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Cloud Data Warehouse: A Comprehensive Guide

Astera

What is a Cloud Data Warehouse? Simply put, a cloud data warehouse is a data warehouse that exists in the cloud environment, capable of combining exabytes of data from multiple sources. A cloud data warehouse is critical to make quick, data-driven decisions.

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Finance Data Warehouse for Reporting and Analytics

Astera

It serves as the foundation of modern finance operations and enables data-driven analysis and efficient processes to enhance customer service and investment strategies. This data about customers, financial products, transactions, and market trends often comes in different formats and is stored in separate systems.

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The Ultimate Guide to Enterprise Data Warehouse

Astera

But have you ever wondered how data informs the decision-making process? The key to leveraging data lies in how well it is organized and how reliable it is, something that an Enterprise Data Warehouse (EDW) can help with. What is an Enterprise Data Warehouse (EDW)?

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Modern Data Warehouse: Why Should You Migrate?

Astera

D ata is the lifeblood of informed decision-making, and a modern data warehouse is its beating heart, where insights are born. In this blog, we will discuss everything about a modern data warehouse including why you should invest in one and how you can migrate your traditional infrastructure to a modern data warehouse.

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Real-Time Data Drives Reporting Success With Wands for Oracle

Insight Software

Users need to go in and out of individual reports to get specific data they are looking for. Access to Real-Time Data Can Revolutionize Your Reporting To sidestep the negative effects of outdated data, your reporting tool should prioritize data quality, accuracy, and timeliness. Enable cookies.

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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.

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Data Integration 101: Understanding The Basics

Astera

Data movement involves data transformation, cleansing, formatting, and standardization. Data Quality Consideration Emphasis is on data availability rather than extensive data quality checks. Enforces data quality standards through transformations and cleansing as part of the integration process.