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Data Modeling 101: OLTP data modeling, design, and normalization for the cloud

erwin

How to create a solid foundation for data modeling of OLTP systems. As you undertake a cloud database migration , a best practice is to perform data modeling as the foundation for well-designed OLTP databases. This makes mastering basic data modeling techniques and avoiding common pitfalls imperative.

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A hybrid approach in healthcare data warehousing with Amazon Redshift

AWS Big Data

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. This is one of the biggest hurdles with the data vault approach. What is a dimensional data model?

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Benefits of Data Vault Automation

erwin

The benefits of Data Vault automation from the more abstract – like improving data integrity – to the tangible – such as clearly identifiable savings in cost and time. So Seriously … You Should Automate Your Data Vault. By Danny Sandwell.

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

Cloudera

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

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What is a Data Pipeline?

Jet Global

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

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The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure

DataKitchen

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. SQL Server Integration Services (SSIS): You know it; your father used it.

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Improve healthcare services through patient 360: A zero-ETL approach to enable near real-time data analytics

AWS Big Data

AWS has invested in a zero-ETL (extract, transform, and load) future so that builders can focus more on creating value from data, instead of having to spend time preparing data for analysis. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.