L4: Data Literacy

Ensuring data accuracy and consistency through Atomicity, Consistency, Isolation, and Durability (ACID) in database transactions.

Cloud-hosted integration platforms that offer integration services through virtual private clouds or hybrid cloud models, providing scalability and flexibility.

A type of NoSQL database that organizes data in cells grouped as columns, often used for systems requiring high write request volume and storage of time-series or IoT data.

Data that is stored and not actively in motion, typically residing in a database or storage system for various purposes, including backup.

A discipline involving practices, architectural techniques, and tools that enable organizations to ingest, transform, combine, and provision data across various data types, used for purposes such as data consistency, master data management, data sharing, and data migration.

A data repository for storing large volumes of structured, semi-structured, and unstructured data in its native format, facilitating agile data exploration and analysis.

A subset of a data warehouse designed for specific business functions or user communities, providing isolated security and performance for focused analytics.

A comprehensive data movement process that covers the entire journey of data from source systems to destination systems, which includes data integration as a key component.

A general term referring to data that has been collected, organized, and isolated for business operations or data analysis. It can include databases, data warehouses, and big data stores.

A central repository that consolidates data from various sources through the Extract, Transform, and Load (ETL) process, making it accessible for analytics and business intelligence.

A type of NoSQL database that stores each record and its associated data within a single document, allowing flexible indexing, ad hoc queries, and analytics over collections of documents.

The Extract, Transform, and Load process for data integration involves extracting data from various sources, transforming it into a usable format, and loading it into a repository.

A type of NoSQL database that uses a graphical model to represent and store data, ideal for visualizing, analyzing, and discovering connections between interconnected data points.

A type of NoSQL database where data is stored as key-value pairs, with the key serving as a unique identifier and the value containing data, which can be simple or complex.

The capability of data integration tools to be used in various environments, including single-cloud, multi-cloud, or hybrid-cloud scenarios, provides flexibility in deployment options.

Cataloged connectors and adapters that simplify connecting and building integration flows with diverse data sources like databases, flat files, social media, APIs, CRM, and ERP applications.

Databases that organize data into a tabular format with rows and columns, following a well-defined structure and schema.

The ability of a data repository to grow and expand its capacity to handle increasing data volumes and workload demands over time.

The predefined structure that describes the organization and format of data within a database, indicating the types of data allowed and their relationships.

Data that is continuously generated and transmitted in real-time requires specialized handling and processing to capture and analyze.

Applications such as Online Transaction Processing (OLTP), Data Warehouses (OLAP), and IoT solutions where relational databases excel.

A situation where a user becomes dependent on a specific vendor’s technologies and solutions, making it challenging to switch to other platforms.