AWS Partner Network (APN) Blog

Tag: Data Lake

Tealium-AWS-Partners

Where Does a Customer Data Platform Fit in With My AWS Data Lake?

When it comes to evaluating tools and technologies that focus on customer data, it can be difficult to understand how one tool differentiates from the next. Tealium was one of the first entrants in the Customer Data Platform (CDP) category and helped shape the industry. As such, Tealium is uniquely positioned to help organizations make the most of their data and offer more ways to deliver high-quality customer data to AWS in real-time.

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Talend-AWS-Partners

Embrace Data Sovereignty and Low Latency in Building a Trusted Data Lake with AWS Outposts and Talend

Globalization and digitalization require companies to comply with data protection rules in the limitless world of the internet. Meeting this challenge requires maximum data agility and availability along with minimal data latency. Integration with AWS Outposts makes Talend Data Fabric allows you to quickly integrate, clean, and move data from different sources with low-latency, and meet data sovereignty regulatory requirements for hybrid deployments.

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Cazena-AWS-Partners

Cazena’s Instant AWS Data Lake: Accelerating Time to Analytics from Months to Minutes

Given the breadth of use cases, data lakes need to be a complete analytical environment with a variety of analytical tools, engines, and languages supporting a variety of workloads. These include traditional analytics, business intelligence, streaming event and Internet of Things (IoT) processing, advanced machine learning, and artificial intelligence processing. Learn how Cazena builds and deploys a production ready data lake in minutes for customers.

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Bursting Your On-Premises Data Lake Analytics and AI Workloads on AWS

Developing and maintaining an on-premises data lake is a complex undertaking. To maximize the value of data and use it as the basis for critical decisions, the data platform must be flexible and cost-effective. Learn how to build a hybrid data lake with Alluxio to leverage analytics and AI on AWS alongside a multi-petabyte on-premises data lake. Alluxio’s solution is called “zero-copy” hybrid cloud, indicating a cloud migration approach without first copying data to Amazon S3.

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Cloud Anything-13

How AWS and ISVs Are Empowering Customers on Their Cloud Journey

AWS is building a partner community that is the most customer-centric in the world and creates long-term success for AWS and our committed partners. One of the ways we do this is by focusing our investments on independent software vendors (ISVs) that extend the reach of the AWS Cloud and provide our customers with more choice. These trusted AWS Partners provide feature-rich experiences on AWS to support customers’ enterprise IT needs.

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nClouds-AWS-Partners

Rapid Data Lake Development with Data Lake as Code Using AWS CloudFormation

Data lakes have evolved into the single store-platform for all enterprise data managed. On AWS, an integrated set of services are available to engineer and automate data lakes. A data lake on AWS is able to group all of the previously mentioned services of relational and non-relational data and allow you to query results faster and at a lower cost. Learn how nClouds used code automation via AWS CloudFormation to create a dynamic data lake stack to visualize and analyze the financial market data.

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Okta-AWS-Partners

Implementing SAML AuthN for Amazon EMR Using Okta and Column-Level AuthZ with AWS Lake Formation

As organizations continue to build data lakes on AWS and adopt Amazon EMR, especially when consuming data at enterprise scale, it’s critical to govern your data lakes by establishing federated access and having fine-grained controls to access your data. Learn how to implement SAML-based authentication (AuthN) using Okta for Amazon EMR, querying data using Zeppelin notebooks, and applying column-level authorization (AuthZ) using AWS Lake Formation.

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Onica-AWS-Partners

Best Practices from Onica for Optimizing Query Performance on Amazon Redshift

Effective and economical use of data is critical to your success. As data volumes increase exponentially, managing and extracting value from data becomes increasingly difficult. By adopting best practices that Onica has developed over years of using Amazon Redshift, you can improve the performance of your AWS data warehouse implementation. Onica has completed multiple projects ranging from assessing the current state of an Amazon Redshift cluster to helping tune, optimize, and deploy new clusters.

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Machine Learning-4

How to Use Amazon SageMaker to Improve Machine Learning Models for Data Analysis

Amazon SageMaker provides all the components needed for machine learning in a single toolset. This allows ML models to get to production faster with much less effort and at lower cost. Learn about the data modeling process used by BizCloud Experts and the results they achieved for Neiman Marcus. Amazon SageMaker was employed to help develop and train ML algorithms for recommendation, personalization, and forecasting models that Neiman Marcus uses for data analysis and customer insights.

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Cazena-AWS-Partners

Accelerating Apache and Hadoop Migrations with Cazena’s Data Lake as a Service on AWS

Running Hadoop, Spark, and related technologies in the cloud provides the flexibility required by these distributed systems. Cazena provides a production-ready, continuously optimized and secured Data Lake as a Service with multiple features that enables migration of Hadoop and Spark analytics workloads to AWS without the need for specialized skills. Learn how Cazena makes it easy to migrate to AWS while ensuring your data is as secure on the cloud as it is on-premises.

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