Benchmark research, reports, and more.
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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Benchmark
The State of Data Science
Just how many data scientists are there? How is the field changing?
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Guide
Getting Started with Stitch Enterprise
How Stitch Enterprise meets the data needs of your organization.
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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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Business intelligence, data warehouses, and the cloud
Make faster, better decisions with business intelligence tools and a cloud data warehouse.
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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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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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Oracle Database: demystifying your data strategy
Accelerate your time to value with Oracle Database by replicating your data to a cloud warehouse.
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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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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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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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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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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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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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Data warehouse: a foundation for business intelligence
Learn about the role of a data warehouse in improving data accessibility and enhancing decision-making.
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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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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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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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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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What is data mining?
Data mining is the process of extracting relevant patterns or trends from a data set — but there's more to it than that.
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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 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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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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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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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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Business intelligence: a complete guide
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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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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What is data transformation: definition, benefits, and uses
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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OLTP and OLAP: a practical comparison
Online transaction processing (OLTP) captures, stores, and processes data from transactions. Online analytical processing (OLAP) analyzes data for insights.
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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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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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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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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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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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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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Understanding data replication and its impact on business strategy
Data replication stores the same data in multiple locations for faster access and improved system resilience.
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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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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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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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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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Snowflake: 5 benefits for your business
Snowflake's cloud-based data warehouse allows storage and compute functions to scale independently.
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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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Using prescriptive analytics
Learn how prescriptive analytics can help your business learn how to make smarter decisions from its data
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AWS S3 offers powerful features with minimal complexity
Amazon S3 is a cloud storage solution provided by Amazon Web Services, and is well suited for use as a data lake.
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What is data extraction?
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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What is predictive analytics?
Predictive analytics applications parse complex data sets that integrate data from multiple sources to generate insights.
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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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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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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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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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The causes and costs of data silos
Data silos waste business resources and make companies less efficient by inhibiting collaboration.
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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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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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What is a data pipeline?
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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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 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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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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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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What is a data lake?
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 are data migration tools?
Agile, scalable cloud-based data migration tools handle rapidly changing business needs with pay-as-you-go pricing.
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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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Snowflake vs. Redshift: choosing a modern data warehouse
These leading cloud data warehouses aren’t equally suited to all user needs.
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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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Unlocking big data with retail data analytics
Retail data analytics uses big data technology to optimize the customer experience, supply chain, inventory management, and retail expansion.
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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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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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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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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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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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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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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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Top 25 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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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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Keep up with Stitch news and feature releases.
A definitive guide to data definitions and trends.
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.