Aggregations
In general aggregations are grouping functions. So, instead of returning single row or document data, the response is grouped by a certain criteria. Learn more about aggregations in this article.
Plain-language definitions of the data warehousing, analytics, and data engineering terms that matter.
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In general aggregations are grouping functions. So, instead of returning single row or document data, the response is grouped by a certain criteria. Learn more about aggregations in this article.
Airflow is a powerful open-source tool for orchestrating and managing workflows. Learn what are Airflow DAGs and how to use the, in this article.
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Columnar storage is a data organization technique where data is stored and retrieved by columns rather than rows. Learn about columnar storage vs row storage.
Customer facing analytics provides an opportunity for the data producer (Enterprise that owns the data) and data consumer (end user or customer) to interact through data.
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What are the data flattening and what is the data unflattening processes in data warehousing?Learn all you need to know about data flattening here.
Explore data lake architecture, implementation best practices, and performance optimization strategies. Learn how to build scalable data lakes with sub-second query performance.
Run analytics and ML on one platform with a data lakehouse. Combine warehouse performance with lake storage flexibility.
What Is Data Mesh? Learn the definition and the advantages of Data Mesh Implementation of in this article.
What are the data nesting and what is the data unnesting processes in data warehousing? Learn the definition and the meanings of data nesting inside.
Data observability is concerned with the health of your data, which is obtained from a variety of sources. Learn more about the definition of data observability here.
Data orchestration tools enforce the relationship and dependency between the tasks. Multiple tasks can be run simultaneously in this approach. Learn more about the definition of data orchestration.
Discover what a data warehouse is and its purpose. Learn how businesses use data warehouses for analytics, decision-making and is it right for you.
What is a data warehousing? Learn the definition of data warehousing, data warehousing concepts, benefits and much more.
A data-intensive application is an application that makes an intense usage of data in all its heterogeneous forms. Learn the definition of a data intensive application here.
Discover the core SQL components: DDL and DML. Understand their purposes, differences, and how they are used in database management.
What is DWaaS? How does a data warehouse as a service works? Learn the definition, the benefits and the challenges in this glossary article.
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What are ETL and ELT? Learn the definitions, differences, and when to use each for modern data pipelines.
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What are Materialized Views? What are the advantages and the challanges of Materialized Views? Learn all you need to know in this article.
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What is OLAP and what does OLAP stands for? Learn all you need to know OLAP, including OLAP vs OLTP, inside our glossary.
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Partitioning is a technique used in databases to break a single table into smaller chunks or partitions. Sharding typically references horizontal partitioning. Learn mote about the definitions of partitioning and sharding here.
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Discover how federated queries help web developers and data engineers run SQL across distributed data sources without ETL overhead.
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Send warehouse data to CRMs, ad platforms, and support tools with Reverse ETL.
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Data warehouses without servers act like regular centered repositories of information that can be accessed for analysis to aid decision making. Learn more about the definition of a serverless data warehouse.
Here are some SQL optimization tips and ricks, that are meant to be simple to implement and not compromise the overall code readability while giving you a performance. boost.
What is slowly changing dimension? Definition and examples of slowly changing dimensions in data warehousing.
Simply put, a Spark Job is a single computation action that gets instantiated to complete a Spark Action. Learn more about Spark Job in this article.
Explore SQL's evolution from traditional databases to high-performance cloud analytics, with tips for faster queries using Firebolt.
Stream data processing or simply stream processing is a Big data technology that goes by different names like real-time streaming analytics and event processing.
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Chapter 1: An introduction to Cloud Data Warehousing definition and concepts, cloud data warehouse architecture, and online analytical processing (OLAP).
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‘Upsert’ is a simple function when performed on a database because the in-built indexes of a database facilitate identification of a specific record or entry.