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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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Data Vault 2.0: What You Need to Know

Astera

With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, What is Data Vault 2.0? Data Vault 2.0

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Modernize Your ETL Processes, Discover Better Insights

Sisense

Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

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OLTP and OLAP: Two Sides of the Same Data Coin?

Astera

This means that they use a data model that minimizes redundancy and ensures data consistency. Low data latency: OLTP systems offer low data latency and provide real-time data updates, ensuring immediate availability of updated data to users.This is important for applications that require real-time data access and responsiveness.

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The Future of AI in Data Warehousing: Trends and Predictions 

Astera

By AI taking care of low-level tasks, data engineers can focus on higher-level tasks such as designing data models and creating data visualizations. For instance, Coca-Cola uses AI-powered ETL tools to automate data integration tasks across its global supply chain to optimize procurement and sourcing processes.

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Too Much Data, Too Few Actionable Insights…Too Late!

Actian

The key to converting data into actionable insights is having the right set of tools and a structured method for processing data through a value stream to generate progressive levels of refinement. There are only 2 levels of refinement (aggregation into the warehouse and curation into reports) occurring.

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Build Data Warehouse with Concentrated Teams

Astera

Enterprises will soon be responsible for creating and managing 60% of the global data. Traditional data warehouse architectures struggle to keep up with the ever-evolving data requirements, so enterprises are adopting a more sustainable approach to data warehousing. Best Practices to Build Your Data Warehouse .