer flexibility and scalability, making them suitable for handling unstructured data types like documents, graphs, and key-value pairs.