CIO Business Intelligence

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity.

Data Architecture 111

Data Architecture Data Integration IoT Data-driven 111

BizAcuity

NOVEMBER 22, 2022

In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

AWS Big Data

JANUARY 8, 2024

In the subsequent post in our series, we will explore the architectural patterns in building streaming pipelines for real-time BI dashboards, contact center agent, ledger data, personalized real-time recommendation, log analytics, IoT data, Change Data Capture, and real-time marketing data.

Analytics 134

Analytics IoT Data-driven Snapshot 134

Cloudera

NOVEMBER 1, 2022

Through modern data architectures powered by CDP, including Cloudera-enabled data fabric, data lakehouse, and data mesh , DoD agencies can rapidly provision and manage innovative data engineering, data warehouse, and machine learning environments, with access to secured supply chain data stored in CDP Private Cloud.

Cost-Benefit 89

Cost-Benefit Data Architecture Risk IoT 89

Cloudera

JANUARY 26, 2022

Modern, real-time businesses require accelerated cycles of innovation that are expensive and difficult to maintain with legacy data platforms. The hybrid cloud’s premise—two data architectures fused together—gives companies options to leverage those solutions and to address decision-making criteria, on a case-by-case basis. .

Data Processing 87

Data Processing IoT Data Warehouse Cost-Benefit 87

Cloudera

APRIL 13, 2021

But while the company is united by purpose, there was a time when its teams were kept apart by a data platform that lacked the scalability and flexibility needed for collaboration and efficiency. Disparate data silos made real-time streaming analytics, data science, and predictive modeling nearly impossible.

Enterprise 78

Enterprise Cost-Benefit Data Warehouse Data Architecture 78

Cloudera

DECEMBER 19, 2018

The most common big data use case is data warehouse optimization. Big data architecture is used to augment different applications, operating alongside or in a discrete fashion with a data warehouse. A big data implementation may even replace a data warehouse entirely with a data lake.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

Cloudera

AUGUST 9, 2022

Data platforms are no longer skunkworks projects or science experiments. As customers import their mainframe and legacy data warehouse workloads, there is an expectation on the platform that it can meet, if not exceed, the resilience of the prior system and its associated dependencies.

Data Lake 78

Data Lake Data Warehouse Data-driven IoT 78

Cloudera

MAY 22, 2019

Although the program is technically in its seventh year, as the first joint awards program, this year’s Data Impact Awards will span even more use cases, covering even more advances in IoT, data warehouse, machine learning, and more. DATA ANYWHERE. DATA SECURITY AND GOVERNANCE.

Machine Learning 56

Machine Learning Data Architecture IoT Data Warehouse 56

BizAcuity

APRIL 1, 2023

Introduction In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. For this reason, Snowflake is often the cloud-native data warehouse of choice.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Lake Internet of Things 52

IBM Big Data Hub

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Alation

APRIL 14, 2022

Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. Integrating data from your own ERP and CRM systems may be a chore, but for today’s data-aware applications, the fabric of data is multi-colored. Automatic sampling to test transformation. Scheduling.

Metadata 59

Metadata Data Governance Data-driven Modeling 59

O'Reilly on Data

SEPTEMBER 11, 2019

Our call for speakers for Strata NY 2019 solicited contributions on the themes of data science and ML; data engineering and architecture; streaming and the Internet of Things (IoT); business analytics and data visualization; and automation, security, and data privacy. Streaming, IoT, and time series mature.

IoT 25

IoT Big Data Data Warehouse Uncertainty 25

CIO Business Intelligence

APRIL 23, 2025

Step 1: Data ingestion Identify your data sources. First, list out all the insurance data sources. These include older systems (like underwriting, claims processing and billing) as well as newer streams (like telematics, IoT devices and external APIs). Collect your data in one place.

Insurance 109

Insurance Digital Transformation Data Quality Data Lake 109