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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 138
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The Architecture of Serverless Data Systems

Hacker News

I recently blogged about why I believe the future of cloud data services is large-scale and multi-tenant, citing, among others, S3. “Top Serving customers over large resource pools provides unparalleled efficiency and reliability at scale.”

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Exploring the Power of Microsoft Fabric: A Hands-On Guide with a Sales Use Case

Data Science Dojo

These experiences facilitate professionals from ingesting data from different sources into a unified environment and pipelining the ingestion, transformation, and processing of data to developing predictive models and analyzing the data by visualization in interactive BI reports.

Power BI 222
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Process Mining – Ist Celonis wirklich so gut? Ein Praxisbericht.

Data Science Blog

Dabei darf gerne in Erinnerung gerufen werden, dass Process Mining im Kern eine Graphenanalyse ist, die ein Event Log in Graphen umwandelt, Aktivitäten (Events) stellen dabei die Knoten und die Prozesszeiten die Kanten dar, zumindest ist das grundsätzlich so. Es handelt sich dabei also um eine Analysemethodik und nicht um ein Tool.

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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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The Best Data Management Tools For Small Businesses

Smart Data Collective

Usually the term refers to the practices, techniques and tools that allow access and delivery through different fields and data structures in an organisation. Data management approaches are varied and may be categorised in the following: Cloud data management. Master data management. Data transformation.

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phData Honored as Pioneer in Composable CDP Solutions

phData

A Composable CDP is a new technical architecture for how businesses manage and activate their customer data for marketing programs. The Composable CDP transforms an existing cloud data warehouse, like the Snowflake Data Cloud , into the central repository of customer data in a company.