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FAQ
Stitch FAQ
Quick answers to questions about Stitch and Singer.
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Benchmark
The State of Data Engineering
Explore salaries, job growth, and skill sets of data engineers.
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Guide
Getting Started with Stitch Enterprise
How Stitch Enterprise meets the data needs of your organization.
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Benchmark
The State of Data Science
Just how many data scientists are there? How is the field changing?
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Guide
Setting the data strategy for your growing organization
Everything you need to know about building a data-driven company.
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Data science vs. data analytics: What they are and how to use them
Data science encompasses methods for manipulating raw data to obtain meaningful insights, while data analytics answers specific business questions.
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Data warehouse vs. data mart: a comparison
Cloud data warehouses are created quickly, and once a centralized data warehouse is operational, data marts can be spun off for business units.
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Redshift vs. Azure Synapse Analytics: comparing cloud data warehouses
Redshift and Azure Synapse Analytics both support data analytics, but differ in aspects of architecture, pricing, performance, administration, security, and compliance.
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What is an operational data store?
An operational data store (ODS) is a central database used primarily for transactional functions and operational reporting.
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What is data mining?
Data mining refers to the process of identifying within a data set patterns, trends, or anomalies. Click to learn how data mining works.
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OLTP vs OLAP: Understanding the differences and use cases
Online transaction processing (OLTP) captures, stores, and processes data from transactions. Online analytical processing (OLAP) analyzes data for insights.
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What is data extraction: tools and methods
Data extraction is the process of obtaining data from multiple sources, and moving it to a new destination designed to support online analytical processing.
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How to choose the right business intelligence tool
Stitch surveyed its customers to learn which business intelligence tools they use. These seven tools were mentioned most often.
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Data transformation: A comprehensive guide to benefits, challenges, and tools
Data transformation is the process of changing the format, structure, or values of data. It's a key step in ETL or ELT data integration.
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Tutorial: Using Google Data Studio with BigQuery and Stitch
How do you begin combining data from cloud applications with your internal databases to gain insight into your business?
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6 best practices for unlocking the value of a data warehouse
Discover best practices your organization should implement to get the most out of your data warehouse and facilitate data analytics.
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What is enterprise data management?
Enterprise data management refers to a set of processes and activities focused on data accuracy, quality, security, availability, and good governance.
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7 reasons to use Microsoft Power BI
Power BI has all the advantages of a modern BI platform, and unique benefits that distinguish it from the array of competing tools on the market today.
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6 Redshift features that change the data warehouse game
Here's a look at six features that set Redshift apart from other cloud data warehouses.
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Oracle Database: demystifying your data strategy
Oracle's ecosystem is expansive, but with the right tool, you can quickly and reliably bring your data to any cloud data warehouse, extracting the maximum value from your data with analytics and business intelligence tools.
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Best practices for data modeling
This article covers some guidelines on how to build better data models that are more maintainable, more useful, and more performant.
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Using business intelligence tools for marketing
Business intelligence (BI) tools allow enterprises to obtain valuable insights from information across all digital marketing channels.
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Marketing analytics: definition and uses
Marketing analytics is a set of technologies and methods for transforming data into marketing insights to maximize ROI from marketing initiatives.
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Tutorial: Using Redshift and Amazon QuickSight to deliver business analytics
How do you begin combining data from SaaS applications with your internal databases to gain insight into your business? In this tutorial, we’ll show you how QuickSight can help you deliver business insights.
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Unlocking big data with retail data analytics
Retail customers expect an engaging personal experience when shopping online or in a store. Retail data analytics helps organizations retain customers, and can enhance their lifetime value (LTV) to the business.
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Improving health care with business intelligence
Business intelligence (BI) leads to better health care. Learn how your organization can improve treatment outcomes and increase patient satisfaction with BI.
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Using business intelligence with big data
Enterprises can use the reporting and visualization capabilities of business intelligence (BI) tools to obtain insights from big data.
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MySQL vs. MariaDB: drop-in or diverging?
MariaDB started out as a fork of MySQL. A decade after its debut, how do the two databases differ?
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Application integration vs. data integration: how they differ
Application integration and data integration are two approaches organizations can take to make use of data from different systems, but they meet different needs.
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Best practices for data warehouse maintenance
The foundation of any organization's data analytics stack is its data warehouse. Have you given any thought to data warehouse maintenance?
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How Redshift differs from PostgreSQL
If you have SQL skills you developed from working with PostgreSQL, you'll be able to get by in Amazon Redshift pretty well – but you'll have to familiarize yourself with the differences between the two platforms.
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What is a Data Pipeline? Process and Examples
A data pipeline is a set of actions that ingests raw data from disparate sources and moves the data to a destination for storage, analysis, or business intelligence.
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4 benefits of self-service data ingestion
Learn how self-service data ingestion with an ELT tool makes it easy to replicate data and get business insights quickly.
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The causes and costs of data silos
A data silo (or information silo) is a repository of information in a department or an application that is not easily or fully accessible by other departments or applications.
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PostgreSQL vs. MySQL: 9 key criteria to drive your database decision
PostgreSQL and MySQL are two of the better known open source databases in use today, but which one is right for your organization, and why?
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Azure SQL Database: Grow your potential in the cloud
Azure SQL Database is Microsoft’s cloud-based SaaS relational database service, which is managed for availability, durability, and scalability.
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How to replicate Google Sheets to your data warehouse
Stitch now offers a Google Sheets integration! In the Stitch dashboard, choose Google Sheets and ask to be added to the public beta.
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Guide
Data Driven Advertising with Performance Marketing
Advertisers track digital advertising performance to properly drive value. Digital marketing strategy is nothing without data, make sure you know what you need to capture.
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FAQ
What is Google Analytics 4?
Today, your web analytics tool needs to include mobile app data to successfully track customer events. Watch this video for a step-by-step tutorial of connecting your GA4 data with the rest of your data pipeline.
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Data ingestion: the first step to a sound data strategy
Data ingestion is the transportation of data from assorted sources to a storage medium where it can be accessed, used, and analyzed by an organization.
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Guide
How Google BigQuery Compares as a Data Warehouse
Compare a free-to-start cloud warehouse solution like Google BigQuery to Amazon Redshift, Snowflake, and Microsoft Azure, and see how to quickly set up a data warehouse in minutes.
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Amazon Redshift vs. Google BigQuery: a comparison
Redshift and BigQuery have many similarities, but also important differences that can tip the scales in a cloud data warehouse comparison.
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Understanding data replication and its impact on business strategy
One common use of data replication is for disaster recovery, to ensure that an accurate backup exists at all times in case of a catastrophe, hardware failure, or a system breach where data is compromised.
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Snowflake vs. Redshift: choosing a modern data warehouse
Successful businesses depend on sound intelligence, and as their decisions become more data-driven than ever, it's critical that all the data they gather reaches its optimal destination for analytics: a high-performing data warehouse in the cloud.
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Data visualization and your business
Data visualization encompasses any method for displaying data visually to reveal useful trends and insights. It's a key aspect of business intelligence.
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Top ETL options for AWS data pipelines
Finding the best AWS ETL process for your business can make the difference between working on your data pipeline or making your data pipeline work for you.
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5 steps for choosing a cloud data warehouse
Learn about the most popular cloud data warehouses' key features and the criteria to use when evaluating them.
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How to transfer your data to Amazon S3
When moving data to S3, you can choose among the many services offered by AWS and third parties for everything from large migrations to streaming data.
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Improve your data team's productivity through automated data analytics
Automated data analytics is the practice of using computer systems and processes to perform analytical tasks with little or no human intervention.
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Resolving four common Snowflake data ingestion barriers with Stitch
Learn about the best Snowflake data ingestion methods using various different formats and volume of data.
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What is AWS S3?
Amazon S3, or simple storage service, is a cloud storage solution provided by Amazon Web Services. Use cases for AWS S3 include data lakes for big data analytics, and data archiving.
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What is Data Migration?
Agile, scalable cloud-based data migration tools handle rapidly changing business needs with pay-as-you-go pricing.
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BigQuery vs. Azure Synapse Analytics: comparing cloud data warehouses
BigQuery and Azure Synapse Analytics cloud data warehouses have the necessary features to support data analytics, but differ in aspects of architecture, pricing, and more.
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What's the difference between business intelligence and business analytics?
Find out how business intelligence and business analytics can help your enterprise make smarter, data-driven decisions.
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What is ELT? Understanding the difference between ELT and ETL
Cloud-based data warehouses and ELT deliver faster time to value than local hardware and ETL.
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How to use change data capture to optimize the ETL process
Businesses can optimize ETL by using change data capture to ingest only the data that has changed since the previous ETL operation.
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5 benefits of data analytics for your business
Data analytics can benefit your business by helping it reduce risks, improve its bottom line, and make informed decisions.
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Snowflake vs. BigQuery: comparing cloud data warehouses
Snowflake and BigQuery cloud data warehouses have great features to support data analytics, but differ in aspects such as architecture, pricing, and more.
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Snowflake Data Cloud: Revolutionizing data management and analytics
Snowflake is built for the cloud from the ground up. It delivers the flexibility and efficiency that simply isn’t possible with a traditional approach.
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What is a Data Lake? Examples & Solutions
A data lake is a centralized repository of raw, untransformed enterprise data. Today, most data lakes are implemented on cloud-based storage platforms.
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What is predictive analytics?
Predictive analytics applications parse complex data sets that integrate data from multiple sources to generate insights.
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Guide
Uncover business opportunities with Stitch Data and HubSpot
When you add HubSpot data to the Stitch data warehouse, you can learn more about your audience, access predictive analytics, and more — read on to learn more.
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Guide
How Can Google Analytics 4 Grow Ecommerce Websites?
A guide to why and how you should take advantage of new Google Analytics 4 functionality to grow your ecommerce site. Learn how to migrate historical data from an existing Universal Analytics property and pull new GA4 API data using Stitch.
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Building a data analytics stack for big data
Learn about the layers of the data analytics stack and how they can help your business unlock the value of big data.
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Data warehouse design for data-driven enterprises
Design a robust data warehouse by considering user needs, data modeling, the physical environment, and ETL tools.
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What is an enterprise data warehouse?
An EDW is a central repository that gathers enterprise data from multiple sources and makes it available for analysis, BI, and data-driven decision-making.
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General
Tutorial: Using Power BI with your data warehouse for analytics
To analyze data from diverse sources, you need a data warehouse that consolidates all of your data in a single location.
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What is big data analytics?
Big data analytics transforms digital information into useful business intelligence with software that makes sense of the endless stream of data a business receives.
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On-premises vs. cloud data warehouses: a comparison
Choosing a data warehouse depends on factors like cost, resources, control, scalability, and security that are unique to a business and its goals.
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How to connect a Singer tap with Stitch
We think it’s critical that ETL be extensible to support any data source. That's why we created the open source Singer project.
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Database vs. data warehouse: differences and dynamics
An introduction to the key differences between databases and data warehouses, two components of a data pipeline.
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Google BigQuery: a serverless data warehouse
Google BigQuery, a cloud-based data warehousing and analytics platform with a built-in query engine, can process terabytes of data in seconds.
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Business intelligence vs. data analytics
Data-driven organizations often use the terms "business intelligence" (BI) and "data analytics" interchangeably. They're not the same thing, but if someone asked you to explain the difference, what would you say?
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Data pipeline architecture: Building a path from ingestion to analytics
Data pipeline architecture is the design of processing and storage systems that capture, cleanse, transform, and route raw data to destination systems.
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MySQL: Get the best insights from your data, faster than ever
Drawing business insights from MySQL, the most popular open source RDBMS, requires an ETL solution.
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Business Intelligence - Your Complete Guide to BI Tools
Business intelligence (BI) is a collection of software tools and practices designed to leverage enterprise data to improve business decision-making.
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Business intelligence, data warehouses, and the cloud
Make faster, better decisions with business intelligence tools and a cloud data warehouse.
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3 advantages of self-service analytics
Self-service analytics tools allow nontechnical users to explore and share data, while maintaining necessary security protocols to protect sensitive information.
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Prescriptive Analytics Guide: Use Cases & Examples
Learn how prescriptive analytics can help your business learn how to make smarter decisions from its data
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An executive’s guide to data integration
Data integration is the process of consolidating and homogenizing data from disparate sources into a central location for data analysis and BI.
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What is Stream Processing?
Streaming data is a continuous flow of data from sources such as mobile apps, e-commerce websites, GPS devices, and IoT sensors.
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Top 24 tools for data analysis and how to decide between them
Take a look at the top tools for data analysis and learn how to choose one that fits your needs.
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Big data: a game-changer in every industry
Big data isn't just for search engines and media companies. Analyzing big data for insights can be a game-changer for any business.
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14 key metrics in Google Analytics for digital marketing
Learn about 14 Google Analytics metrics that all digital marketers should understand.
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Understanding ETL (extract, transform, load)
ETL (extract, transform, load) is a general process for replicating data from source systems to target systems to facilitate data analytics and BI.
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What is data consolidation?
Data consolidation is the corralling, combining, and storing of varied data in a single place to enable insights that drive better, faster decision-making.
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Guide
Social Media Data Extraction Across Entire Ad Stack
Automating social media data extraction allows advertisers to holistically track digital advertising performance and optimize their omnichannel ad strategy to drive leads faster.
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Using Python for ETL: tools, methods, and alternatives
Learn about libraries and frameworks for using Python to perform ETL, as well as alternative languages and tools to consider.
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What is a data warehouse? Your guide to definition, architecture, and benefits.
Learn about the role of a data warehouse in improving data accessibility and enhancing decision-making.
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A quick intro to Amazon QuickSight
Amazon QuickSight, a component of AWS, is a cloud-based business intelligence platform that allows users to create visualizations and dashboards.
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Data Strategy: What it is and how to achieve it
Data strategy refers to the tools, processes, and rules that define how to manage, analyze, and act upon business data.
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The data glossary
A definitive guide to data definitions and trends.
- Analytics
- Big data
- Business intelligence (BI)
- Common table expression
- Data analytics
- Data architecture
- Data engineering
- Data enrichment
- Data exploration
- Data ingestion
- Data integration
- Data lake
- Data migration
- Data mining
- Data modeling
- Data pipeline
- Data preparation
- Data science
- Data visualization
- Data warehouse
- Data Wrangling: Definition and Examples
- Database
- Deduplication
- ELT
- ESB - What is an Enterprise Service Bus?
- ETL
- ETL pipeline
- Information lifecycle management (ILM)
- Machine learning
- Master data management (MDM)
- SaaS
- Service-oriented architecture (SOA)
Looking for more?
Keep up with Stitch news and feature releases.
More on working with data
Stitch has a variety of guides to help you learn how to get the data from your various databases, SaaS tools, and other technologies into your warehouse manually. See these sample guides on sending MySQL to Amazon Redshift, Google AdWords to Google BigQuery, Jira to Postgres, and Salesforce to Snowflake.