Research Library

Powered by

All Research Sponsored By:Ascension Labs


    Data teams are suffering from huge demand for data products and limited team resources, with 96% of data teams reporting they are operating at or over capacity according to the 2021 DataAware Pulse Survey. Read on to learn how data teams can tackle some of their most difficult headaches via automation, replatforming, and other approaches.

  • 2021 DataAware Pulse Survey

    According to’s 2021 DataAware Pulse Survey, 96% of data professionals say they are at or over capacity. View the full results of their survey here to learn more about the work capacity and priorities of today’s data teams and to see where your company falls in this mix.

  • Cool Vendors in Enterprise AI Operationalization and Engineering

    Access this Gartner report to discover why it’s necessary to evaluate new vendors when building the data foundations for your AI projects and initiatives, learn how emerging trends show that infrastructure and platform decisions will come to be dominated by AI considerations, and discover the value of open-source technologies in this process.

  • Case Study: A Deep Dive Into Data Orchestration at Harry's with Ascend

    Explore this resource to learn how Ascend helped Harry’s create flexible, automated data pipelines and more easily integrate data from S3 and other sources into their Looker BI environment.

  • An Assessment of Pipeline Orchestration Approaches

    Download this white paper to learn why, instead of using expensive and brittle workflow automation systems, opting to adopt dataflow automation can lower design and maintenance costs while improving the quality and reliability of data pipelines

  • Tech Talk | Intelligent Orchestration: The Key to Declarative Data Pipelines

    What if you could adopt a data pipelining approach that results in 95% less code, 10x faster build times, automated maintenance, and more efficient pipelines? Explore this examination to learn how intelligent orchestration creates declarative pipelines with ease, improving your data integration abilities.

  • How HNI Drives Manufacturing digital Transformation with Data Pipelines

    Read this short case study to learn how Ascend’s data platform helped HNI dramatically accelerate their data pipeline creation, even in the midst of migrating to Azure, allowing them to quickly ingest ERP data and transform it into data ready for analytics and other crucial business tasks.

  • How To: Getting Started with the Ascend Platform and Creating Your First Dataflow

    Access this solution walkthrough to learn how the Unified Data Engineering Platform works and discover how easily you can create dataflows, query, and manipulate information stored in an AWS S3 environment.

  • Top 6 List - Why Looker Users Love Ascend

    Ascend’s Unified Data Engineering Platform enables businesses to infuse their BI programs with a wealth of data from all kinds of sources, including IoT and streaming data. Inside, explore the top 6 reasons Looker users love Ascend, including pipeline visualizations that simplify complex queries, better data quality, and more.

  • Supercharging Time to Analysis at Harry’s

    Read this short case study discover how Harry’s used to simplify new analytics processes with a low-code sandbox environment, speed the time to ingest, transform, and pipe data into Looker by 10x, and unify data in an omni-channel view.

Bitpipe Definitions: A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Other Research Library Copyright © 1998-2022 Bitpipe, Inc. All Rights Reserved.

Designated trademarks and brands are the property of their respective owners.

Use of this web site constitutes acceptance of the Bitpipe Terms and Conditions and Privacy Policy.

Cookie Preferences