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9 Best Practices for Real-Time Data Management

Dataversity

Businesses increasingly rely on real-time data to make informed decisions, improve customer experiences, and gain a competitive edge. However, managing and handling real-time data can be challenging due to its volume, velocity, and variety.

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Real-Time Data in Machine Learning: Challenges and Solutions

Dataversity

There are instances in which real-time decision-making isn’t particularly critical (such as demand forecasting, customer segmentation, and multi-touch attribution). In those cases, relying on batch data might be preferable. However, when you need real-time automated […].

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As Data Privacy Concerns Ramp Up, the Need for Governed Real-Time Data Has Never Been Greater

Dataversity

Data privacy is essential for any business, but it is especially important at a time when consumers are taking notice and new regulations are being deployed. […]. The post As Data Privacy Concerns Ramp Up, the Need for Governed Real-Time Data Has Never Been Greater appeared first on DATAVERSITY.

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ETL vs. ELT: A Comprehensive Comparison and Guide to Modern Data Integration Strategies

Analysts Corner

Data integration has become a crucial aspect of managing this information, and two popular approaches have emerged to address these needs: Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT). In ELT, raw data is loaded directly into the target system, and the transformation process occurs after the data has been loaded.

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Best Azure ETL Tools For 2024

Astera

Azure SQL Data Warehouse, now called Azure Synapse Analytics, is a powerful analytics and BI platform that enables organizations to process and analyze large volumes of data in a centralized place. Scalability: As businesses grow and generate more data, Azure ETL tools can easily handle the increased volume and complexity of data.

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What is a Data Pipeline?

Astera

Data pipelines are a fundamental element in today’s technology landscape, providing seamless data movement and valuable insights for businesses. In this article, we will explore the concept of data pipelines, their key components, and the various use cases and benefits they offer.

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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.