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Setting up Data Lake on GCP using Cloud Storage and BigQuery

Analytics Vidhya

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

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Data Warehouse vs. Data Lake

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As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

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10 Things AWS Can Do for Your SaaS Company

Smart Data Collective

AWS (Amazon Web Services), the comprehensive and evolving cloud computing platform provided by Amazon, is comprised of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS). In this article we will list 10 things AWS can do for your SaaS company. What is AWS?

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning Blog

We also discuss common security concerns that can undermine trust in AI, as identified by the Open Worldwide Application Security Project (OWASP) Top 10 for LLM Applications , and show ways you can use AWS to increase your security posture and confidence while innovating with generative AI.

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Hybrid Vs. Multi-Cloud: 5 Key Comparisons in Kafka Architectures

Smart Data Collective

A hybrid cloud system is a cloud deployment model combining different cloud types, using both an on-premise hardware solution and a public cloud. Amazon’s AWS Glue is one such tool that allows you to consume data from Apache Kafka and Amazon-managed streaming for Apache Kafka (MSK).

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Mainframe Technology Trends for 2024

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Yet mainframes weren’t initially designed to integrate easily with modern distributed computing platforms. Cloud computing, object-oriented programming, open source software, and microservices came about long after mainframes had established themselves as a mature and highly dependable platform for business applications.

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Mainframe Technology Trends for 2023

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Yet mainframes weren’t designed to integrate easily with modern distributed computing platforms. Cloud computing, object-oriented programming, open source software, and microservices came about long after mainframes had established themselves as a mature and highly dependable platform for business applications.

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