AWS Partner Network (APN) Blog

Tag: AWS Lake Formation

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Securely Querying Your Data Lake with Ahana Presto and AWS Lake Formation

Ahana provides a fully managed and easy-to-use service for running Presto on AWS, and customers like Metropolis use Ahana to query data in their Amazon S3-based data lake for business intelligence, ad-hoc analytics, and reporting. Learn how Metropolis uses AWS Lake Formation and Ahana to build a data lake that allows their analysts and data scientists to develop a simple, hands-free parking experience for their customers.

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Implementing Data Mesh Using LTI’s Canvas Scarlet Framework on AWS

As data grows at an exponential rate both in volume and velocity, it becomes important for organizations to carve out a strategy to store data in appropriate locations with the correct safeguards to address data access and privacy concerns. Learn how organizations can transform their data landscape into a more controlled, flexible, and secure landscape using LTI’s Canvas Scarlet Data Mesh framework built on AWS to meet the data challenges an organization faces today.

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How Genpact is Innovating the Data-Driven Finance Office

Forward-looking finance teams will build resilience and responsiveness to future disruption. To deliver this strategic mandate, finance offices must be data-driven and share insights that help the organization connect, predict, and adapt within a changing business environment. Learn how Genpact’s data lake analytics reference architecture helps finance teams incorporate functional expertise into AWS solutions with the goal of delivering business impact beyond increased productivity.

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Automate Data Sharing with Informatica Axon Data Marketplace and AWS Lake Formation

A key goal of modern data strategy, whether a data mesh, data fabric, data lake, or data warehouse, is to deliver access to data when and where it’s needed. Learn how AWS and Informatica can combine and automate data governance for access within a data marketplace. This solution combines Information’s data governance architecture and the Informatica Intelligent Data Management Cloud (IDMC) which orchestrates and automates data access management with AWS Lake Formation.

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From Data Chaos to Data Intelligence: How an Internal Data Marketplace Transforms Your Data Landscape

The concept of an Internal Data Marketplace (IDM) is increasingly resonating with data organizations. An IDM is a secure, centralized, simplified, and standardized data shopping experience for data consumers. Explore how the IDM framework includes data governance and data catalogs, role-based access controls, data profiling, and powerful contextual search to easily identify the most relevant data. The end result is a seamless data consumption experience for end users.

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How WANdisco LiveData Migrator Can Migrate Apache Hive Metastore to AWS Glue Data Catalog

Big datasets have traditionally been locked on-premises because of data gravity, making it difficult to leverage cloud-native, serverless, and cutting-edge technologies provided by AWS and its community of partners. Modernizing an on-premises analytics platform takes time, effort, and careful planning. Explore the challenges of migrating large, complex, actively-used structured datasets to AWS and how the combination of WANdisco LiveData Migrator, Amazon S3, and AWS Glue Data Catalog overcome those challenges.

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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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Using Dremio for Fast and Easy Analysis of Amazon S3 Data

Although many SQL engines allow tools to query Amazon S3 data, organizations face multiple challenges, including high latency and infrastructure costs. Learn how Dremio empowers analysts and data scientists to analyze data in S3 directly at interactive speed, without having to physically copy data into other systems or create extracts, cubes, and/or aggregation tables. Dremio’s unique architecture enables faster and more reliable query performance than traditional SQL engines.

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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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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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