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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

Flipboard

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis. or a later version) database.

ETL 135
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5 strategies for data security and governance in data warehousing: ensuring data protection and compliance

Data Science Dojo

M aintaining the security and governance of data within a data warehouse is of utmost importance. Data Security: A Multi-layered Approach In data warehousing, data security is not a single barrier but a well-constructed series of layers, each contributing to protecting valuable information.

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Data sips and bites: An evening of data insights

Dataconomy

Hosted at one of Mindspace’s coworking locations, the event was a convergence of insightful talks and professional networking. Mindspace , a global coworking and flexible office provider with over 45 locations worldwide, including 13 in Germany, offered a conducive environment for this knowledge-sharing event.

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Data Version Control for Data Lakes: Handling the Changes in Large Scale

ODSC - Open Data Science

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. Schema Enforcement: Data warehouses use a “schema-on-write” approach.

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The Best Data Management Tools For Small Businesses

Smart Data Collective

Extraction, Transform, Load (ETL). The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Diagnostic analytics: Diagnostic analytics goes a step further by analyzing historical data to determine why certain events occurred. By understanding the “why” behind past events, organizations can make informed decisions to prevent or replicate them. Ensure that data is clean, consistent, and up-to-date.

Analytics 203
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Top 10 Big Data CRM Tools To Increase Business Sales

Smart Data Collective

Top Big Data CRM Integration Tools in 2021: #1 MuleSoft: Mulesoft is a data integration platform owned by Salesforce to accelerate digital customer transformations. This tool is designed to connect various data sources, enterprise applications and perform analytics and ETL processes.

Big Data 142