Remove Cost-Benefit Remove Data Lake Remove Data Processing Remove Enterprise
article thumbnail

Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 105
article thumbnail

Introducing the technology behind watsonx.ai, IBM’s AI and data platform for enterprise

IBM Big Data Hub

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. ” These large models have lowered the cost and labor involved in automation. Data: the foundation of your foundation model Data quality matters.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Power enterprise-grade Data Vaults with Amazon Redshift – Part 2

AWS Big Data

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

article thumbnail

DS Smith sets a single-cloud agenda for sustainability

CIO Business Intelligence

Its digital transformation began with an application modernization phase, in which Dickson and her IT teams determined which applications should be hosted in the public cloud and which should remain on a private cloud. This enables the company to extract additional value from the data through real-time availability and contextualization.

article thumbnail

Your New Cloud for AI May Be Inside a Colo

CIO Business Intelligence

Enterprises moving their artificial intelligence projects into full scale development are discovering escalating costs based on initial infrastructure choices. Many companies whose AI model training infrastructure is not proximal to their data lake incur steeper costs as the data sets grow larger and AI models become more complex.

article thumbnail

CIOs weigh where to place AI bets — and how to de-risk them

CIO Business Intelligence

When it comes to AI, Nafde sees risks in the vendors selected, the business-worthiness of the use case, and the cost of the initiative. To find promising use cases, Webster Bank canvassed several dozen proposals and decided to start with three that could deliver tangible benefits. It’s a significant danger with significant costs.

Risk 133
article thumbnail

Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

Offering this service reduced BMS’s operational maintenance and cost, and offered flexibility to business users to perform ETL jobs with ease. For the past 5 years, BMS has used a custom framework called Enterprise Data Lake Services (EDLS) to create ETL jobs for business users.