AWS Big Data

NOVEMBER 22, 2024

The need for streamlined data transformations As organizations increasingly adopt cloud-based data lakes and warehouses, the demand for efficient data transformation tools has grown. This approach helps in managing storage costs while maintaining the flexibility to analyze historical trends when needed.

Data Lake 83

Data Lake Data Warehouse Cost-Benefit Data Transformation 83

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 100

IoT Machine Learning Metadata Data-driven 100

AWS Big Data

SEPTEMBER 5, 2024

If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported. In scenarios where data transformation is required, you can use Redshift stored procedures to modify data in Redshift tables.

IoT 106

IoT Data Warehouse Cost-Benefit Reporting 106

AWS Big Data

APRIL 11, 2023

Such a solution should use the latest technologies, including Internet of Things (IoT) sensors, cloud computing, and machine learning (ML), to provide accurate, timely, and actionable data. In the inventory management and forecasting solution, AWS Glue is recommended for data transformation.

Forecasting 83

Forecasting Management IoT Data-driven 83

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. The success criteria are the key performance indicators (KPIs) for each component of the data workflow. Data transformation experts to convert database stored functions in the producer or consumer.

Data Warehouse 99

Data Warehouse KPI Optimization Cost-Benefit 99

Sisense

MAY 11, 2021

Reporting Reporting contains the flattest and most cleaned version of our data. It often will collapse the metrics in a fact table to the level of a single dimension through a form of aggregation or lookback window. Importantly, both workflows for data analytics are supported by a set of data models that follow the same data pipeline.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

DataRobot Blog

MARCH 10, 2022

This “revolution” stems from breakthrough advancements in artificial intelligence, robotics, and the Internet of Things (IoT). The first step in building a model that can predict machine failure and even recommend the next best course of action is to aggregate, clean, and prepare data to train against.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52