Remove Big Data Remove Data Governance Remove Data Security Remove Data Warehouse
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Data Vault 2.0: What You Need to Know

Astera

With its foundation rooted in scalable hub-and-spoke architecture, Data Vault 1.0 provided a framework for traceable, auditable, and flexible data management in complex business environments. Building upon the strengths of its predecessor, Data Vault 2.0 What’s New in Data Vault 2.0? Aspect Data Vault 1.0

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So Many Choices…. Oh My! Choosing the right Cloud Data Warehouse for my Modernization Project

Actian

So, you have made the business case to modernize your data warehouse. But how do you effectively go about choosing the right data warehouse to migrate to? Should you stay with your existing traditional data warehouse provider as they try to convince you to stay on-premise with their latest appliance?

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Scalable ETL Architectures: Handling Large Volumes of Data 

Astera

ETL architectures have become a crucial solution for managing and processing large volumes of data efficiently, addressing the challenges faced by organizations in the era of big data. ETL architectures ensure data integrity and enable organizations to derive valuable insights for decision-making.

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Data Warehouse vs. Database: Understanding the Differences

Astera

Businesses rely heavily on various technologies to manage and analyze their growing amounts of data. Data warehouses and databases are two key technologies that play a crucial role in data management. While both are meant for storing and retrieving data, they serve different purposes and have distinct characteristics.

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A Look Inside the Modern Analytics Stack

Dataversity

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

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What Is Data Management and Why Is It Important?

Astera

Free Download Here’s what the data management process generally looks like: Gathering Data: The process begins with the collection of raw data from various sources. Once collected, the data needs a home, so it’s stored in databases, data warehouses , or other storage systems, ensuring it’s easily accessible when needed.

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How to Build a Data Pipeline: A Step-by-Step Guide

Astera

For instance, they can extract data from various sources like online sales, in-store sales, and customer feedback. They can then transform that data into a unified format, and load it into a data warehouse. Facilitating Real-Time Analytics: Modern data pipelines allow businesses to analyze data as it is generated.