Astera

JANUARY 24, 2024

Approach: Depending on their use case and requirements, organizations set up different change data capture approaches. Common methods include the log-based approach which involves monitoring the database transaction log to identify changes, and trigger-based CDC where certain triggers are used to capture changes.

E-Commerce 52

E-Commerce Data Warehouse Real-time Data Monitoring 52

Data Pine

MAY 2, 2023

To work effectively, big data requires a large amount of high-quality information sources. Where is all of that data going to come from? Transparency: With the ability to monitor the movements of goods and delivery operatives in real-time, you can improve internal as well as external efficiency.

Supply Chain 110

Supply Chain Logistics Big Data Customer Experience 110

Astera

NOVEMBER 28, 2023

They ensure compliance with regulations like the European Union’s General Data Protection Regulation (GDPR), safeguarding data and building trust with policyholders. How To Build a Robust Data Pipeline Building a data pipeline is a multi-step process that requires careful planning and execution.

Data Warehouse 52

Data Warehouse Monitoring Data Security Healthcare 52

Tableau

APRIL 6, 2022

Dynamic data and visualizations will aid providers in taking a holistic approach to wellbeing in care models, including integration of SDOH data. Analytics are being leveraged to segment the patient population to understand which members are at risk of falling behind on care plans and proactively act.

Healthcare 97

Healthcare Supply Chain Real-time Data Government 97

Tableau

APRIL 6, 2022

Dynamic data and visualizations will aid providers in taking a holistic approach to wellbeing in care models, including integration of SDOH data. Analytics are being leveraged to segment the patient population to understand which members are at risk of falling behind on care plans and proactively act.

Healthcare 93

Healthcare Supply Chain Real-time Data Government 93

Astera

FEBRUARY 9, 2024

To optimize the data destination, you can choose the most suitable and efficient options, such as: Destination type and format : These are the type and format of the data destination, such as the database, the file, web services such as APIs, the cloud platform, or the application.

IBM Support 52

IBM Support Data Quality IBM Maintenance Data Governance 52

Astera

OCTOBER 27, 2023

Data Ingestion Layer: The data journey in a cloud data warehouse begins with the data ingestion layer, which is responsible for seamlessly collecting and importing data. This layer often employs ETL processes to ensure that the data is transformed and formatted for optimal storage and analysis.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52