Category: Analytics

Unlocking data intelligence and implementing modern data architectures can turn organizations into data-driven enterprises and help drive business outcomes. Learn how AWS and Accenture are helping customers transform to data-driven organizations through Accenture’s Data Lake Accelerator built on AWS. It’s a one-stop solution for automated data platform creation, managed data transformation, and data and analytics performed in a cloud-native way.

Many organizations leverage unstructured data collected from social media feeds, stock streaming, and data clickstream to gain insights about the needs of their customers. The EZ Lake Access (EZLA) solution developed by TCS centralizes and simplifies access management of the Data Lake House by codifying most of the enterprise access controls in the form of a rule engine. This provides increased efficiencies and easy adoption of the Data Lake House.

Privacera is an AWS Partner that provides security and privacy tools for enterprises to secure and govern user access to databases and datastores in the cloud. PrivaceraCloud reduces the burden of self-managing Apache Ranger by providing Ranger as a hosted service. It provides centralized management of data access, authorization policies, and auditing. Learn how Amazon EMR can integrate with PrivaceraCloud to provide a fully-managed data governance solution.

Many customers operate in a hybrid environment with on-premises infrastructure interconnected with a cloud provider’s infrastructure. This post details how HCLTech used the AWS Centralized Log Management Reference Architecture, and discusses how HCLTech removed the requirements for Amazon Kinesis Data Streams. We also explore how HCLTech used Amazon Kinesis Data Firehose to stream from an Amazon CloudWatch Logs destination in a centralized logging account.

There has been a lot of buzz about a new data architecture design pattern called a Lake House. A Lake House approach integrates a data lake with the data warehouse and all of the purpose-built stores so customers no longer have to take a one-size-fits-all approach and are able to select the storage that best suits their needs. Learn how to couple Amazon Redshift with a semantic layer from AtScale to deliver fast, agile, and analysis-ready data to business analysts and data scientists.

Data in any format is valuable as long as you know how to use it effectively, but such data monetization is only possible if you also trust your data. In today’s fast-paced world, where data is rapidly produced, stored, and consumed, many organizations struggle to organize, find, and utilize their data skillfully and successfully. Collibra’s data lineage, access control, and data cataloging capabilities powered by AWS are a valuable asset in terms of analyst productivity for data discovery and research.

Global business leaders recognize the value of advanced and augmented big data analytics over various internal and external data sources. However, technical leaders also face challenges capturing insights from data silos without unified master data. Learn how migrating Tamr’s data mastering solutions from on-premises to AWS allowed a customer to process billions of records five times faster with fully managed Amazon EMR clusters.

VMware Cloud on AWS brings VMware’s SDDC technologies to the AWS global infrastructure. When customers combine Amazon OpenSearch Service with Amazon Kinesis Data Firehose and AWS Lambda, you can create a managed, end-to-end log aggregation and workload monitoring solution for workloads, including those running in VMware Cloud on AWS. In this post, Learn the benefits of this monitoring solution and explore ideas on how to get started utilizing it.

Data warehouse modernization has been a key aspect of many customers’ broader cloud transformation stories. Legacy data warehouse systems, however, present many challenges when dealing with today’s enterprise data needs. Learn how AWS and Infosys collaborated to transform a legacy Netezza platform on AWS for a large retail customer. With Infosys tools, processes, and industry knowledge, the collaboration between AWS and Infosys enables customers to transform their analytics platforms.

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.