Tag: AWS Lake Formation

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.

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.

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.

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.

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.

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.

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.

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.

Adapting to the digitally disrupted world is high on the agenda for organizations everywhere. DevOps is a response to this challenge. It lowers internal transaction costs, flattens hierarchies, and makes the IT function more responsive. DevOpsGroup, an AWS DevOps Competency Partner, is addressing this need with the Adaptive IT Framework. It draws on learnings gained helping organizations implement DevOps methodologies, as well as established best practice principles.

Successful data lake implementations can serve a corporation well for years. Accenture, an APN Premier Consulting Partner, recently had an engagement with a Fortune 500 company that wanted to optimize its AWS data lake implementation. As part of the engagement, Accenture moved the customer to better-suited services and developed metrics to closely monitor the health of its overall environment in the cloud.