Databricks Unified Data Analytics on AWS

Databricks Competencies

  • Machine Learning Competency
  • Data & Analytics Competency
  • Life Sciences Competency
  • Retail Competency
  • Public Sector Partner

Databricks Unified Data Analytics on AWS

Unified data analytics platform for accelerating innovation across data science,
data engineering, and business analytics, integrated with your AWS infrastructure.

Data

One reliable and scalable data lake
for all analytics

People

One collaborative workspace for data and ML teams

AI

One platform for data science, ML, and analytics


Amazon Redshift

Databricks can read data securely from Redshift and integrate it with other datasets. With Delta Lake, Databricks can make that data into simplified and reliable data pipelines using optimized cluster resources. Data can then be used for machine learning in Databricks, or put back into Redshift for data warehouse workloads.

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AWS Glue Integration

The AWS Glue service is an Apache compatible Hive serverless metastore which allows you to easily share table metadata across AWS services, applications, or AWS accounts.

This provides several concrete benefits:

  • Simplifies manageability by using the same AWS Glue catalog across multiple Databricks workspaces.
  • Simplifies integrated security by using Identity and Access Management Credential Passthrough for metadata in AWS Glue. Refer to the Databricks blog introducing Databricks AWS IAM Credential Passthrough for a detailed explanation.
  • Provides easier access to metadata across the Amazon services and access to data catalogued in AWS Glue.

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Amazon SageMaker

Databricks is integrated with Amazon SageMaker using MLflow to enable distribution of machine learning models. Databricks is used to build collaborative ML models and train them at scale. The deployment enables real-time model serving and REST API integration.

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Automated, High Scale Data Pipelines

Created automated data pipelines at scale that minimize cost with features such as auto-clustering and spot pricing. Using Delta Lake, you can scale up to the largest datasets, with high velocity data providing constant updates, instantly available for analytics.

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Lisez ce livre électronique et découvrez comment unifier le big data et l'IA dans le secteur des services financiers

Quickly prepare clean data at massive scale, and continuously train and deploy state-of-the-art ML models for best-in-class AI applications. Common use cases include:

  • Risk, Fraud, Intrusion Detection & Prevention
  • Customer 360 Engagements , Ad Targeting
  • Predictive Maintenance, SCM Seasonal Costing
  • Sentiment & Customer Churn Analysis
  • Security Compliance & Intelligence

 

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Santé et sciences du vivant

Recentrer les systèmes de soins sur les patients grâce aux unified analytics

Built by the original creators of Apache SparkTM, the Databricks Unified Data Analytics Platform enables data processing and machine learning at massive scale — empowering healthcare organizations to drive innovations in care while reducing costs.

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Vente au détail

Suscitez l'engagement des consommateurs à chaque interaction

Exploitez tout le potentiel du big data et de l'IA pour mieux connaître vos clients et leur offrir des expériences d'achat personnalisées qui les captivent sur tous les canaux de distribution

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Enabling AWS Single Sign-On (SSO) Service Integration with Databricks Control Plane

Databricks integrates with Amazon security and single sign-on, making it easy to roll out across your organization. Users can access Databricks with their corporate credentials using AWS SSO. This delivers a better user experience without the need for managing separate sets of credentials.

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Témoignage client

Digital Turbine

“We needed to be able to deliver fast query responses to enable internal
business analysts. Now they are using Notebooks to query Delta Lake
directly.” – Daniel Ferrante, Director of Platform Engineering

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Étude de cas client

Quby

“Databricks, through the power of Delta Lake and Structured Streaming, allows us to deliver alerts to our product’s users with a very limited latency, so they’re able to react to problems within their home before it affects their comfort levels.” – Steven Galsworthy, Head of Data Science at Quby

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Webinaire

ShopRunner

ShopRunner ingests over 1TB a day to drive online retail merchandise recommendations. They use Databricks for ingesting data, as well as for running their machine learning jobs. With the Databricks ML runtime that includes machine learning frameworks like TensorFlow, ShopRunner is making recommendations based up physical item appearance.

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Conde Nast customer testomonial

Témoignage client

Conde Naste

“Databricks enables us to decide in real time, without having to commit until we know this is a viable solution for our business.”

Paul Fryzel, Conde Nast

Edmunds customer testimonial

Témoignage client

Showtime

“Our pipeline has gone from over 24 hours to refresh to less then 4 hours using Databricks.”

Josh McNutt, Showtime

Edmunds customer testimonial

Témoignage client

Edmunds

“Databricks democratizes data engineering and machine learning, and enables us to instill data driving principles.”

Gregory Rokita, Edmunds

Health Direct customer testimonial

Témoignage client

Health Direct

“Databricks enabled us to hit the time to market and analytics and operational uplift to meet the new demands of the healthcare sector.”

Peter James, Health Direct

Étude de cas client

People.AI

“We were looking for a leader to partner with on analytics infrastructure. With Databricks we can focus our time and resources on innovating new solutions that drive our business.” – John Wulf, Principal Engineer

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FIS global customer testimonial

Témoignage client

FIS Global

“Databricks enables you to unlock your imagination.”

Aaron Colcord, FIS Global