--- title: The Top 7 ETL Requirements Template & Checklist --- # The Top 7 ETL Requirements Template & Checklist Last Reviewed: March 16, 2026 16 min read [No comments](https://www.selecthub.com/etl/etl-requirements/#respond) [ ![Ritinder Kaur](https://www.selecthub.com/wp-content/uploads/2021/06/cropped-Ritinder-Kaur-v2-1-96x96.png) ](https://www.selecthub.com/author/ritinder-kaur/) [Written by Ritinder Kaur](https://www.selecthub.com/author/ritinder-kaur/) Sr. Technical Content Writer [ ![Hunter Lowe](https://www.selecthub.com/wp-content/uploads/2023/11/cropped-Hunter-Headshot-96x96.jpg) ](https://www.selecthub.com/author/hunter-lowe/) [Edited by Hunter Lowe](https://www.selecthub.com/author/hunter-lowe/) Content Editor [ ![Sagardeep Roy](https://www.selecthub.com/wp-content/uploads/2025/01/Sagardeep-Roy-96x96.jpg) ](https://www.selecthub.com/author/sagardeep-roy/) [Technical Research by Sagardeep Roy](https://www.selecthub.com/author/sagardeep-roy/) Senior Analyst [ ![Bill Inmon](https://www.selecthub.com/wp-content/uploads/2024/12/cropped-Bill-Inmon-96x96.jpg) ](https://www.selecthub.com/author/bill-inmon/) [Contributions by Bill Inmon](https://www.selecthub.com/author/bill-inmon/) Expert Contributor Table of Contents * [Top ETL Requirements](#Top%5FETL%5FRequirements) * [1\. Data Sources and Targets Connectivity](#1%5FData%5FSources%5Fand%5FTargets%5FConnectivity) * [2\. Data Delivery](#2%5FData%5FDelivery) * [3\. Data Transformation](#3%5FData%5FTransformation) * [4\. Workflow Management](#4%5FWorkflow%5FManagement) * [5\. Metadata Management](#5%5FMetadata%5FManagement) * [6\. Data Quality](#6%5FData%5FQuality) * [7\. Platform Capabilities](#7%5FPlatform%5FCapabilities) * [ETL Requirement Gathering Considerations](#ETL%5FRequirement%5FGathering%5FConsiderations) * [What Are Your Goals?](#What%5FAre%5FYour%5FGoals) * [Are Technical Resources Available?](#Are%5FTechnical%5FResources%5FAvailable) * [What Is Your Business Size?](#What%5FIs%5FYour%5FBusiness%5FSize) * [How To Choose the Right System](#How%5FTo%5FChoose%5Fthe%5FRight%5FSystem) * [Create an ETL Requirements Checklist](#Create%5Fan%5FETL%5FRequirements%5FChecklist) * [Get Stakeholder Approval](#Get%5FStakeholder%5FApproval) * [Finalize the Requirements Document](#Finalize%5Fthe%5FRequirements%5FDocument) * [Reach Out to Vendors](#Reach%5FOut%5Fto%5FVendors) * [Decide](#Decide) * [FAQs](#FAQs) * [Next Steps](#Next%5FSteps) ETL requirements gathering is a team effort, and it can be overwhelming to carry everyone along. Managing stakeholder expectations and balancing them with organizational goals is a tightrope walk. Add to it assigning ownership for data engineering tasks to prepare for an ETL deployment, and you’ve got your hands full. Relax, we got you. [Get our ETL Tools Requirements Template](https://pmo.selecthub.com/etl-tools-requirements-onsite/) This article provides a handy ETL requirements checklist for selecting a suitable ETL solution. ## Top ETL Requirements [Data Sources and Targets Connectivity](#group%5F146) Simplify data integration by connecting to various sources, enabling unified data access and analysis. [Learn more](#1%5FData%5FSources%5Fand%5FTargets%5FConnectivity) [Data Delivery](#group%5F406) Empower data-driven decision-making by instantly accessing and analyzing relevant information across diverse sources. [Learn more](#2%5FData%5FDelivery) [Data Transformation](#group%5F540) Enhance data quality and reliability for accurate and insightful analysis with a consistent and usable format. [Learn more](#3%5FData%5FTransformation) [Workflow Management](#group%5F369) Streamline data engineering processes and foster collaboration by automating tasks and sharing reusable components. [Learn more](#4%5FWorkflow%5FManagement) [Metadata Management](#group%5F150) Improve understanding and governance by creating a comprehensive inventory of data assets, including lineage and quality metrics. [Learn more](#5%5FMetadata%5FManagement) [Data Quality](#group%5F637) Drive confident decisions by ensuring the accuracy, completeness and consistency of insight. [Learn more](#6%5FData%5FQuality) [Platform Capabilities](#group%5F307) Optimize platform performance and ensure regulatory compliance by proactively monitoring key metrics and usage patterns. [Learn more](#7%5FPlatform%5FCapabilities) We’ve onboarded over 100,000 users into our software selection platform. This has given us a wealth of insights into their usage patterns based on industry, company size and user persona. By leveraging this data, we’ve identified key requirements you should consider to minimize the risk of selecting the wrong software. Our goal is to empower you to benefit from the collective experience of your peers who’ve embarked on the same journey before you. ![ETL Requirements Project Summary in SelectHub Express App]() An ETL requirements checklist helps categorize must-have and nice-to-have features. Capturing ETL software requirements early on will set the tone for vendor discussions. Plus, a requirements document will be a handy reference after deployment. ![ETL Software Requirements and Features]() ### 1\. Data Sources and Targets Connectivity Prepare a source list once you’ve collated information from the concerned departments. Ask teams which data formats are acceptable, JSON, CSV and XML being the most common. How much data do they expect to handle on average and at what velocity? What are their real-time data requirements? Your ETL platform must connect to HTTPS servers, a common web protocol, and its alternatives, as some app and database servers don’t support HTTPS directly. Depending on your domain, you might need data from one or more of the software listed below. * [Enterprise BI platforms](https://www.selecthub.com/c/business-intelligence-tools/), including [SAP Analytics Cloud](https://www.selecthub.com/p/business-analytics-tools/sap-analytics-cloud/), [SAP BusinessObjects](https://www.selecthub.com/p/business-intelligence-tools/businessobjects/), [IBM Cognos](https://www.selecthub.com/p/business-analytics-tools/cognos-analytics/), [Oracle Business Intelligence Enterprise Edition (OBIIEE)](https://www.selecthub.com/p/business-intelligence-tools/oracle-bi/) and [Microsoft Power BI](https://www.selecthub.com/p/business-intelligence-tools/power-bi/). * Big data processing tools like Apache Hive, Cloudera Hive, Cloudera Impala, [Databricks Cloud](https://www.selecthub.com/p/big-data-analytics-tools/azure-databricks/), [Hortonworks](https://www.selecthub.com/p/business-intelligence-tools/hortonworks/), MapR Drill, [Google BigQuery](https://www.selecthub.com/p/big-data-analytics-tools/bigquery/) and Presto. * [CRM platforms](https://www.selecthub.com/c/crm-software/), including [Salesforce](https://www.selecthub.com/p/crm-software/salesforce/), [HubSpot](https://www.selecthub.com/p/marketing-automation-software/hubspot/) and [Freshsales](https://www.selecthub.com/p/crm-software/freshsales/). * [Customer success platforms](https://www.selecthub.com/c/customer-success-software/) like [Freshdesk](https://www.selecthub.com/p/help-desk-software/freshdesk/), [Intercom](https://www.selecthub.com/p/live-chat-software/intercom/) and [Zendesk](https://www.selecthub.com/p/help-desk-software/zendesk/). * Marketing platforms, such as [Marketo](https://www.selecthub.com/p/marketing-automation-software/marketo/), [Salesforce Pardot](https://www.selecthub.com/p/marketing-automation-software/pardot/), [Oracle Eloqua](https://www.selecthub.com/p/marketing-automation-software/eloqua/), [MailChimp](https://www.selecthub.com/p/marketing-automation-software/mailchimp/), [SurveyMonkey](https://www.selecthub.com/p/customer-experience-software/surveymonkey-enterprise/), Unbounce, and Google Adwords. * [eCommerce software](https://www.selecthub.com/c/ecommerce-platforms/), including [Shopify,](https://www.selecthub.com/p/ecommerce-platforms/shopify/) [Magento](https://www.selecthub.com/p/business-intelligence-tools/magento-business-intelligence/) and [BigCommerce](https://www.selecthub.com/p/ecommerce-platforms/bigcommerce/). * [ERP software](https://www.selecthub.com/c/erp-software/) like [SAP](https://www.selecthub.com/p/erp-software/sap-erp/) and Oracle. * Cloud warehouses and lakes, including [Snowflake](https://www.selecthub.com/p/business-intelligence-tools/snowflake/), [Amazon Redshift](https://www.selecthub.com/p/big-data-platform-software/redshift/), Azure Data Lake Storage Gen 2, [Azure Synapse Analytics](https://www.selecthub.com/p/big-data-analytics-tools/azure-synapse-analytics/), [Databricks Delta Lake](https://www.selecthub.com/p/big-data-analytics-tools/azure-databricks/) and [Google BigQuery](https://www.selecthub.com/p/big-data-analytics-tools/bigquery/). * Cloud computing platforms, including Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform. * Data modeling software like [Erwin Data Modeler](https://www.selecthub.com/p/business-intelligence-tools/erwin-data-modeler/) and SAP PowerDesigner. * Cloud storage systems, including Google Drive, OneDrive and [Dropbox](https://www.selecthub.com/p/collaboration-software-tools/dropbox-enterprise/). * [Accounting platforms](https://www.selecthub.com/c/accounting-software/), such as [Intuit QuickBooks](https://www.selecthub.com/p/accounting-software/quickbooks-online/), [Freshbooks](https://www.selecthub.com/p/accounting-software/freshbooks/), [Sage](https://www.selecthub.com/p/accounting-software/sage-100-cloud/) and [Xero](https://www.selecthub.com/p/accounting-software/xero/). * Industry-standard message formats, like electronic data interchange (EDI), * Health Level Seven International (HL7) and Society for Worldwide Interbank Financial Telecommunication (SWIFT). * Mainframes and legacy databases like IMS DB, DB2 z/OS, DB2 i5/OS, VSAM and JCL. * Massively parallel processing (MPP) databases, including Aster Data nCluster, Pivotal Greenplum and Sybase IQ. * Message-oriented middleware (MOM) such as [IBM WebSphere MQ](https://www.selecthub.com/p/business-process-management-software/websphere/), Microsoft Message Queuing (MSMQ), Java Message Service (JMS) and TIBCO Rendezvous. * [NoSQL databases](https://aws.amazon.com/nosql) like MongoDB, Cassandra, Apache Hbase, Couchbase, CouchDB, Redis, Riak and Amazon SimpleDB. * [Point-of-sale software](https://www.selecthub.com/c/pos-software/), including [PayPal](https://www.selecthub.com/p/ecommerce-platforms/paypal/), [Square](https://www.selecthub.com/p/pos-software/square-pos/) and [Stripe](https://www.selecthub.com/p/pos-software/stripe/). * [Project management platforms](https://www.selecthub.com/c/project-management-software/) such as [Jira](https://www.selecthub.com/p/project-management-software/jira/), [Asana](https://www.selecthub.com/p/project-management-software/asana/), [Trello](https://www.selecthub.com/p/project-management-software/trello/) and [Mavenlink.](https://www.selecthub.com/p/psa-software/mavenlink/) * Relational databases, including Oracle, [SQL Server](https://www.selecthub.com/p/relational-databases/sql-server/), Sybase ASE and [IBM DB2](https://www.selecthub.com/p/relational-databases/ibm-db2/). * [SEO](https://www.selecthub.com/c/seo-software/) and web analytics tools like [Adaptive Insights,](https://www.selecthub.com/p/accounting-software/adaptive-insights/) [Adobe Analytics Brandwatch](https://www.selecthub.com/p/marketing-automation-software/brandwatch/), Crimson Hexagon, Google Analytics, Moat Analytics, Salesforce Social Studio and [Heap Analytics](https://www.selecthub.com/p/business-intelligence-tools/heap/). * Popular social media platforms, such as Twitter, Facebook, TikTok, Instagram, YouTube, LinkedIn and Pinterest. * Standard files, including ML Excel, MS Word, MS PowerPoint, PDF, flat files, text, CSV, XML and JSON files. * Streaming platforms like Apache Kafka and [Confluent](https://www.selecthub.com/p/big-data-analytics-tools/confluent/). [Build Comprehensive Requirements with the Decision Platform](https://www.selecthub.com/decision-platform/) ### 2\. Data Delivery Full and incremental refreshes and event-based ingestion keep your databases up-to-date and ready to go. ![DynamoDB to Snowflake sync dashboard showing history, stats, and logs]() Ensure reliable ETL pipelines by monitoring the sync history dashboard. [Source](https://fivetran.com/docs/core-concepts/syncoverview) A full refresh is resource-intensive, though not as complex as incremental updates — to load data selectively, you’ll need to dot your i’s and cross your t’s. Incremental updates are behind eCommerce platforms updating inventory after each sale and stock market applications uploading the latest share prices to underlying databases. [Change data capture](https://www.qlik.com/us/change-data-capture/cdc-change-data-capture) is an ETL technique that delivers data updates to downstream systems after recording them in real time. Event-based ingestion works on a pre-defined trigger — the ETL platform extracts data when a specified condition is satisfied. It delivers the latest data to downstream systems, enabling a proactive response and a satisfactory customer experience. Data delivery methods should adhere to your business rules, and your ETL system should inherit them when you bring it on board. ### 3\. Data Transformation Ever seen a glass blower at work? They shape molten glass into beautiful tumblers, vases and decanters. Data transformation is similar, molding raw data into refined, usable insights. It includes filters, joins, pivot/unpivot, string and aggregate functions. ![Fivetran transformations list with status, connectors, and run details]() A dashboard to track transformations should be part of your ETL requirements. [Source](https://fivetran.com/docs/using-fivetran/fivetran-dashboard/transformations) Sort functions work with aggregate functions to display data in a meaningful order. Lookups enrich data by adding contextual information from other tables. Data type conversions remind me that even the best data systems need a little help from humans when they confuse date or alphanumeric fields as numbers. Before talking to vendors, assess the required data transformations and complexity. Will you need scripting if built-in functions don’t suffice? Does your preferred ETL software provide a code editor and auto-suggestions for non-technical users? [Get our ETL Tools Requirements Template](https://pmo.selecthub.com/etl-tools-requirements-onsite/) ### 4\. Workflow Management A readymade ETL workflow would be like getting the keys to the city — pipeline templates help you hit the ground running. For custom tasks, workflow wizards allow you to set up a sequence of ETL steps and set them on a schedule or pre-defined triggers. If you’re a coding wiz, a query builder allows creating scripts for custom jobs. Job notebooks are collaborative workspaces for running integration workflows. Object libraries provide reusable workflow components and metadata — there’s no need to reinvent the wheel every time. With version control, you can manage ETL workflows, transformations and configurations. Error handling, debugging and process tuning are part of ETL tools. Workflow tags are great for searchability as processes multiply. Finding workflows becomes easier if you can tag them by team assignments, security protocols and projects. ### 5\. Metadata Management Metadata is your map and address book rolled into one. It helps track data’s origin, transformations, workflows and related issues. Like the data it represents, metadata has a lifecycle from birth to archival. ![Talend Data Catalog dashboard with tools for governance and metadata]() Metadata enhances searchability and agile analysis. [Source](https://youtu.be/dv8eiGcy4Ao?si=DbjN1JRs8TWQF1m8&t=88) Before that, metadata mapping from source to target systems helps in seamless data uploads. It’s like carefully removing a piece from one puzzle and placing it in the correct spot in another. Your ETL software should support the extraction and import/export of metadata. As data moves, so should its metadata to support bulk updates and general data management. Custom metadata views will save search time, helping find the desired dataset associations. Your ETL solution should support impact analysis — assessing how changes to data sources, transformations and system configurations will affect downstream systems. ### 6\. Data Quality Data quality starts from the schema, a graphical representation of how your system arranges data, in your source and target systems. Once your ETL tool detects the schema, it should update the metadata accordingly. Your ETL platform might store metadata in a data catalog or database along with the actual data. Alternatively, you can store it in a spreadsheet or a custom metadata tool. If this process is automatic, it helps onboard new sources quicker, promoting agile analysis. A business glossary establishes clear data definitions, aligning disparate teams toward the same goal. Data enrichment holds great promise in virtually every field. Enriching HR data with historical employee tenure data can reveal interesting patterns to guide future hiring efforts. Similarly, planning your sales strategy by incorporating previous campaign data is an excellent use of historical data. What worked? What didn’t? What could work now? Driving safely involves looking at the rearview mirror from time to time. Automated feature engineering improves the understanding of data associations, reducing the time to insight. Plus, it assists in defining governance rules. If set up properly, automated workflows will correct data anomalies without requiring human intervention. [Select the Right Software with the Free Lean Selection Book](https://pmo.selecthub.com/lean-selection-book/) ### 7\. Platform Capabilities So, you bought the ETL platform subscription. How’s your data team using it, and which tasks did they run? Is your investment well-spent? Visibility into platform usage and integration tasks is crucial to assess your money’s worth. Your ETL tool should provide dashboarding and reporting for tracking user activity, compliance and data quality metrics. A global search bar helps you find files, folders, fields, objects and tags. Real-time alerts keep you updated on the status of the ETL pipeline process so you can intervene and resolve issues as they arise. ![Fivetran dashboard overview with connectors, activity, and insights]() Manage connections, transformations and storage from the homepage. [Source](https://fivetran.com/docs/using-fivetran/fivetran-dashboard) [Get our ETL Tools Requirements Template](https://pmo.selecthub.com/etl-tools-requirements-onsite/) ## ETL Requirement Gathering Considerations Evaluate your business needs internally by asking the following questions. ### What Are Your Goals? Ever tried shooting darts in the dark? It’s not much fun — you’re just throwing things around but not hitting the target. Checking off goal evaluation on your task list without due diligence is like that. A needs analysis is a must-do exercise before gathering requirements. Here are some considerations to keep in mind when conducting one: * Understand your team’s goals. What do you want to accomplish — improve integration, enhance customer satisfaction or boost revenue? * Would you prefer a standalone ETL tool like [Talend](https://www.selecthub.com/p/etl-tools/talend/) or an integrated suite like [IBM InfoSphere](https://www.selecthub.com/p/etl-tools/infosphere-information-server/) and [Informatica PowerCenter](https://www.selecthub.com/p/etl-tools/informatica-powercenter/)? * Customizations will depend on your domain, data sources, formats and business rules. * What do you need to do to reduce the technical debt of legacy software? Will it involve an IT assessment to gauge its compatibility with modern ETL tools? * If you’re planning ETL in the cloud, identify which factors will make or break your software buying decision. According to [Bill Inmon](https://www.linkedin.com/in/billinmon), data warehousing expert and best-selling author, the primary considerations include the data volumes and how often you need to perform transformations. * Measuring the success of your ETL deployment will require establishing clear benchmarks at the onset. ### Are Technical Resources Available? Technical expertise on call can be a lifesaver when deploying, even if you work with the vendor or implementation partner. You’ll need data engineers to deploy and map the ETL solution to your data architecture. Though managed solutions are the vendor’s responsibility, there’s always a learning curve. Assess carefully — will your in-house team prove adequate, or will you need to hire externally? ### What Is Your Business Size? Small businesses have simpler data and need less frequent updates. Integration needs are likely to be lighter, with a smaller source list and simpler transformations. User management is easier, and while they might need customization, pivoting to adapt to a new ETL solution isn’t likely to be disruptive. Large enterprises have sophisticated requirements regarding data complexity, integrations and advanced analytics. Customization needs might be more extensive, but they’re more set in their ways and less flexible if the tool demands it. Dedicated support is a must-have for any business, whether large or small. Enterprises with large-scale operations will need a dedicated account manager and round-the-clock support. [Get our ETL Tools Requirements Template](https://pmo.selecthub.com/etl-tools-requirements-onsite/) ## How To Choose the Right System Shortlisting your business needs in a requirements document lays down your organization’s expectations from the ETL software. ![ETL Software Selection Steps]() ### Create an ETL Requirements Checklist Build a checklist using the abovementioned primary requirements and questions. ![Set ETL Requirements with SelectHub Express App]() Define specific requirements with the SelectHub Jumpstart Platform. Departmental data differs from business data — it’s something we don’t pay attention to. When we perform ETL, we convert departmental data into business data. Inmon explains it: ![Bill Inmon]() ETL represents a significant transformation of data. Most data was written for the purpose of satisfying an organization’s departmental needs. But when accounting, sales, marketing and finance want to look at data across the enterprise they cannot use departmental data. Each department has their own way of creating and using their data. And each department has their own formats, encoding schemes, and the like. As people use ETL they are transforming application data into corporate data. The significance of that transformation escapes many people. Bill Inmon Co-founder, Datavox According to him, the **T** in ETL should be the primary focus. Your data is only as good as your transformations, and analytics systems don’t check data accuracy and integrity, taking it at face value. The result is incorrect information and wrong decisions, and you want to avoid it at all costs. That’s why transformations should be the focus of your ETL processes. We recommend adding the following questions to your list before talking to vendors. * How frequent are the updates? * What is the average turnaround time for support requests and issue fixes? * How does the vendor handle unscheduled downtime? * Which features are built-in, and which functionalities are available for a price? * Which processes can you automate? * How steep is the learning curve? Is training required, and is it available? * What is the deployment time? * What customization options do they offer? [Receive Advice From the Experts](https://www.selecthub.com/managed-selection-services/) ### Get Stakeholder Approval Once the ETL requirements checklist is ready, share it with senior stakeholders and teams. Google Drive and MS Office are excellent collaboration tools to get everyone’s input on ranking features by priority. You can use a spreadsheet or refer to our [requirements management platform](https://www.selecthub.com/about/selecthub-product-site/). ### Finalize the Requirements Document Summarize your findings into a formal report and share with the teams that’ll use the tool directly or indirectly. Stakeholder meetings are crucial for getting their perspectives on which features should rank higher and why. Be prepared to push not-too-critical requirements to the back burner if need be. A good grasp of your company’s operations, vision and roadmap is necessary to identify requirements correctly. ### Reach Out to Vendors Create a questionnaire from your ETL requirements and send it to potential vendors. Review their responses and select the ones that promise to address your business needs. Reach out to the chosen vendors for demos and proof-of-concept and score them on their performance. ![Top 5 ETL products comparison report in SelectHub Express App]() Compare up to five ETL products with our Jumpstart Platform. ### Decide Start at the top of your vendor shortlist and contact sellers for further discussions. Finalize a suitable vendor based on how well their terms of service and conditions match your needs and get stakeholder approval to proceed with the software procurement. Have your legal team review the vendor agreement and sign on the dotted line. [Get our ETL Tools Requirements Template](https://pmo.selecthub.com/etl-tools-requirements-onsite/) ## FAQs [What is meant by ETL?](#group%5F794) ETL is a data integration process to prepare data for analysis. Beyond extracting, transforming and loading data, this process focuses on data quality for business intelligence and analytics. Organizations should focus on how ETL can better facilitate better insights and strategic decisions rather than viewing it merely as a data-gathering exercise. [What are the five steps of the ETL process?](#group%5F102) 1. Extract: Source raw data from databases, files, APIs and cloud systems and place it in a temporary staging area. 2. Clean: Identify discrepancies and remove errors and duplicates with data profiling. 3. Transform: Convert the data to match the format in the target system and organize it in schemas for searchability. Apply business rules for data quality and integrity. 4. Load: Efficiently transfer data into the warehouse or database. 5. Analyze: Derive meaningful insight using descriptive analysis or apply advanced techniques, such as data mining, statistical analysis and machine learning. [What are the requirements for ETL Testing?](#group%5F130) The litmus test for ETL is when your data is accurate and decisions are on point. But, you can’t wait that long. The right time to test your ETL processes is after the initial data upload, the addition of a new data source, and the migration of data from one target system to another. Check data for correctness, format and structure, and replicate transformations to check if the system adheres to business rules. Here’s what the testing process will look like: * Assess your reporting needs. Who needs the test results, what should be the format and what should you include/omit? * Verify source connections and the data structure mappings to the target database. * Create test cases based on ETL mappings and business rules. Leave nothing to chance — include edge cases to ensure comprehensive test coverage. * Run the ETL process to extract data from the source systems into the staging area and check the results. Was there any data corruption or loss? * Apply transformations and check if they adhere to the target schema and business rules. This step checks for data quality and consistency. * Load the transformed data into the warehouse and check the record count to confirm your data is complete. Did the warehouse reject incorrect data? * Identify, document and report bugs and fix them before proceeding to the next step. * Share your findings with stakeholders. * Iterate and improve your test cases and processes based on this testing cycle. [Get our ETL Tools Requirements Template](https://pmo.selecthub.com/etl-tools-requirements-onsite/) ## Next Steps In our conversation, Inmon shone the spotlight on a data type organizations ignored for too long — text. We generate extremely large volumes of text data daily, but it has languished in the shadows till now as we didn’t have the technology to harness it. But now we do, with textual ETL. Ask yourself — do you have the data maturity to deploy it? We can help you figure it out. Our free [ETL requirements template](https://pmo.selecthub.com/etl-tools-requirements-onsite/) will help you hit the ground running with a pre-filled, customizable list. Do you have any questions about the ETL requirements process? Ask away in the comments! ### Trending Topics #### [ETL](https://www.selecthub.com/category/etl/) [ETL vs ELT: A Comprehensive Comparison](https://www.selecthub.com/etl/etl-and-elt/) [ETL (extract, transform and load) gathers business intelligence, but it isn’t fast enough for specific… ](https://www.selecthub.com/etl/etl-and-elt/) [ ![Ritinder Kaur](https://www.selecthub.com/wp-content/uploads/2021/06/cropped-Ritinder-Kaur-v2-1-96x96.png) Ritinder Kaur ](https://www.selecthub.com/author/ritinder-kaur/) May 12, 2026 Originally published in October 2022 and last updated in March 2026\. Contributions from Ritinder Kaur, Sagardeep Roy, Akshay Parekh, Hunter Lowe, and Bill Inmon. ## About the Contributors The following SelectHub team members and subject matter experts helped research, create, and review this content. [ ](https://www.selecthub.com/author/ritinder-kaur/) Written by [Ritinder Kaur](https://www.selecthub.com/author/ritinder-kaur/) Sr. Technical Content Writer Ritinder Kaur is a Senior Technical Content Writer at SelectHub and has ten years of experience writing about B2B software and quality assurance. She has a Masters degree in English language and literature and writes about Business Intelligence and Data Science. Her articles on software testing have been published on Stickyminds. [See Full Bio](https://www.selecthub.com/author/ritinder-kaur/) [ ](https://www.selecthub.com/author/sagardeep-roy/) Technical Research by [Sagardeep Roy](https://www.selecthub.com/author/sagardeep-roy/) Senior Analyst Sagardeep is a Senior Research Analyst at SelectHub, specializing in diverse technical categories. His expertise spans Business Intelligence, Analytics, Big Data, ETL, Cybersecurity, artificial intelligence and machine learning, with additional proficiency in EHR and Medical Billing. Holding a Master of Technology in Data Science from Amity University, Noida, and a Bachelor of Technology in Computer Science from West Bengal University of Technology, his experience across technology, healthcare, and market research extends back to 2016\. As a certified Data Science and Business Analytics professional, he approaches complex projects with a results-oriented mindset, prioritizing individual excellence and collaborative success. [See Full Bio](https://www.selecthub.com/author/sagardeep-roy/) [ ](https://www.selecthub.com/author/akshay-parekh/) Technical Research by [Akshay Parekh](https://www.selecthub.com/author/akshay-parekh/) Principal Analyst Akshay is a highly analytical and detail-oriented Software Research Analyst with a proven track record of generating industry-standard templates for RTs, RFIs, pricing guides, LTSRs, and more across software categories like Big Data Analytics, BI, ETL, EDI, EHR, Endpoint Security and Medical Billing. He holds a Bachelor of Technology in Computer Science Engineering and an MBA in Marketing and Analytics from IBS Hyderabad. He loves to spend time exploring spirituality, reading books, and watching sports, especially cricket, tennis, MMA, and boxing. [See Full Bio](https://www.selecthub.com/author/akshay-parekh/) [ ](https://www.selecthub.com/author/hunter-lowe/) Edited by [Hunter Lowe](https://www.selecthub.com/author/hunter-lowe/) Content Editor Hunter Lowe is a Content Editor, Writer and Market Analyst at SelectHub. His team covers categories that range from ERP and business intelligence to transportation and supply chain management. Hunter is an avid reader and Dungeons and Dragons addict who studied English and Creative Writing through college. In his free time, you'll likely find him devising new dungeons for his players to explore, checking out the latest video games, writing his next horror story or running around with his daughter. [See Full Bio](https://www.selecthub.com/author/hunter-lowe/) [ ](https://www.selecthub.com/author/bill-inmon/) Contributions by [Bill Inmon](https://www.selecthub.com/author/bill-inmon/) Expert Contributor Bill Inmon is a computer scientist, author and technology pioneer. His data warehouse architecture emphasizes a top-down, subject-oriented design for maintaining data integrity and consistency. His books and articles continue to educate and inspire data professionals worldwide. His hands-on experience and thought leadership have shaped the software industry's best practices. As co-founder of Datavox, his current focus is textual ETL for comprehensive data analytics. [See Full Bio](https://www.selecthub.com/author/bill-inmon/) Ritinder KaurETL vs ELT: A Comprehensive Comparison * ‹ * › ### Conversation ![Avatar](https://secure.gravatar.com/avatar/281d3616cf761f3582c0d76c23517846?s=32&d=mm&r=g) Write a response [Cancel reply](https://www.selecthub.com/etl/etl-requirements/#respond) Your message Your name \* Your email \* Website Save my name, email, and website in this browser for the next time I comment. Compare **Tier 1:** Fully/moderately supported out-of-the-box allowing for quick and easy deployment. Fully or moderately supported out-of-the-box with industry-leading capabilities and is immediately available after installation without needing any add-ons, integrations, or custom development. **Tier 2:** Supported with workarounds or add-ons that may require additional costs. Not directly available in the software, but can be accomplished using other built-in features, workarounds, or add-ons/products from the vendor with or without any additional cost. **Tier 3:** Requires partner integrations or custom development that is often at an additional cost. Requires additional integrations, plugins, marketplace applications from a third-party vendor, or custom development using the APIs, libraries, extensions, and development framework supported by the software, with or without any additional cost. [Close](#) ```json {"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.selecthub.com\/etl\/etl-requirements\/#article","isPartOf":{"@id":"https:\/\/www.selecthub.com\/etl\/etl-requirements\/"},"author":{"name":"Ritinder Kaur","@id":"https:\/\/www.selecthub.com\/#\/schema\/person\/7ef713c9c022e75ea5995d3c1cd516b2"},"headline":"The Top 7 ETL Requirements Template & Checklist","datePublished":"2022-10-20T00:35:03+00:00","dateModified":"2026-03-16T16:08:09+00:00","mainEntityOfPage":{"@id":"https:\/\/www.selecthub.com\/etl\/etl-requirements\/"},"wordCount":3447,"commentCount":0,"publisher":{"@id":"https:\/\/www.selecthub.com\/#organization"},"articleSection":["ETL"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/www.selecthub.com\/etl\/etl-requirements\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/www.selecthub.com\/etl\/etl-requirements\/","url":"https:\/\/www.selecthub.com\/etl\/etl-requirements\/","name":"Top 7 ETL Requirements Template & Checklist For 2026","isPartOf":{"@id":"https:\/\/www.selecthub.com\/#website"},"datePublished":"2022-10-20T00:35:03+00:00","dateModified":"2026-03-16T16:08:09+00:00","breadcrumb":{"@id":"https:\/\/www.selecthub.com\/etl\/etl-requirements\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.selecthub.com\/etl\/etl-requirements\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/www.selecthub.com\/etl\/etl-requirements\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.selecthub.com\/"},{"@type":"ListItem","position":2,"name":"ETL","item":"https:\/\/www.selecthub.com\/category\/etl\/"},{"@type":"ListItem","position":3,"name":"The Top 7 ETL Requirements Template & Checklist"}]},{"@type":"WebSite","@id":"https:\/\/www.selecthub.com\/#website","url":"https:\/\/www.selecthub.com\/","name":"SelectHub","description":"Confidence in Software","publisher":{"@id":"https:\/\/www.selecthub.com\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.selecthub.com\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.selecthub.com\/#organization","name":"SelectHub","url":"https:\/\/www.selecthub.com\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.selecthub.com\/#\/schema\/logo\/image\/","url":"","contentUrl":"","caption":"SelectHub"},"image":{"@id":"https:\/\/www.selecthub.com\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/selecthub\/","https:\/\/x.com\/SelectHub","https:\/\/www.linkedin.com\/company\/selecthub"]},{"@type":"Person","@id":"https:\/\/www.selecthub.com\/#\/schema\/person\/7ef713c9c022e75ea5995d3c1cd516b2","name":"Ritinder Kaur","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.selecthub.com\/wp-content\/uploads\/2021\/06\/cropped-Ritinder-Kaur-v2-1-96x96.png","url":"https:\/\/www.selecthub.com\/wp-content\/uploads\/2021\/06\/cropped-Ritinder-Kaur-v2-1-96x96.png","contentUrl":"https:\/\/www.selecthub.com\/wp-content\/uploads\/2021\/06\/cropped-Ritinder-Kaur-v2-1-96x96.png","caption":"Ritinder Kaur"},"description":"Ritinder Kaur is a Senior Technical Content Writer at SelectHub and has ten years of experience writing about B2B software and quality assurance. She has a Masters degree in English language and literature and writes about Business Intelligence and Data Science. Her articles on software testing have been published on Stickyminds.","sameAs":["https:\/\/www.selecthub.com","https:\/\/www.linkedin.com\/in\/ritinder-kaur\/"],"url":"https:\/\/www.selecthub.com\/author\/ritinder-kaur\/"}]} {"@context":"https://schema.org","@type":"FAQPage","mainEntity":[{"@type":"Question","name":"What is meant by ETL?","acceptedAnswer":{"@type":"Answer","text":"ETL is a data integration process to prepare data for analysis. Beyond extracting, transforming and loading data, this process focuses on data quality for business intelligence and analytics.\nOrganizations should focus on how ETL can better facilitate better insights and strategic decisions rather than viewing it merely as a data-gathering exercise."}},{"@type":"Question","name":"What are the five steps of the ETL process?","acceptedAnswer":{"@type":"Answer","text":"Extract: Source raw data from databases, files, APIs and cloud systems and place it in a temporary staging area.\nClean: Identify discrepancies and remove errors and duplicates with data profiling.\nTransform: Convert the data to match the format in the target system and organize it in schemas for searchability. Apply business rules for data quality and integrity.\nLoad: Efficiently transfer data into the warehouse or database.\nAnalyze: Derive meaningful insight using descriptive analysis or apply advanced techniques, such as data mining, statistical analysis and machine learning."}},{"@type":"Question","name":"What are the requirements for ETL Testing?","acceptedAnswer":{"@type":"Answer","text":"The litmus test for ETL is when your data is accurate and decisions are on point. But, you can’t wait that long.\nThe right time to test your ETL processes is after the initial data upload, the addition of a new data source, and the migration of data from one target system to another. Check data for correctness, format and structure, and replicate transformations to check if the system adheres to business rules.\nHere’s what the testing process will look like:\n\nAssess your reporting needs. Who needs the test results, what should be the format and what should you include/omit?\nVerify source connections and the data structure mappings to the target database.\nCreate test cases based on ETL mappings and business rules. Leave nothing to chance — include edge cases to ensure comprehensive test coverage.\nRun the ETL process to extract data from the source systems into the staging area and check the results. Was there any data corruption or loss?\nApply transformations and check if they adhere to the target schema and business rules. This step checks for data quality and consistency.\nLoad the transformed data into the warehouse and check the record count to confirm your data is complete. Did the warehouse reject incorrect data?\nIdentify, document and report bugs and fix them before proceeding to the next step.\nShare your findings with stakeholders.\nIterate and improve your test cases and processes based on this testing cycle."}}]} { "@context": "https://schema.org", "@type": "Article", "headline": "The Top 7 ETL Requirements Template & Checklist", "author":{ "@type": "Person", "name": "Ritinder Kaur", "url": "https://www.selecthub.com/author/ritinder-kaur/", "jobTitle":"Sr. Technical Content Writer", "image": "https://www.selecthub.com/wp-content/uploads/2021/06/cropped-Ritinder-Kaur-v2-1-96x96.png" }, "publisher":{ "@type": "Organization", "name": "SelectHub", "logo": { "@type":"ImageObject", "url": "https://www.selecthub.com/wp-content/uploads/2019/10/favicon.png" } }, "datePublished": "2022-10-19T18:35:03-06:00", "dateModified": "2026-03-16T10:08:09-06:00", "mainEntityOfPage": "https://www.selecthub.com/etl/etl-requirements/" } ```