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10 Database Schema Best Practices
Follow these tips to ensure that your database schema delivers maximum utility for data warehouse users, data analysts, and data scientists.
11 Database Schema Mistakes to Avoid
A good database schema is indispensable for making data warehouses work. Get it wrong, and you’ll be in a world of hurt.
Data Lakes vs. Data Warehouses
Successful analytics depends on choosing the right approach to storing your enterprise data.
What Is the Modern Data Stack?
A radically new approach to data integration saves engineering time, allowing engineers and analysts to pursue higher-value activities.
ETL vs. ELT: Choose the Right Approach for Data Integration
Learn about ETL and ELT so you can decide which method works for you.
Product Managers! Join Us at #mdscon 2021
This year's Modern Data Stack Conference features speakers and sessions for data professionals of all kinds.
Team Leads! Join Us at #mdscon 2021
This year's Modern Data Stack Conference features speakers and sessions for data professionals of all kinds.
Applying the Scientific Method to Improve Business Intelligence
The scientific method is a proven route to successful, tested and verified improvement. Here’s how to combine it with BI.
What Is a Database Schema?
Use schemas to make life easier for your analysts and engineers.
Data Analysts! Join Us at #mdscon 2021
This year's conference features speakers and sessions for data professionals of all kinds.
Data Engineers and Data Architects! Join Us at #mdscon 2021
This year's Modern Data Stack Conference features speakers and sessions for data professionals of all kinds.
Database Schema Design: Best Practices for Integration and Analysis
Learn how to design normalized schemas that make life easier for analysts and data engineers.
How to Handle HIPAA Concerns With Cloud Data Warehouses
Achieve HIPAA compliance and reduce risk while offloading some of your operational burden.
Data Analytics vs. Business Intelligence
Should your data team focus on business problems and use cases, or expand into more complex areas like predictive analytics?
Business Intelligence: What You Need to Know
Business intelligence is the art of extracting actionable insights from your data. There’s a whole stack of technologies under the hood.
Data Warehouse vs. Database
Data warehouses are a particular kind of database. Learn how they are uniquely suited to analytics.
The Importance of ETL Security
ETL security is essential for safeguarding your customer's data and complying with regulations. Learn about the Fivetran approach.
dbt Explained
Learn how dbt adds data modeling and transformation to the modern data stack.
Introducing the Fivetran Protocol
Here's how SaaS providers can build bulletproof data replication APIs.
Data Transformation Fundamentals, Uses and Tools
Data can transform a struggling business into a successful one, but first, you need to transform the data. Here’s how.
Key Considerations for Pipeline Performance
Data pipeline performance hinges on several important techniques, including algorithmic optimization and parallelization.
What Is a Data Lakehouse?
The data lakehouse is a promising new technology that combines aspects of data warehouses and data lakes.
When to Use NoSQL and MongoDB
What is MongoDB used for? Learn how MongoDB and its Fivetran connector can help you.
SQL vs. NoSQL: Database Differences Explained
What is NoSQL, and what does it bring to the table?
ETL Platform Alternatives: Fivetran vs. Informatica and More
Compare popular data integration tools on cost, security, reliability and number of supported sources.
Which Connectors Does Your ETL Tool Need?
Make sure your data integration solution can connect to critical data sources.
How to Compare ETL Tools
Use these criteria to choose the best ETL tool for your data integration needs.
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