| Analytics Engineer |
A professional who focuses on developing and implementing analytics solutions, including data modelling, data transformation, analysis, and visualization. |
| Data Architecture |
The design and organization of data-related components, including databases, data models, and data storage. |
| Data Engineer |
A professional responsible for designing, building, and maintaining data architecture, infrastructure, and tools for data processing. |
| Data Ingestion |
The process of collecting, importing, and processing raw data from different sources into a data storage or processing system. For more information on how to ingest data check out the Datacoves offering. |
| Data Lake |
A centralized repository that allows the storage of structured and unstructured data at any scale, enabling diverse analytics and data processing. |
| Data Lineage |
The tracking of the flow and transformation of data from its origin through various processes and systems, providing visibility into data movement. |
| Data Loading |
The process of inserting data into a database or data warehouse from external sources. |
| Data Mesh |
Data Mesh is a decentralized approach to data management where each team treats their data as a distinct, easily accessible product, promoting collaboration and efficiency across an organization. |
| Data Migration |
The transfer of data from one system to another, often involving the movement of data between storage systems or databases. |
| Data Modelling |
The process of defining the structure and relationships of data to create a blueprint for organizing and representing information in a database. |
| Data Observability |
The practice of monitoring, measuring, and ensuring the reliability, performance, and quality of data in a system. For more information check out the Five Pillars of Data Observability by Monte Carlo. |
| Data Orchestration |
The coordination and management of various data processing tasks that ensure seamless end to end processing of data from ingestion through integration and finally activation / consumption. |
| Data Pipeline |
A set of processes and tools for moving and transforming data from source to destination, typically in a systematic and automated way. |
| Data Platform |
A comprehensive infrastructure or ecosystem that supports various aspects of data management, including storage, processing, analytics, and visualization. For more information on the accelerators provided to set up the platform, check out the Datacoves offering. |
| Data Silos |
Isolated or segregated storage of data within an organization, hindering efficient data sharing and collaboration between different departments or teams. |
| Data Stack |
The combination of technologies and tools used in a data ecosystem, often comprising databases, data processing, analytics, and visualization tools. |
| Data Visualization |
The representation of data in graphical or visual formats to help users understand patterns, trends, and insights. |
| Data Warehouse |
A centralized repository for storing and managing structured and/or unstructured data from various sources, designed for efficient querying and reporting. |
| DataOps |
A set of practices that combines aspects of development (DevOps) and data management to improve collaboration and productivity across data engineering, data integration, and data analysis teams throughout the entire data lifecycle. |
| ELT (Extract, Load, Transform) |
A data processing approach where raw data is first loaded into a data warehouse and then transformed as needed. Check out 10 Best Data Transformation Tools for a Smoother ELT Process. |
| ETL (Extract, Transform, Load) |
A traditional data processing approach where data is extracted from source systems, transformed, and then loaded into a target system. Check out 10 Best Data Transformation Tools for a Smoother ELT Process. |
| ETL Pipeline |
The process of extracting data from various sources, transforming it into a suitable format, and loading it into a target system, typically a data warehouse. Checkout how Datacoves helps you Load, Transform, and Orchestrate your data. |
| Linting |
The process of analyzing code or data for potential errors, inconsistencies, or non-compliance with coding standards. The process of analyzing code for errors, inconsistencies, or non-compliance with coding standards. Tools like SQLFluff are commonly used for linting SQL. |
| Modern Data Stack |
A modern and integrated set of tools and technologies for handling data, often including cloud-based services and open-source components. Check out how you can Accelerate your Modern Data Stack. |
| Platform Engineer |
A professional involved in designing, building, and maintaining the underlying infrastructure and platforms that support software applications and data systems. |
| Query |
A request for information from a database, typically written in a specific language (e.g., SQL), to retrieve or manipulate data. |
| Reverse ETL |
The process of moving data from a data warehouse or analytics platform back to operational systems or other applications for various use cases. |
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