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Ascend Data Delivery

Data Delivery

Seamlessly deliver processed data to BI, analytics, machine learning, and AI tools​.​

Start Delivering

Get Data Where It Needs to Go, When It Needs To Be There, With the Ascend Data Automation Cloud​

Ascend Deliver_Notebooks

Native Notebook Connectors​

Native BI & Data Visualization Access​

Multi-Point Data Delivery

End-to-End Schema Management

				
					import pyspark
from pyspark.sql import SparkSession

spark = SparkSession.builder \
    .master("local[*]") \
    .appName("test_sdl") \
    .config("spark.jars.packages", "org.apache.hadoop:hadoop-aws:3.2.0,com.amazonaws:aws-java-sdk-bundle:1.11.375") \
    .getOrCreate()

sc = spark.sparkContext

sc._jsc.hadoopConfiguration().set("fs.s3a.impl", "org.apache.hadoop.fs.s3a.S3AFileSystem")
sc._jsc.hadoopConfiguration().set("fs.s3a.endpoint", "https://s3.ascend.io")
sc._jsc.hadoopConfiguration().set("fs.s3a.access.key", access_id)
sc._jsc.hadoopConfiguration().set("fs.s3a.secret.key", secret_key)

df = spark.read.parquet('s3a://trial/Getting_Started_with_Ascend/_DF__Clusters_w__Solar')

File-based Access​

Record APIs and SDKs​

Ascend Transform_Full Featured SDK

From Our Customers

"What I just did in an hour… would have taken me weeks. This is really cool. I don’t need to worry about data coming through the pipeline anymore. New data will show up and get pushed where it needs to go."
Francis ChanDirector of Engineering, DivX
"Ascend's declarative engine is a game-changer for our team's productivity and its flex-code approach strikes the right balance, offering the flexibility we need—ranging from our simple SQL transforms to our most complex recursive PySpark transforms."
Remi PaulinData Architect, PrestaShop
"The Ascend Platform is a phenomenal application for data engineering in companies like Be Power, which benefits from an end-to-end platform like Ascend instead of investing in custom open source solutions that take massive amounts of time and effort to build and operate. I’ve searched for something like Ascend for a long time.”
Paolo EspostoChief Data Officer, Be Power
"We no longer look at individual data sources to pull into Ascend, we look at our entire enterprise—customer-facing and internal—and decide how to pull that into Ascend and then feed it into other systems for visualizations. Ascend is the gateway that processes all our data.”
Ariscielle NovicioSVP & Head of Technology, New York Post
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Resources

The New Data Scale Challenge
From struggling with data volume and infrastructures to scaling data team capacity—what is the answer to increasing bandwidth?
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Whitepaper
DataAware Podcast
With a variety of guests from all facets of data engineering and associated teams, episodes look in-depth at the role of data engineering and data teams, trends, best (and worst) practices, real world use cases, and more.
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PODCAST
A Deep Dive Into Data Orchestration at Harry's
Learn how the Harry's data science team expedited ingesting, transforming, and delivering retail data feeds into a new, robust shared data model.
Watch Now
Video

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