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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

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Data Pipeline Observability: A Model For Data Engineers

Databand.ai

Data observability works with your data pipeline by providing insights into how your data flows and is processed from start to end. Here is a more detailed explanation of how data observability works within the data pipeline: Data ingestion : Observability begins from the point where data is ingested into the pipeline.

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Accenture’s Smart Data Transition Toolkit Now Available for Cloudera Data Platform

Cloudera

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

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AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

Application programming interfaces (APIs) are used to modify the retrieved data set for integration and to support users in keeping track of all the jobs. Users can schedule ETL jobs, and they can also choose the events that will trigger them. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog.

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New Snowflake Features Released in April 2023

Snowflake

Cross-Cloud Snowgrid Account Replication expands replication beyond databases – general availability Account Replication, now generally available, expands replication beyond databases to account metadata and integrations, making business continuity truly turnkey. Visit our documentation page to learn more. Learn more.

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The Good and the Bad of the Elasticsearch Search and Analytics Engine

AltexSoft

Analysis of logs, metrics, and security events. With Elasticsearch, you can aggregate and analyze large streams of logs, metrics, and security events in near real-time, making it indispensable for system monitoring and security information and event management (SIEM). Real-time behavior modeling with ML.

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Data Pipeline Architecture Explained: 6 Diagrams and Best Practices

Monte Carlo

Why is data pipeline architecture important? This is frequently referred to as a 5 or 7 layer (depending on who you ask) data stack like in the image below. Here are some of the most common solutions that are involved in modern data pipelines and the role they play.