AWS Big Data

DECEMBER 16, 2024

With the ability to browse metadata, you can understand the structure and schema of the data source, identify relevant tables and fields, and discover useful data assets you may not be aware of. This new capability can simplify your data journey. To learn more, refer to Amazon SageMaker Unified Studio.

Visualization 71

Visualization Data Processing Testing Publishing 71

IBM Big Data Hub

FEBRUARY 9, 2023

Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Data governance is a crucial aspect of managing an organization’s data assets.

Data Governance 76

Data Governance Business Objectives Data Quality Measurement 76

AWS Big Data

MAY 3, 2023

Components of the consumer application The consumer application comprises three main parts that work together to consume, transform, and load messages from Amazon MSK into a target database. The following diagram shows an example of data transformations in the handler component. Younggu Yun works at AWS Data Lab in Korea.

IoT 111

IoT Internet of Things Data Transformation Management 111

AWS Big Data

JULY 31, 2023

AWS DMS enables us to capture deltas, including deletes from the source database, through the use of Change Data Capture (CDC) configuration. CDC in DMS enables us to capture deltas without writing code and without missing any changes, which is critical for the integrity of the data. Under Transforms , choose SQL Query.

Sales 52

Sales Data Warehouse Visualization Testing 52

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. Additionally, organizations must carefully consider factors such as cost implications, security and compliance requirements, change management processes, and the potential disruption to existing business operations during the migration.

Data Warehouse 99

Data Warehouse KPI Optimization Cost-Benefit 99

Ontotext

AUGUST 24, 2023

The update is to drop and re-import the same graph data into a single atomic transaction. In use cases when the named graph has other meanings or the granularity of the updates is smaller like on the business object level, the user can design an explicit DELETE/INSERT template. Persistent or non-persistent IDs?

Data Integration 52

Data Integration Modeling Business Objectives Optimization 52

Sisense

MAY 11, 2021

Both of these concepts resonated with our team and our objectives, and so we found ourselves supporting both to some extent. 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.

Modeling 84

Modeling Big Data IoT Data Warehouse 84