Data Management Data Warehouse E-Commerce Innovation 
Astera
JANUARY 25, 2024
Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.
Astera
APRIL 28, 2023
Data management can be a daunting task, requiring significant time and resources to collect, process, and analyze large volumes of information.
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Astera
JANUARY 24, 2024
What is Change Data Capture? Change Data Capture (CDC) is a technique used in data management to identify and track changes made to data in a database, and applying those changes to the target system. Below is the step-by-step explanation on how change data capture typically works.
Astera
JUNE 13, 2023
Data Migration Data pipelines facilitate smooth and efficient data migration from legacy systems to modern infrastructure. By ensuring a seamless transition without disruption, organizations can leverage advanced technologies and drive innovation. Use Astera's no-code data pipeline to solve your data management problems!
BizAcuity
APRIL 14, 2022
They tell you how big data helped them create a mark in today’s world. Tesla is another company that picks up data from their cars and also analyzes traffic and weather. One leverages data to improve their supply chain resilience while the other to improve their product innovation. Big Data Ecosystem.
Astera
NOVEMBER 13, 2023
But have you ever wondered how data informs the decision-making process? The key to leveraging data lies in how well it is organized and how reliable it is, something that an Enterprise Data Warehouse (EDW) can help with. What is an Enterprise Data Warehouse (EDW)?
Insight Software
JANUARY 20, 2021
In order to achieve that, though, business managers must bring order to the chaotic landscape of multiple data sources and data models. That process, broadly speaking, is called data management. Worse yet, poor data management can lead managers to make decisions based on faulty assumptions.
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