- FAQ\ \ Stitch FAQ\ \ Quick answers to questions about Stitch and Singer.\ \ Read now →
- Benchmark\ \ The State of Data Engineering\ \ Explore salaries, job growth, and skill sets of data engineers.\ \ Read now →
- Guide\ \ Getting Started with Stitch Enterprise\ \ How Stitch Enterprise meets the data needs of your organization.\ \ Read now →
- Benchmark\ \ The State of Data Science\ \ Just how many data scientists are there? How is the field changing?\ \ Read now →
- Guide\ \ Setting the data strategy for your growing organization\ \ Everything you need to know about building a data-driven company.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ What is an operational data store?\ \ An operational data store (ODS) is a central database used primarily for transactional functions and operational reporting.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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. \ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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?\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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. \ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ Using business intelligence tools for marketing\ \ Business intelligence (BI) tools allow enterprises to obtain valuable insights from information across all digital marketing channels.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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?\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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?\ \ Read now →
- Feature\ \ 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. \ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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?\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- 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.\ \ Read now →
- 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.\ \ Read now →
- Feature\ \ 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. \ \ Read now →
- 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. \ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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. \ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ What is Data Migration?\ \ Agile, scalable cloud-based data migration tools handle rapidly changing business needs with pay-as-you-go pricing. \ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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. \ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ What is predictive analytics?\ \ Predictive analytics applications parse complex data sets that integrate data from multiple sources to generate insights.\ \ Read now →
- 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.\ \ Read now →
- 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ Data warehouse design for data-driven enterprises\ \ Design a robust data warehouse by considering user needs, data modeling, the physical environment, and ETL tools.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- 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. \ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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. \ \ Read now →
- Feature\ \ Database vs. data warehouse: differences and dynamics\ \ An introduction to the key differences between databases and data warehouses, two components of a data pipeline.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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?\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ Business intelligence, data warehouses, and the cloud\ \ Make faster, better decisions with business intelligence tools and a cloud data warehouse.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ Prescriptive Analytics Guide: Use Cases & Examples\ \ Learn how prescriptive analytics can help your business learn how to make smarter decisions from its data\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 14 key metrics in Google Analytics for digital marketing\ \ Learn about 14 Google Analytics metrics that all digital marketers should understand.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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. \ \ Read now →
- 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. \ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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.\ \ Read now →
- Feature\ \ 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. \ \ Read now →
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.
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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.