List of Cloudera Data Warehouse Customers
Cloudera
395 Page Mill Road,
Palo Alto, 94306, CA,
United States
Palo Alto, 94306, CA,
United States
1 165-036-0488
Professional Services
2728
$783M
Since 2010, our global team of researchers has been studying Cloudera Data Warehouse 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 Cloudera Data Warehouse for Data Warehouse 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 Cloudera Data Warehouse for Data Warehouse include: Woolworths Group, a Australia based Retail organisation with 201413 employees and revenues of $44.36 billion, IQVIA, a United States based Professional Services organisation with 93000 employees and revenues of $16.31 billion, Regions Bank, a United States based Banking and Financial Services organisation with 19969 employees and revenues of $7.53 billion, Safra Bank Brazil, a Brazil based Banking and Financial Services organisation with 30000 employees and revenues of $4.00 billion, Bank Danamon, a Indonesia based Banking and Financial Services organisation with 22794 employees and revenues of $1.14 billion and many others.
Contact us if you need a completed and verified list of companies using Cloudera Data Warehouse, 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 Cloudera Data Warehouse 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 |
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Bank Danamon | Banking and Financial Services | 22794 | $1.1B | Indonesia | Cloudera | Cloudera Data Warehouse | Data Warehouse | 2020 | n/a |
In 2020, Bank Danamon implemented Cloudera Data Warehouse as part of a broader modern data platform to consolidate customer data and enable real-time analytics. The deployment targeted Data Warehouse workloads and was positioned to support enterprise customer marketing, fraud detection, and anti-money laundering functions across the bank.
The implementation incorporated Cloudera Data Warehouse alongside core Cloudera components such as Apache HBase, Apache Impala, Apache Kafka, Apache Sentry, Apache Spark, and Cloudera Navigator to provide storage, query, streaming, security, and governance capabilities. The bank paired the platform with the Kogentix Automated Machine Learning Platform to test, train, validate, and monitor machine learning models, enabling descriptive through prescriptive analytic workflows and ongoing model performance analysis.
Operationally the platform ingests and analyzes more than one terabyte of structured and unstructured data daily, both in batch and via live streaming, integrating sources from about 50 different systems. Data sources include transactional systems, product systems, internet and mobile banking logs, credit card feeds, customer care voice, digital logs, social media, socioeconomic inputs, and third-party data, supporting real-time recommendation engines, business intelligence, fraud detection, and AML applications.
Governance and process changes emphasize model lifecycle management and real-time operationalization, with capabilities to observe interaction performance, self-correct based on feedback, and send real-time alerts to customers for potential fraud. The solution also addressed data protection and compliance management through centralized metadata and governance provided by Cloudera Navigator and security controls enforced by Apache Sentry.
Explicit results reported by Bank Danamon from the Cloudera Data Warehouse implementation include a greater than 300 percent increase in marketing conversion rates, improved customer retention, a 30 percent reduction in the number of fraud incidents, reduced marketing costs, identification of new fraud patterns, and a lower capital expenditure per terabyte compared to traditional data management mechanisms.
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IQVIA | Professional Services | 93000 | $16.3B | United States | Cloudera | Cloudera Data Warehouse | Data Warehouse | 2020 | n/a |
In 2020, IQVIA implemented Cloudera Data Warehouse as a Data Warehouse solution to consolidate and analyze its global life sciences datasets. IQVIA is a global provider of analytics and contract research services to the life sciences industry, and the deployment was driven by the need to bring analytics to large, distributed data holdings for faster discovery and operational decision making.
The Cloudera Data Warehouse implementation uses core Cloudera components including Apache Kudu, Apache Impala, and Apache Spark, alongside Cloudera Data Science Workbench and Cloudera Navigator to enable self-service BI, data science, and data engineering workflows. The platform supports development of predictive algorithms using R, Python, and Scala, and enables users to run interactive, high performance queries and machine learning model development without moving data out of the platform.
Operationally the initiative created a global multi-tenant data lake, consolidating more than two petabytes of data from roughly 250 source data warehouses including Oracle, Netezza, and Teradata systems. IQVIA partitioned the platform into four data tenants, a U.S. data lake, a Spain data lake, a France data lake, and a Japan data lake, and 70 internal teams with approximately 1,500 to 2,000 users access the environment. The platform ingests diverse data sources such as prescription data, electronic medical records, claims, sales, social data, and genomic data, and the environment has supported tens of hundreds of thousands of queries using BI tools such as Tableau and MicroStrategy.
Governance and security were implemented as a shared data experience with centralized encryption, governance controls, and role based access management, enabling global administrative oversight while preserving tenant isolation. IQVIA also architected the environment for a hybrid cloud future, using Cloudera Director to provision sister tenants in public cloud environments when a meeting place for client data and IQVIA data is required.
The deployment produced explicit operational outcomes documented by IQVIA, including accelerating query responses from days to seconds and improving the ability to predict if a patient is eligible for a clinical trial before they are symptomatic by four times. The platform also reduced the time to identify qualified clinical trial participants from weeks or months to seconds and minutes, enabling faster research cycles and more rapid development of new treatments.
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Regions Bank | Banking and Financial Services | 19969 | $7.5B | United States | Cloudera | Cloudera Data Warehouse | Data Warehouse | 2020 | n/a |
In 2020, Regions Bank implemented Cloudera Data Warehouse as part of a broader enterprise data science platform to centralize analytics for banking and wealth management use cases. The deployment addressed the need to unify fragmented data sources and enable scalable modelOps and data product delivery for corporate relationship managers, commercial teams, private wealth advisors, fraud detection teams, and centralized analytics groups across the banks US branch and ATM network.
The implementation used Cloudera Data Platform components including Cloudera Data Warehouse, CDP Private Cloud Base, Cloudera Data Science Workbench, Cloudera SDX, and Cloudera Stream Processing and Analytics to create a hybrid cloud capable data lake and analytic stack. Regions configured real-time ingestion pipelines and streaming features, and built analytics workflows that leverage Spark for enrichment and processing, Hive and Impala for deep data analytics, and Cloudera Data Science Workbench for model development and exploration.
Integrations and operational architecture focused on streaming ingestion with Kafka, Spark processing for large transaction volumes, and governed analytic serving layers, with Cloudera Professional Services supporting the in-place CDP Private Cloud upgrade to minimize downtime. Regions also worked with IBM on advanced analytics methodologies, and designed the environment to support containerized isolated workloads and future cloud bursting for ad hoc data science compute.
Governance and process changes included centralizing a data lake, instituting a data governance framework under Cloudera SDX for consistent security and metadata management, and standing up an analytics Center of Excellence to standardize model deployment and lifecycle practices. The platform consolidated data assets into a single security model and a unified data pipeline, enabling broader reuse of data and models by business-facing teams.
Explicit results reported from the deployment include improved customer conversations enabled by data products, over $10 million per year in retention savings, a production ML risk scoring model that improved fraud capture by 95 percent, a 30 percent decrease in false positive alerts, a 50 percent reduction in average daily dollar losses, and more than 10 percent cloud cost savings as Regions shifts workloads to burstable hybrid cloud patterns.
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Safra Bank Brazil | Banking and Financial Services | 30000 | $4.0B | Brazil | Cloudera | Cloudera Data Warehouse | Data Warehouse | 2021 | n/a |
In 2021 Safra Bank Brazil implemented Cloudera Data Warehouse as part of a corporate Big Data consolidation for Safrapay and the broader bank analytics program, classifying the deployment under the Data Warehouse category. The initiative ran in parallel with platform upgrades, notably migrations from Cloudera Data Platform 6.3 OnPremise toward Cloudera Data Platform 7.1 Cloud, with cloud-hosted CDP components providing the foundation for the Cloudera Data Warehouse deployment and analytics workload consolidation.
The implementation centered on data ingestion, streaming, and analytical reporting capabilities. Engineers used Apache Spark with Python for batch ingest from multiple OnPremise sources, and implemented streaming pipelines to synchronize transaction and fraud signals, leveraging Kafka and Spark Streaming as part of the data pipeline stack. Cloudera Data Warehouse hosted analytical datasets consumed by PowerBI corporate dashboards, and development practices included unit and integration testing for backend services with reported high coverage.
Operational integrations were explicit to Safrapay systems, including the Safrapay Authorizer and an anti-fraud engine Feedzai, plus ECommerce gateway feeds used by sales indicators projects. The scope covered the Corporate Big Data area and Safrapay product analytics, servicing Commercial and Product team decision workflows through implemented dashboards and monitoring capabilities. Migration work included refactoring older projects with obsolete technologies to more robust platform components, coordinated with Architecture and Infrastructure teams.
Governance and rollout followed an agile operating model with technical leadership and cross-functional squads. Technical leads managed teams sized from three to ten engineers, coordinating Data Engineering, Backend, Frontend, UX, and QA disciplines, working with Product Owners and Scrum Masters to deliver the Meu Desempenho Safrapay sales indicators and streaming integrations. The Cloudera Data Warehouse implementation therefore served as the central analytical layer, enabling consolidated reporting and real-time feeds for fraud and commerce monitoring used in decision making by business stakeholders.
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Sefaz MT | Government | 1500 | $180M | Brazil | Cloudera | Cloudera Data Warehouse | Data Warehouse | 2014 | n/a |
In 2014 Sefaz MT implemented Cloudera Data Warehouse as a Data Warehouse solution to manage high volume tax and transport datasets generated across state systems. The deployment established a scalable analytics platform to support tax administration use cases in the government domain, with initial operational focus in Cuiabá and surrounding regions of Mato Grosso, Brazil.
Cloudera Data Warehouse was configured to provide core functional modules for data ingestion, batch data loads, SQL-based warehousing, and ad hoc analytics. Implementation work included ETL and data load pipelines to normalize Electronic Invoice NFe and NFCe records, Tax Bookkeeping EFD files, and Bill of Transport CTE data, plus interactive SQL access for analysts through Impala and Hive metadata services.
The architecture centered on the Cloudera CDH distribution, with Apache Hive used for structured dataset management and Impala for low-latency interactive queries. Source integrations explicitly included Oracle Exadata for relational extracts, Microsoft Reporting Services for managerial report delivery, and analytics environments such as Jupyter Notebook with Python for investigative and exploratory analysis.
Operational governance aligned the platform to tax analysis and investigative workflows, with IT analysts and analytics teams producing scheduled data loads, reports, and investigative notebooks to detect taxpayer anomalies and support managerial views. Cloudera Data Warehouse served as the central Data Warehouse for analytical workloads tied to state tax enforcement and related legal projects, with development and operational practices implemented to sustain ETL scheduling, query performance, and analytical collaboration.
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Professional Services | 7822 | $567M | Brazil | Cloudera | Cloudera Data Warehouse | Data Warehouse | 2019 | n/a |
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Retail | 201413 | $44.4B | Australia | Cloudera | Cloudera Data Warehouse | Data Warehouse | 2015 | n/a |
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Buyer Intent: Companies Evaluating Cloudera Data Warehouse
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FAQ - APPS RUN THE WORLD Cloudera Data Warehouse Coverage
Cloudera Data Warehouse is a Data Warehouse solution from Cloudera.
Companies worldwide use Cloudera Data Warehouse, from small firms to large enterprises across 21+ industries.
Organizations such as Woolworths Group, IQVIA, Regions Bank, Safra Bank Brazil and Bank Danamon are recorded users of
Cloudera Data Warehouse for Data Warehouse.
Companies using Cloudera Data Warehouse are most concentrated in Retail, Professional Services and Banking and Financial Services, with adoption spanning over 21 industries.
Companies using Cloudera Data Warehouse are most concentrated in Australia, United States and Brazil, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Cloudera Data Warehouse across Americas, EMEA, and APAC.
Companies using Cloudera Data Warehouse 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 - 28.57%, and global enterprises with 10,000+ employees - 71.43%.
Customers of Cloudera Data Warehouse 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 Cloudera Data Warehouse customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Data Warehouse.