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Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Michelin, an e2open customer evaluated Oracle Transportation Management

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Michelin, an e2open customer evaluated Oracle Transportation Management

List of IBM InfoSphere DataStage Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight
Allstate Insurance 55000 $67.7B United States IBM IBM InfoSphere DataStage Extract, Transform, and Load (ETL) 2021 n/a
In 2021, Allstate implemented IBM InfoSphere DataStage as a core Extract, Transform, and Load (ETL) capability to standardize enterprise ETL pipelines. The deployment anchored data movement and transformation workstreams for the companys data engineering and analytics functions using IBM InfoSphere DataStage alongside complementary tooling. Configuration focused on pipeline development and orchestration, with DataStage jobs and Azure Data Factory used to create and schedule ETL pipelines, and advanced SQL in Snowflake employed for set based transformations and efficient data movement. The implementation supported API driven access patterns, with RESTful APIs built with FastAPI to expose transformed datasets to downstream applications and analytics consumers. Integrations explicitly included Azure Data Factory for orchestration, Snowflake for analytic storage and advanced SQL processing, and cloud APIs from AWS and GCP for automated resource management and data collection. The work also connected to ML lifecycle tooling, including MLflow and custom PyTorch data transformers, to enable feature preparation and model training workflows that consume ETL outputs. Governance and operational changes emphasized software engineering practices, including documented APIs, coding standards, enforced code reviews, and unit testing with Pytest, alongside monitoring tools for pipeline performance tracking. The broader data engineering program included mentoring of junior engineers and the development of interactive Dash applications in AWS for stakeholder visualization, and within that scope optimization of data structures reduced query times by 35%.
Baxter India Manufacturing 2600 $500M India IBM IBM InfoSphere DataStage Extract, Transform, and Load (ETL) 2022 n/a
In 2022, Baxter India implemented IBM InfoSphere DataStage as a core platform in its Extract, Transform, and Load (ETL) environment. The deployment is hosted on AWS and combines IBM InfoSphere DataStage orchestration with PySpark based transformation logic to develop and run ETL and data transformation jobs that support manufacturing and operational data flows. Implementation work focuses on development of new ETL and data transformation jobs, enhancement and support of existing jobs, and technical code reviews for peer submissions moving into production. The configuration profile emphasizes DataStage job design, PySpark transformation modules, automated testing gates, and integration testing prior to production migrations. Operational scope centers on Baxter India IT resources in Bengaluru, providing ongoing technical support and root cause analysis within the ETL domain. Governance and process controls include mandatory peer code reviews, staged integration testing, and formal production migration checks, aligning data engineering, analytics, and operations functions under the Extract, Transform, and Load (ETL) practice.
Cooperative Financial Services (inc Co op Bank) Banking and Financial Services 2800 $800M United Kingdom IBM IBM InfoSphere DataStage Extract, Transform, and Load (ETL) 2007 n/a
In 2007, Cooperative Financial Services, including the Co-operative Bank, implemented IBM InfoSphere DataStage as its enterprise Extract, Transform, and Load (ETL) platform. The deployment formed a core component of an Analytical Data Integration strategy for the Co-operative Banking Group and informed high level design for elements of the proposed banking platform replacement. The implementation focused on establishing central ETL capabilities to support a retail banking core type data model and Master Data Management for customer data. IBM InfoSphere DataStage was positioned to deliver standard ETL workflows for extraction, transformation and loading, data staging and consolidation, and to operationalize data definitions created for Desktop, Finance, HR, Membership and Marketing domains. Architecturally the DataStage implementation was proposed as part of an enterprise stack alongside an ESB using Websphere Message Broker and a Teradata data warehouse, and it was incorporated into design blueprints for a Finacle re-platform for CRM, Marketing and Data Management. Operational coverage extended to customer-facing channels and systems that included Customer, ATM and Branch functions, and the ETL layer was used to support analytical integration required by acquisition-related engagements with Lloyds. Governance and process work accompanied the technical rollout, including creation of a business led data governance committee with active participation from the implementation team, a Master Data Management strategy for customer master data, and an architecture framework to ensure consistent divestment definitions for the Life Business. Senior architecture leadership acted as interim Head of IT Architecture for central functions and guided the high level design approach and roadmaps used during banking transformation planning. Practically, the Analytical Data Integration and Master Data Management artifacts produced during the programme were used to drive high level solution designs, and the case for enterprise wide adoption of IBM InfoSphere DataStage, Websphere Message Broker and Teradata was formally proposed to support the articulated data strategies.
Department of Social Services Government 2300 $366M Australia IBM IBM InfoSphere DataStage Extract, Transform, and Load (ETL) 2014 n/a
In 2014, the Department of Social Services implemented IBM InfoSphere DataStage as its Extract, Transform, and Load (ETL) platform. The deployment was scoped to support enterprise data warehouse and big data initiatives, including reporting, master and reference data management, and analytics across the agency. IBM InfoSphere DataStage was configured for enterprise ETL workflows, with formalized job design, reusable transformation routines, parallel pipeline configuration and scheduling, and centralized error handling and logging. Solution architecture included development of conceptual, logical and physical data models using ERWIN, creation of source-to-target mappings, and a metadata registry and data dictionary to support governance and lineage. The implementation integrated with core source and target systems explicitly identified in program artifacts, including Siebel CRM, Oracle Exadata, SQL Server 2014 and Hadoop, and supported downstream delivery to analytics and federation layers such as IBM federation server and Qlik Sense. Extraction patterns referenced SPARC based extraction and complementary tooling in the ingestion layer such as WhereScape Red and IBM InfoSphere Integration Server as part of the broader data flow architecture. Governance and rollout were led from a discovery driven model, using DTO Digital Service standard artifacts to produce service maps, business process documentation and high level business requirements, followed by detailed solution designs. Enterprise Architecture practices applied TOGAF to produce baseline business, data and technology architectures, perform gap analysis, and manage the technical and delivery teams through to production readiness and go live.
European Investment Bank (EIB) Banking and Financial Services 4426 $6.0B Luxembourg IBM IBM InfoSphere DataStage Extract, Transform, and Load (ETL) 2014 n/a
In 2014, European Investment Bank (EIB) deployed IBM InfoSphere DataStage as its Extract, Transform, and Load (ETL) platform to provide centralized data integration for the bank's data warehouse environment. The IBM InfoSphere DataStage estate was managed as a multi-node deployment comprising 16 DataStage servers running RedHat Linux with Oracle repositories, operated within the EIB data integration practice. Functional usage emphasized ETL job orchestration, parallel processing and metadata-aware data flows consistent with Extract, Transform, and Load (ETL) implementations. Operations included repeated version upgrades and patch cycles, and tuning for high workload servers to maintain throughput for batch and scheduled data pipelines. Integrations explicitly included Oracle repository storage for metadata and artifacts, authentication via Windows Active Directory for user and process access, and coordination with IBM product teams for licensing and support. License management and compliance follow up was handled using IBM License Metric Tool ILMT, and IBM InfoSphere DataStage was managed alongside IBM InfoSphere Business Glossary components that were installed on RedHat with Oracle repositories to support governance and shared metadata. Operational governance focused on platform lifecycle management, with scheduled patching and upgrade processes, AD based authentication controls, and ongoing vendor relationship management with IBM for licensing and support. The implementation positioned IBM InfoSphere DataStage within the EIB technology stack as the bank's core Extract, Transform, and Load (ETL) solution for enterprise data integration.
Retail 32324 $6.3B United Kingdom IBM IBM InfoSphere DataStage Extract, Transform, and Load (ETL) 2016 n/a
Insurance 4309 $2.5B United Kingdom IBM IBM InfoSphere DataStage Extract, Transform, and Load (ETL) 2011 n/a
Insurance 13700 $6.7B Brazil IBM IBM InfoSphere DataStage Extract, Transform, and Load (ETL) 2020 n/a
Communications 2400 $600M Philippines IBM IBM InfoSphere DataStage Extract, Transform, and Load (ETL) 2012 n/a
Banking and Financial Services 2700 $590M Canada IBM IBM InfoSphere DataStage Extract, Transform, and Load (ETL) 2017 n/a
Showing 1 to 10 of 15 entries

Buyer Intent: Companies Evaluating IBM InfoSphere DataStage

ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating IBM InfoSphere DataStage. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating IBM InfoSphere DataStage for Extract, Transform, and Load (ETL) include:

  1. DeskDay, a United States based Professional Services organization with 30 Employees
  2. Monte dei Paschi di Siena, a Italy based Banking and Financial Services company with 16727 Employees
  3. Bank of America, a United States based Banking and Financial Services organization with 213000 Employees

Discover Software Buyers actively Evaluating Enterprise Applications

Logo Company Industry Employees Revenue Country Evaluated
DeskDay Professional Services 30 $3M United States 2025-10-28
Monte dei Paschi di Siena Banking and Financial Services 16727 $4.7B Italy 2025-10-27
Bank of America Banking and Financial Services 213000 $101.9B United States 2025-06-18
Manufacturing 10 $1M India 2025-05-22
Manufacturing 2200 $500M United States 2025-05-16
Education 15000 $1.6B United States 2025-05-15
Professional Services 500 $58M United States 2025-05-07
Professional Services 1000 $401M United States 2025-05-05
Banking and Financial Services 4137 $1.2B Lithuania 2025-04-15
Manufacturing 24 $3M Spain 2025-04-15
FAQ - APPS RUN THE WORLD IBM InfoSphere DataStage Coverage

IBM InfoSphere DataStage is a Extract, Transform, and Load (ETL) solution from IBM.

Companies worldwide use IBM InfoSphere DataStage, from small firms to large enterprises across 21+ industries.

Organizations such as Allstate, Porto Seguro, Next, European Investment Bank (EIB) and Unieuro are recorded users of IBM InfoSphere DataStage for Extract, Transform, and Load (ETL).

Companies using IBM InfoSphere DataStage are most concentrated in Insurance, Retail and Banking and Financial Services, with adoption spanning over 21 industries.

Companies using IBM InfoSphere DataStage are most concentrated in United States, Brazil and United Kingdom, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of IBM InfoSphere DataStage across Americas, EMEA, and APAC.

Companies using IBM InfoSphere DataStage range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 0%, large organizations with 1,001-10,000 employees - 80%, and global enterprises with 10,000+ employees - 20%.

Customers of IBM InfoSphere DataStage include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.

Contact APPS RUN THE WORLD to access the full verified IBM InfoSphere DataStage customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Extract, Transform, and Load (ETL).