List of Etleap ETL Customers
Since 2010, our global team of researchers has been studying Etleap ETL customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Etleap ETL for Extract, Transform, and Load (ETL) from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Etleap ETL for Extract, Transform, and Load (ETL) include: Moderna, a United States based Life Sciences organisation with 5600 employees and revenues of $6.75 billion, PagerDuty, a United States based Professional Services organisation with 1242 employees and revenues of $467.0 million, eMoney Advisor, a United States based Banking and Financial Services organisation with 800 employees and revenues of $150.0 million and many others.
Contact us if you need a completed and verified list of companies using Etleap ETL, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Etleap ETL customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight | Insight Source |
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eMoney Advisor | Banking and Financial Services | 800 | $150M | United States | Etleap | Etleap ETL | Extract, Transform, and Load (ETL) | 2024 | n/a | In 2024, eMoney Advisor deployed Etleap ETL to centralize multiple on premises and cloud data sources into Amazon Redshift. The deployment supported a finance and customer experience initiative in the United States, enabling FP&A and customer journey analytics by pairing Etleap ETL, an Extract, Transform, and Load (ETL) solution, with Looker and reaching production in six weeks with broad internal adoption. The implementation configured Etleap ETL pipelines to extract from on premises systems and cloud sources, apply centralized transformation logic and schema enforcement, and load curated datasets into Amazon Redshift. Core ETL capabilities implemented included scheduled pipeline orchestration, incremental loads and data validation, with transformed data surfaced to Looker for semantic modeling and reporting. Integrations were explicitly with Amazon Redshift as the centralized analytical store and Looker as the analytics layer, creating an end to end flow from source extraction through transformation to self service reporting. Operational scope targeted finance FP&A and customer experience teams across the US, consolidating cross functional data feeds to support reporting and customer journey analysis. Governance and rollout focused on standardizing datasets and refresh cadences to support repeatable FP&A workflows and customer analytics consumption. Reported outcomes from the engagement included faster reporting and increased internal efficiency, with the six week implementation to production cited as a key delivery milestone. | |
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Moderna | Life Sciences | 5600 | $6.8B | United States | Etleap | Etleap ETL | Extract, Transform, and Load (ETL) | 2024 | n/a | In 2024 Moderna deployed Etleap ETL to operationalize life sciences research analytics in the United States. The implementation used Etleap ETL as an Extract, Transform, and Load (ETL) platform to ingest and prepare data from more than 100 internal and partner sources for analytics consumption. Deployment was executed in a VPC private cloud configuration, with Etleap ETL configured to run automated data pipelines that perform source connection, mapping, transformation, and staging into an AWS Redshift backed analytics repository. The architecture emphasized secure network isolation and scalable processing to align with research and regulatory data handling requirements. Operational scope centered on R&D and regulatory analytics teams, consolidating diverse internal and partner feeds into standardized Redshift schemas to support downstream reporting and analysis. Integrations explicitly included AWS Redshift as the analytics datastore, with Etleap ETL delivering transformed datasets into the Redshift backed analytics platform. Governance and operational controls were implemented through centralized pipeline orchestration and VPC based access controls, coupled with automated ingestion workflows to reduce manual ETL operations across sources. The deployment enabled secure, scalable data delivery for R&D and regulatory analytics as described in the Etleap case study. | |
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PagerDuty | Professional Services | 1242 | $467M | United States | Etleap | Etleap ETL | Extract, Transform, and Load (ETL) | 2024 | n/a | PagerDuty adopted Etleap ETL in 2024 to consolidate data ingestion and processing for its engineering and operations analytics. The Etleap ETL implementation centralized over 20 data sources into a central Amazon Redshift data warehouse, establishing a managed Extract, Transform, and Load (ETL) layer to standardize transformations and reduce ad hoc data handling. Implementation work focused on configuring reusable ETL pipelines, scheduling and orchestration of data flows, schema management for Redshift targets, and operational monitoring to lower maintenance overhead. Etleap ETL was used to extract from diverse sources, transform data into analytics ready models, and load those models into the Redshift destination to support downstream BI and analytics workloads. The rollout was scoped to engineering and operations analytics teams in the United States, consolidating more than 20 source systems into a single analytics store. The case study reports that data flow request fulfillment moved from a multiweek cycle to an hours level, and that ongoing maintenance burden on engineering teams was reduced, allowing engineers to focus more on core product work. Governance changes included centralizing pipeline ownership, standardizing data models in Redshift, and democratizing access to analytics across the organization, which broadened operational visibility beyond centralized data teams. The Etleap ETL deployment created a repeatable pattern for onboarding additional sources and unified extraction, transformation, and loading processes for PagerDuty. |
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