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Basic Info
Ascend.io, the Data Pipeline Automation Platform, provides the most advanced automation for building intelligent data pipelines in the cloud. Ascend unifies data engineering’s core capabilities—ingestion, transformation, delivery, orchestration, and observability—into a single platform so teams deliver 10X faster. Engineering productivity is a top priority, and with Ascend’s DataAwareTM intelligence, data teams no longer spend hours orchestrating brittle data workloads and instead rely on advanced automation to optimize the entire data lifecycle.
Ascend helps gridlocked teams break through constraints to build, manage and optimize the increasing number of data workloads with:
- Data Ingestion: Ascend gives you the power to connect to popular data sources with pre-built connectors, or create your own with Ascend’s flex-code interface.
- Data Transformation: Normalize, enrich, filter, aggregate, and otherwise transform data in SQL, Python, Scala or Java. Drive Ascend programmatically with our Python SDK or build interactively through our low-code visual interface.
- Data Delivery: Reverse ETL any data set to any destination including popular databases, blob stores, and warehouses whether on-premises or cross-cloud.
- Data Orchestration: Ascend’s DataAware automation is an industry first to incrementally propagate data across data pipelines, checkpoint data at each transform to guarantee the data integrity.
- Data Observability: Visualize activity across your pipelines, understand costs, trace lineage, monitor events, and more.
Book a demo today: https://www.ascend.io/demo/
Why work with us
- Cost Savings: Ascend runs in your infrastructure on almost 100% Spot / Preemptible instances, greatly reducing the cost of your big data infrastructure.
- Democratize Data Engineering: enable more of your team to build advanced data pipelines that connect with the tools they already know and love.
- Build up to 10x faster: with data pipelines requiring 95% less code and integrated features for interactive design, Ascend provides the fastest way of going from prototype to production.
- Automated Maintainance: Ascend's DataAwareTM system tracks all changes to code and data, offloading the vast majority of traditional data engineering maintenance activities.
Clients (12)
HNI
Consumer Discretionary
HNI Corporation is one of the largest office furniture manufacturers in the world in regard to revenues resulting from office segment sales. read more
Mayvenn
Consumer Discretionary
Quality virgin human hair & extensions trusted & recommended by 100,000 stylists, and backed by the only 30-day return policy in the industry. Try Mayvenn hair today! read more
Harry's
Consumer Discretionary
Harry's is an American company that manufactures and sells shaving equipment and men's personal care products via online and retail channels. read more
Afresh
Internet Software & Services
Afresh is building the next-generation food supply chain powered by AI, reducing waste and making fresh, healthy food accessible to all. read more
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Projects or Case studies (4)
Reading from a Single Source of Data Truth with the New York Post
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Understanding advertising information as well as how readers interact with digital content is crucial to the growth and success of the New York Post and its associated online properties. Already hyper-focused on building robust data pipelines to feed insight and analytics teams, the upcoming crackdown from Google on third-party cookie data in the Chrome browser accelerated the need to drive more data-driven personalization and engagement across the New York Post sites. The team at the New York Post needed to quickly create a scalable way to build data pipelines that power critical insights and changes for how readers and subscribers interact with digital content. As the Ascend Unified Data Engineering Platform was introduced to the team, which is composed of software engineers and project managers, they quickly realized that deploying an ETL platform using Ascend would dramatically accelerate their time to market and ability to continuously deliver new data streams.
Speeding Analytics at Harry's
September 2020 - September 2021
Learn how Harry’s uses Ascend.io to rapidly ingest and transform new, varied data sources for analysis in minutes—not weeks.
Digital Transformation at HNI
January 2020 - September 2021
Learn how HNI Corp Drives Digital Transformation with Data Pipelines using Ascend.io
Styling Data Pipelines for Analytics Success at Mayvenn
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Mayvenn, with a mission to provide high-quality beauty products with an unparalleled shopping experience, uses world-class technology to empower beauty professionals by enabling them to grow their business, while providing them and their clients with exceptional customer support—all backed by a robust and growing data analytics backbone. Mayvenn built their business on providing superior experiences for their stylist network as well as the clients those stylists serve, the basis of which relies on extensive data pipelines that covered a variety of customer and marketing data. With increasing, disparate data streams, the Mayvenn analytics team set out to find a data orchestration solution that enabled them to handle the vast majority of data ingest and transformations while also delivering the ability to rapidly iterate on ETL without requiring help from the engineering team. This is what led the Mayvenn team to the Ascend Unified Data Engineering Platform.