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What companies get wrong about data transformation

CIO Business Intelligence

I think that speaks volumes to the type of commitment that organizations have to make around data in order to actually move the needle.”. So if funding and C-suite attention aren’t enough, what then is the key to ensuring an organization’s data transformation is successful? Analytics, Chief Data Officer, Data Management

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Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity

AWS Big Data

With the ability to browse metadata, you can understand the structure and schema of the data source, identify relevant tables and fields, and discover useful data assets you may not be aware of. Next, you will query the data in this table using SageMaker Unified Studios SQL query book feature. Choose Save changes.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

Adapted from the book Effective Data Science Infrastructure. Data is at the core of any ML project, so data infrastructure is a foundational concern. ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses. Model Development.

IT 364
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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

AWS Big Data

Together with price-performance, Amazon Redshift offers capabilities such as serverless architecture, machine learning integration within your data warehouse and secure data sharing across the organization. dbt Cloud is a hosted service that helps data teams productionize dbt deployments.

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4 Key Steps to Data Transformation Success with Data Mesh

Find out how Data Mesh can help you overcome these challenges and more. Download the e-Book!

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What is a DataOps Engineer?

DataKitchen

The data organization wants to run the Value Pipeline as robustly as a six sigma factory, and it must be able to implement and deploy process improvements as rapidly as a Silicon Valley start-up. The data engineer builds data transformations. Their product is the data. Read out Free E-book: The DataOps Cookbook.

Testing 152
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What is DataOps? Collaborative, cross-functional analytics

CIO Business Intelligence

“For example, this style makes it more feasible for data scientists to have the support of software engineering to provide what is needed when models are handed over to operations during deployment,” Ted Dunning and Ellen Friedman write in their book, Machine Learning Logistics.

Analytics 130