Remove Data Processing Remove Management Remove Metadata
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What you need to know about product management for AI

O'Reilly on Data

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools.

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Accelerate your migration to Amazon OpenSearch Service with Reindexing-from-Snapshot

AWS Big Data

It is appealing to migrate from self-managed OpenSearch and Elasticsearch clusters in legacy versions to Amazon OpenSearch Service to enjoy the ease of use, native integration with AWS services, and rich features from the open-source environment ( OpenSearch is now part of Linux Foundation ).

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Manage Amazon OpenSearch Service Visualizations, Alerts, and More with GitHub and Jenkins

AWS Big Data

Amazon OpenSearch Service is a fully managed service for search and analytics. AWS handles the heavy lifting of managing the underlying infrastructure, including service installation, configuration, replication, and backups, so you can focus on the business side of your application. Make sure the Python version is later than 2.7.0:

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Demystify data sharing and collaboration patterns on AWS: Choosing the right tool for the job

AWS Big Data

Let’s briefly describe the capabilities of the AWS services we referred above: AWS Glue is a fully managed, serverless, and scalable extract, transform, and load (ETL) service that simplifies the process of discovering, preparing, and loading data for analytics.

Sales 115
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Modernize your legacy databases with AWS data lakes, Part 2: Build a data lake using AWS DMS data on Apache Iceberg

AWS Big Data

secret_id – The ID of the AWS Secrets Manager secret for the source database credentials. format(host, port, dbname) connectionProperties = { "user" : username, "password" : password } spark.read.jdbc(url=jdbc_url, table='INFORMATION_SCHEMA.TABLE_CONSTRAINTS', properties=connectionProperties).createOrReplaceTempView("TABLE_CONSTRAINTS")

Data Lake 105
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How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes

AWS Big Data

Recognizing this paradigm shift, ANZ Institutional Division has embarked on a transformative journey to redefine its approach to data management, utilization, and extracting significant business value from data insights. This principle makes sure data accountability remains close to the source, fostering higher data quality and relevance.

Metadata 105
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How BMW streamlined data access using AWS Lake Formation fine-grained access control

AWS Big Data

The CDH is used to create, discover, and consume data products through a central metadata catalog, while enforcing permission policies and tightly integrating data engineering, analytics, and machine learning services to streamline the user journey from data to insight. This led to inefficiencies in data governance and access control.

Data Lake 108