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Data Vault 2.0: What You Need to Know

Astera

Building upon the strengths of its predecessor, Data Vault 2.0 elevates data warehouse automation by introducing enhanced scalability, agility, and adaptability. It’s designed to efficiently handle and process vast volumes of diverse data, providing a unified and organized view of information. Data Vault 2.0

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The Future of AI in Data Warehousing: Trends and Predictions 

Astera

Data management can be a daunting task, requiring significant time and resources to collect, process, and analyze large volumes of information. AI is a powerful tool that goes beyond traditional data analytics.

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What is a Data Pipeline?

Astera

Evolution of Data Pipelines: From CPU Automation to Real-Time Flow Data pipelines have evolved over the past four decades, originating from the automation of CPU instructions to the seamless flow of real-time data. Initially, pipelines were rooted in CPU processing at the hardware level.

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Use Case Analysis for Business Intelligence Projects

Business Analysis Knowledge Share

This may involve data from internal systems, external sources, or third-party data providers. The data collected should be integrated into a centralized repository, often referred to as a data warehouse or data lake. Data integration ensures that all necessary information is readily available for analysis.

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What is ETL? – Extract, Transform, Load Explained

Astera

Reverse ETL is a relatively new concept in the field of data engineering and analytics. It’s a data integration process that involves moving data from a data warehouse, data lake, or other analytical storage systems back into operational systems, applications, or databases that are used for day-to-day business operations.

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What Is Ad Hoc Reporting? Your Guide To Definition, Meaning, Examples & Benefits

Data Pine

Ad hoc reporting, also known as one-time ad hoc reports, helps its users to answer critical business questions immediately by creating an autonomous report, without the need to wait for standard analysis with the help of real-time data and dynamic dashboards. Artificial intelligence features.

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What is a Data Pipeline?

Insight Software

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.