Scale ML workloads to petabytes with HPE Machine Learning Data Management Software

[TechExperts]

Discover HPE Machine Learning Data Management Software, a new data pipelining and data versioning solution built on open-source tool Pachyderm, and learn how it empowers data engineering teams.  

The key to great machine learning (ML) models is the quality and volume of data available. Data preparation combined with petabyte size data sets are mandatory. Unfortunately, data preparation is the most time-consuming stage of the ML lifecyle, with data scientists spending over 20% of their time at this stage rather than building models. In addition, data sets are far larger than was originally curated on a laptop or in a Proof of Concept, delaying iterations and time to production.

Introducing HPE Machine Learning Data Management Software, a data pipelining and data versioning solution built on open source Pachyderm. It empowers data engineering teams to automate data processing and ML workflows reducing processing cycles from weeks to hours. Unlike competitive products, its unique architecture is cost‑effective at scaling and enabling complex data transformations with any type of data (unstructured and structured). A flexible solution, it allows engineers to use the language or frameworks that best suited for the job and runs in the cloud and on-premises.

HPE Machine Learning Data Management Software is part of an end-to-end HPE AI software stack that covers every stage of the ML lifecycle from data preparation, experimentation, training, deployment and monitoring. This solution is tool agnostic and can be used to interconnect to any ML ecosystem tool such as HPE Machine Learning Development Environment for training and deployment

Key benefits of the solution

Scalability. The software scales easily to petabytes of data and millions of records using autoscaling and parallel processing, enabling frequent model iterations and faster data processing.

Reproducibility. Every output data set, model, or artifact is easily replicated and traced. Users can meet compliance, expedite debugging, or roll back data sets, pipelines, or code when needed.

Flexibility. The solution is fully cloud native, enabling data scientists and engineers to choose the tools and technologies that best fit their needs without being locked into a specific framework or vendor.

Key features driving the benefits

Data versioning “and” data lineage. The solution automatically captures unchangeable versions of data processed and the code used to perform the transformations and the pipeline runs. This creates auditable data lineage—no other solution can guarantee reproducibility this way.

Proprietary parallelization. The solution can programmatically shard or chunk data without requiring users to change their code. This differentiating feature sets this solution apart at processing large amounts of unstructured data rapidly, further enabling scale.

Incremental processing. The solution calculates what data needs to be processed by deduplicating old data and identifying new or changed data. Complex runs with large data sets can be completed rapidly and require less storage and compute resources.

Intelligently triggered pipelines. A data‑centric approach helps ensure pipelines start by detecting changes to data (additions and modifications), code, or pipeline steps. Models can constantly be refreshed without worries about stale data.

Data management "and" pipelines. The solution utilizes reusable, modular components, and GIT-like concepts for managing both data and pipelines on a common sharable platform. Pipelines are stored as code along with data to accelerate collaboration.

Learn more

For data and ML engineers working with large and complex datasets, HPE Machine Learning Data Management Software is a flexible data management solution that automates and quickly scales data pipelines. Unlike competing MLOps solutions, HPE Machine Learning Data Management software combines data pipelines with versioning. Come see the demo at Discover 2023  or schedule an online demo tailored to your specific needs.

For more information about HPE Machine Learning Data Management Software, please visit the webpage.

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Meet Bhavani Rao, HPE AI Product Marketing Manager

Bhavani Rao is a Product Marketing Manager, responsible for product messaging and positioning at HPE AI solutions. He has a diverse background that spans MLOps, DevOps, CI/CD, relational, and NoSQL databases. A recent convert to the potential of AI/ML, Bhavani is passionate about technology and how it can be leveraged to solve customer problems. Throughout his career, Bhavani has promoted these learnings and best practices in numerous industry gatherings and publications.