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

Join a streaming data source with CDC data for real-time serverless data analytics using AWS Glue, AWS DMS, and Amazon DynamoDB

AWS Big Data

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Recently, data lakes have gained lot of traction to become the foundation for analytical solutions, because they come with benefits such as scalability, fault tolerance, and support for structured, semi-structured, and unstructured datasets.

article thumbnail

How The Cloud Made ‘Data-Driven Culture’ Possible | Part 1

BizAcuity

Despite cost-cutting being the main reason why most companies shift to the cloud, that is not the only benefit they walk away with. Cloud washing is storing data on the cloud for use over the internet. While that allows easy access to users, and saves costs, the cloud is much more and beyond that. More on Kubernetes soon.

Insiders

Sign Up for our Newsletter

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

Trending Sources

article thumbnail

Modern Data Architecture for Telecommunications

Cloudera

Previously, there were three types of data structures in telco: . Entity data sets — i.e. marketing data lakes . What is the rationale for driving a modern data architecture? There are three major architectures under the modern data architecture umbrella. . and — more worryingly — “how can we be sure?”

article thumbnail

How Cloudera Data Flow Enables Successful Data Mesh Architectures

Cloudera

Within the context of a data mesh architecture, I will present industry settings / use cases where the particular architecture is relevant and highlight the business value that it delivers against business and technology areas. A Client Example.

Metadata 124
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.