AWS Big Data

JANUARY 15, 2025

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. Recently, EUROGATE has developed a digital twin for its container terminal Hamburg (CTH), generating millions of data points every second from Internet of Things (IoT)devices attached to its container handling equipment (CHE).

IoT 111

IoT Machine Learning Metadata Data-driven 111

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 96

Analytics Data Warehouse Data Lake Metadata 96

Sisense

MAY 11, 2021

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Sisense

MARCH 14, 2021

Looking at the diagram, we see that Business Intelligence (BI) is a collection of analytical methods applied to big data to surface actionable intelligence by identifying patterns in voluminous data. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

Cloudera

OCTOBER 3, 2018

The tremendous growth in both unstructured and structured data overwhelms traditional data warehouses. We are both convinced that a scale-out, shared-nothing architecture — the foundation of Hadoop — is essential for IoT, data warehousing and ML. We have each innovated separately in those areas.

Uncertainty 75

Uncertainty IoT Risk Reporting 75

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data lakehouse was created to solve these problems.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Cloudera

OCTOBER 17, 2023

As organizations shift from the modernization of data-driven applications via Kafka towards delivering real-time insight and/or powering smart automated systems, Flink At Current, adoption of Flink was a hot topic and many of the vendors (Cloudera included) use Flink as the engine to power their stream processing offerings as well.

Data-driven 79

Data-driven Enterprise IoT Data Warehouse 79