List of Cloudera Data Science Workbench Customers
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Since 2010, our global team of researchers has been studying Cloudera Data Science Workbench 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 Science Workbench for ML and Data Science Platforms 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 Science Workbench for ML and Data Science Platforms include: Vivo Brazil, a Brazil based Communications organisation with 330000 employees and revenues of $45.00 billion, Santander Brasil, a Brazil based Banking and Financial Services organisation with 52000 employees and revenues of $16.00 billion, Claro Brasil, a Brazil based Communications organisation with 10000 employees and revenues of $6.80 billion, Cargill Brazil, a Brazil based Consumer Packaged Goods organisation with 11000 employees and revenues of $2.50 billion, JB Financial Group Co, a South Korea based Banking and Financial Services organisation with 3620 employees and revenues of $1.49 billion and many others.
Contact us if you need a completed and verified list of companies using Cloudera Data Science Workbench, 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 Science Workbench 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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Cargill Brazil | Consumer Packaged Goods | 11000 | $2.5B | Brazil | Cloudera | Cloudera Data Science Workbench | ML and Data Science Platforms | 2020 | n/a |
In 2020 Cargill Brazil deployed Cloudera Data Science Workbench within its ML and Data Science Platforms estate to support the global Trading Data and Analytics Team based in São Paulo Brazil. The implementation targeted analytics for crop science and grain quality workflows as well as research in animal nutrition and bioinformatics, positioning Cloudera Data Science Workbench as the primary environment for algorithm development and experimentation.
The deployment used Cloudera Data Science Workbench to host interactive notebooks and scalable model training, supporting development of artificial neural network prediction models, time series forecasting, Bayesian modeling, Markov Chains and Monte Carlo simulations. Data science toolchains included PySpark and Python libraries such as scikit learn Keras TensorFlow PyMC3 Prophet and PyTorch alongside R Studio for statistical workflows, with metadata and NLP processing integrated into project workspaces.
Operational architecture integrated the workbench with the Hadoop ecosystem including Impala and Hive and consumed relational data from Oracle DB and SQL sources. Graph database capabilities were brought into model pipelines through NeptuneDB and Neo4j, and compute and storage workflows spanned Amazon AWS and Microsoft Azure with selective use of Google AutoML for comparative model experiments.
Governance and delivery relied on a CI CD pipeline built with Docker Kubernetes and Drone to standardize experiment reproducibility and promote automated model packaging and orchestration. The implementation centralized development and experimentation for trading analytics research and local São Paulo science teams while establishing repeatable build and deployment workflows for production handoff.
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Claro Brasil | Communications | 10000 | $6.8B | Brazil | Cloudera | Cloudera Data Science Workbench | ML and Data Science Platforms | 2016 | n/a |
In 2016 Claro Brasil provisioned Cloudera Data Science Workbench to establish an ML and Data Science Platforms capability for its Data Science and Analytics organization. The deployment centralized model development and feature engineering workflows to support business units focused on customer analytics and data driven product initiatives.
Cloudera Data Science Workbench was configured to support feature store development, staging areas, and end to end data pipelines with lifecycle controls for feature creation and refresh. Engineers implemented automated ingestion and update processes for datasets, scheduled report generation with automatic email distribution, and qualitative and quantitative monitoring of data and feature updates. The implementation emphasized reproducible experiment workspaces and operationalization paths for production model scoring within the Cloudera Data Science Workbench environment.
The implementation integrated Cloudera Data Science Workbench with the broader Hadoop ecosystem and included migration of relational databases into Hadoop based storage and processing while retaining source connectivity to relational systems such as Oracle. Operational tooling leveraged HUE and Unix shell scripting for batch orchestration and data validation, and data lineage capture was instrumented across staging and production zones. Architecture and solution design decisions were driven by business data requirements and validated through formal homologation processes.
Governance practices established a feature dictionary, explicit data lineage mapping, and monitoring frameworks to track data quality and feature freshness across the ML lifecycle. Claro Brasil Cloudera Data Science Workbench ML and Data Science Platforms supported the Data Science and Analytics business function by institutionalizing data governance and enabling business teams to develop new products for data monetization.
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JB Financial Group Co | Banking and Financial Services | 3620 | $1.5B | South Korea | Cloudera | Cloudera Data Science Workbench | ML and Data Science Platforms | 2018 | n/a |
In 2018, JB Financial Group Co implemented Cloudera Data Science Workbench as part of its ML and Data Science Platforms initiative. The deployment targeted group level analytics capabilities and established a standardized data science environment across two subsidiary banks and one capital entity within the holding company.
Cloudera Data Science Workbench was configured to provide collaborative notebook environments, reproducible model training, and containerized runtimes for experiment orchestration and model packaging. The implementation emphasized Spark based scalable compute for large scale feature engineering and batch model training, while enabling JupyterLab style development workflows and model lifecycle management.
The deployment integrated Cloudera Data Platform components with Apache Hadoop storage, Apache NiFi for ingestion, Spark for distributed processing, Tableau for visualization, and Docker for runtime consistency. These integrations fed unified data lakes built for the two banks and the capital unit, and the data lake construction was the first among Korean financial holding companies, with explicit schema definitions for customer behaviour data logs to support analytics and scoring.
Operational governance centralized a data science organization, role based access controls, and an internal curriculum for upskilling data experts, led by the Head of Data Team. Use cases executed on Cloudera Data Science Workbench included market response modeling, customer clustering using HDBSCAN DenseClus and KMeans on Spark, customer behaviour analysis and remarketing, and promotion predictive models using Random Forest RFECV and Logistic Regression, which produced a 4 to 5 times increase in response rate and a 3 times increase in conversion rate according to internal reporting.
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Banking and Financial Services | 52000 | $16.0B | Brazil | Cloudera | Cloudera Data Science Workbench | ML and Data Science Platforms | 2019 | n/a |
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Communications | 330000 | $45.0B | Brazil | Cloudera | Cloudera Data Science Workbench | ML and Data Science Platforms | 2022 | n/a |
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