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How Cloud Data Platforms improve Shopfloor Management

Data Science Blog

The fusion of data in a central platform enables smooth analysis to optimize processes and increase business efficiency in the world of Industry 4.0 using methods from business intelligence , process mining and data science. Cloud Data Platform for shopfloor management and data sources such like MES, ERP, PLM and machine data.

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

Data Science Dojo

With this full-fledged solution, you don’t have to spend all your time and effort combining different services or duplicating data. OneLake, being built on Azure Data Lake Storage (ADLS), supports various data formats, including Delta, Parquet, CSV, and JSON.

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Discovering the Role of Data Science in a Cloud World

Pickl AI

Each platform offers unique capabilities tailored to varying needs, making the platform a critical decision for any Data Science project. Major Cloud Platforms for Data Science Amazon Web Services ( AWS ), Microsoft Azure, and Google Cloud Platform (GCP) dominate the cloud market with their comprehensive offerings.

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How to Build Effective Data Pipelines in Snowpark

phData

As today’s world keeps progressing towards data-driven decisions, organizations must have quality data created from efficient and effective data pipelines. For customers in Snowflake, Snowpark is a powerful tool for building these effective and scalable data pipelines.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

We also discuss different types of ETL pipelines for ML use cases and provide real-world examples of their use to help data engineers choose the right one. What is an ETL data pipeline in ML? Xoriant It is common to use ETL data pipeline and data pipeline interchangeably.

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On-Prem vs. The Cloud: Key Considerations 

phData

The Cloud represents an iteration beyond the on-prem data warehouse, where computing resources are delivered over the Internet and are managed by a third-party provider. Examples include: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Data integrations and pipelines can also impact latency.

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How to Optimize Power BI and Snowflake for Advanced Analytics

phData

One big issue that contributes to this resistance is that although Snowflake is a great cloud data warehousing platform, Microsoft has a data warehousing tool of its own called Synapse. In a perfect world, Microsoft would have clients push even more storage and compute to its Azure Synapse platform.