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Tag: Data Management
CData Blog
February 28, 2024
3DES vs AES: Which Algorithm Should You Use?
What is 3DES encryption, and is it right for you? Should you consider AES encryption instead? Understand 3DES secrets and limitations and compare it to modern ciphers. Make informed security choices for your data.
February 27, 2024
SSIS ETL: A Quick Guide on What It Is & How to Set It Up
Master SSIS ETL in 7 steps. Conquer data challenges & unlock workflow efficiency. This beginner-friendly guide simplifies data integration step-by-step.
February 27, 2024
Virtual event: Data Virtualization, Reimagined
Join us on March 14, 2024, at 11:00 am ET for a can’t-miss virtual event, 'Data Virtualization, Reimagined', to hear from data experts on how data virtualization is evolving to meet your modern integration needs.
February 23, 2024
What is Microsoft SQL Server's Change Data Capture and How Do You Implement It?
Ditch inefficient full scans: Learn how SQL Server CDC captures real-time data changes, empowering data pipelines, DB sync & mission-critical applications.
February 22, 2024
Hadoop vs Spark: Which is Best?
Hadoop vs Spark: Discover the differences, performance, and use cases in this article. Find out which framework works best for your business.
February 20, 2024
EDI 940: All You Need to Know About the Warehouse Shipping Order Transaction
Master the essentials of EDI 940. Optimize order-related data for enhanced operations & elevate your supply chain's efficiency with informed decision-making.
February 20, 2024
10 Google Analytics Integrations Every Business Should Know About
Discover how Google Analytics integrations and other ones can streamline your data management processes and learn the benefits of implementing them.
February 15, 2024
What is a Data Lake? Definition, Challenges, and 3 Solutions
Discover the benefits of data lakes: get insights into how they work, types, and best practices for data management. Optimize your data with CData.
February 14, 2024
dbt (Data Build Tool): What Is It & How to Build Data Pipelines
Data transformation made easy: Follow these 5 steps to build a powerful and reliable dbt data pipeline, empowering analysts and boosting data quality.
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