Remove Banking Remove Data Quality Remove Data Warehouse
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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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Guide to Data Warehouse: Concepts, Schemas and Benefits Explained

Astera

In the digital age, a data warehouse plays a crucial role in businesses across several industries. It provides a systematic way to collect and analyze large amounts of data from multiple sources, such as marketing, sales, finance databases, and web analytics. What is a Data Warehouse?

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Automated Credit Risk Assessment: How ETL Is Unlocking Better Investments

Astera

End-to-End Credit Risk Assessment Process The credit risk assessment is a lengthy process where banks receives hundreds of loan applications daily from various channels, such as online forms, email, phone, and walk-in customers. The data is stored in different locations, such as local files, cloud storage, databases, etc.

Banking 52
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CDC for ETL Process Optimization in Finance Industry

Astera

From managing customer transactions and financial records to dealing with regulatory requirements and risk management, data plays a crucial role in every aspect of banking operations. This data is categorized as big data, a term denoting “large, diverse sets of information that grow at ever-increasing rates.”

Finance 52
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How to Automate Credit Risk Assessment Framework Using ETL

Astera

The data is stored in different locations, such as local files, cloud storage, databases, etc. The data is updated at different frequencies, such as daily, weekly, monthly, etc. The data quality is inconsistent, such as missing values, errors, duplicates, etc.

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What is ETL (Extract, Transform, Load)?

The BAWorld

Data is extracted from an online transaction processing (OLTP) database and other sources, transformed to match the data warehouse schema, and loaded into the target (data warehouse/data hub/data lake) database during the ETL process. Importance of ETL.

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Top Data Analytics Terms You Should Know

The BAWorld

Completeness is a data quality dimension and measures the existence of required data attributes in the source in data analytics terms, checks that the data includes what is expected and nothing is missing. Consistency is a data quality dimension and tells us how reliable the data is in data analytics terms.