Charles Wang
What is ELT?
Extract, load and transform, or ELT, is a data integration process that moves data directly from source to destination for analysts to transform as needed.
What is a data pipeline?
A data pipeline is a series of actions that combine data from multiple sources for analysis or visualization.
Reliable data replication in the face of schema drift
Use these techniques to ensure that data replication remains robust, even as schemas change.
A visual guide to transformations: The Salesforce data model
Analysis-ready data models are built using sequences of transformations. Here's how we create our data model for Salesforce.
What is a data lake?
Data lakes serve as central destinations for business data and offer users a platform to guide business decisions.
What is data transformation?
Learn why data transformation is essential to data modeling and bringing your organization to the forefront of data literacy.
What is data integration?
Learn how data integration is the key to a mature analytics practice and more.
Ten 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.
Eleven 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.
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.
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.
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.
Network Performance and Data Integration
Data integration can easily become non-performant. Learn about some common bottlenecks.
Five Things I’ve Learned From Building Analytics Stacks at J.P. Morgan and Fivetran
These data management best practices apply to both large enterprises and fast-growing startups.
Why ELT Will Disrupt ETL
ETL, long a mainstay of data integration, is labor-intensive, brittle, complex — and ripe to be supplanted by ELT.
The Ultimate Guide to Data Integration
This guide is a one-stop introduction to data integration. Learn how to make data-driven decisions a reality for your organization!
The Dangers of DIY Database Replication
Database replication for database analytics involves many serious difficulties.
Process Isolation in Data Pipelines
Process isolation is an important pillar of software engineering that can keep your data pipelines (and you) out of trouble.
The Importance of Database Analytics
Use database connectors to uncover insights about your operations.
Building Efficient Data Pipelines With Incremental Updates
Sync data incrementally, or watch your pipeline grind to a halt.
Don’t Try This at Home: Building an Idempotent Data Pipeline
Learn about the technical challenges involved in building an idempotent data pipeline.
Idempotence and How It Failure-Proofs Your Data Pipeline
Learn how idempotence protects you from the worst consequences of data integration failures.
Database Schema Design Guide
Building a data connector requires you to design a schema to structure your data. This is how Fivetran does it.
Database Schema Best Practices
Learn how Fivetran provides normalized schemas to make life easier for analysts.
Your Data Access and Transparency Journey
How can your organization ensure data access and transparency? Measure yourself against this model, courtesy of our partners at Slalom.
What Is the Architecture of Automated Data Integration?
Automated data integration depends on several key concepts.
Build vs. Buy Data Pipelines: An Illustrated Guide
Consider these comparisons before you try to build your own data pipeline.
What Is Idempotence?
Idempotence is an important characteristic of many systems, including Fivetran. Here's what it means.
Three Kinds of Metrics GitHub Data Can Answer
Data from GitHub can help your engineers quantify how they are doing.
Five Dashboards to Jump-Start Your Analytics
Consider building these dashboards that help answer essential business questions.
Why You Need Automated Schema Migration
Schema changes can completely disrupt a data pipeline. Automated data integration offers a solution.
The Definitive Glossary of Data Integration Terms
New to analytics? Don’t know what an ERD is? Read this comprehensive list of important data integration terms.
How Fivetran Built Its Klaviyo Connector
The process of building a connector is inextricably linked with schema design.
How Well-Designed Schemas Jump-Start Analytics
Fivetran customers share how data integration gets easier with well-designed schemas.
Build vs. Buy: A Comparison
Wondering whether to build or buy? Consider these quality-of-life tradeoffs before you make a decision.
Build vs. Buy: By the Numbers
Wondering whether to build or buy? This infographic puts numbers to the issue.
Seven Steps to Getting Started With Automated Data Integration
In this excerpt from The Essential Guide to Data Integration, we discuss practical steps to getting started with automated data integration.
Top Technical Considerations for Choosing an ETL Tool
In this excerpt from The Essential Guide to Data Integration, we discuss the technical considerations for choosing a data integration tool.
Top Business Considerations for Choosing an ETL Tool
In this excerpt from The Essential Guide to Data Integration, we discuss the business considerations for choosing a data integration tool.
Why You Shouldn't Build Your Own Data Pipeline
In this excerpt from the Essential Guide to Data Integration, we discuss why you shouldn’t build your own data pipeline.
A Primer to Customer Attribution
Demystify customer decision-making with the right tracking tools and attribution models.
Use Fivetran, BigQuery and Looker to Get a Handle on NetSuite Data
NetSuite is essential but complicated. Use this guide to set up dashboards for all your NetSuite data.
Use Fivetran, Snowflake and Tableau to Get a Handle on NetSuite Data
NetSuite is essential but complicated. Use this guide to set up dashboards for all your NetSuite data.
BI Tools Comparison
BI tools can drive data literacy across your organization. Here’s how to choose the right one.
Treat Pipeline Automation Deficiency Syndrome Before It’s Too Late
Don’t miss these warning signs for pipeline automation deficiency! Your organization’s health depends on it.
A Friendly Reminder: One Plus NULL Equals NULL
Whenever you perform arithmetic across SQL columns, take care to handle NULL values appropriately.
Your Data Stack Should Live in the Cloud
For most organizations, on-premises is over. The future? Managed services in the cloud.
Simple and Automated Always Beats Complex and Handwritten
Fivetran Transformations offers a radically simpler approach to modeling data for reports and dashboards.
Machine Learning in One Lesson
You don’t need Python chops to get started with simple predictive models, just BigQuery ML and Looker (Fivetran helps, too!).
Instant Data Stack: Fivetran, Snowflake and Tableau
Want to deploy a full-fledged data stack in minutes? Connect Fivetran through Snowflake Partner Connect, then connect Snowflake to Tableau. That's it!
Now in BETA: Fivetran REST API
Use our REST API to automate your workflow by programmatically managing users, groups and connectors.
Now in BETA: Custom Roles
Tighten your security by specifying the exact sources your users can manage.
How to Think About Schema Changes
Prevent schema changes from ruining your workflow with help from Fivetran.
Google Ads (AdWords) Connector Now Comes With Prebuilt Reports
We now offer five prebuilt AdWords reports to give you a head start on ad analytics.
Why You Shouldn’t Build Reports From Raw Data
Or, how I learned to stop worrying and love data warehousing.
Simpson’s Paradox: Beware the Lurking Variable
You can easily reach misleading conclusions if you don’t carefully slice your data, consider lurking variables, and think about causality.
Build Connector Status Dashboards With the Fivetran REST API
Learn how to combine AWS Lambda and the new Fivetran REST API to build connector status dashboards.
Cloud Data Warehousing: It's Time to Re-Think Your Data Architecture
A digest of Fivetran CEO George Fraser's talk about the merits of cloud data warehousing at MicroStrategy World 2019.
An Introduction to Looker Blocks and LookML
Use Looker Blocks to conduct plug-and-play analyses with data from our standardized connectors.
Use Lambda Functions to Move Data From Redshift
Learn how to incrementally migrate data from Redshift tables using AWS Lambda.
Choose the Right Metrics
What gets measured gets managed. Make sure you measure the right things, identify vanity metrics, and perform sanity checks.
Fivetran and the Hierarchy of Data Needs
Your business's data needs follow a hierarchy, and Fivetran can give you a step up.
Don't Try This at Home: Fivetran Makes NetSuite’s API Usable
Understand the history of the Fivetran NetSuite connector and you'll see why you shouldn't try building your own.
Funnel Analysis and Conversion Metrics in SQL
Using SQL to conduct funnel analysis can help you make sense of multiple facets of your business.
Build vs. Buy: Some Back-of-the-Envelope Costs
A few simple calculations illustrate why it's ill-advised to build your own data pipeline.
Falcon.io: Building a Data-Driven Culture in a Fast-Growing Company
With its modern data stack, Falcon.io builds a comprehensive picture of the business’s critical operations, democratises access to data, and makes faster, more precise business decisions.
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