Professional Services - Databricks

Global Professional Services

Delivering Rapid Success on projects with world-class Data Engineering, Data Science and Project Management expertise

Our Advisory Services ensure Project Success

Industry Best Practices

Best practices from 400+ enterprise customer use-cases including: Streaming, ML (IoT failure prediction), Graph (fraud detection), many others.

Spark Roadmap Access & Influence

Foresight into project, product, and industry directions (e.g. upcoming API or architecture changes).

Overcome Bugs & Performance Blockers

Direct line of communication with Spark Committers. Can turn around bug & performance patches in hours or days, not months.

Service Packages

The Databricks Professional Services Jumpstart package enables new customers to quickly and effectively jumpstart their project implementation with targeted assistance from highly trained and certified Databricks Consultants.

Services Jumpstart

Upon completion of this 1, 2 or 3 week engagement, you will have a working data pipeline utilizing best practices, which can be leveraged as an example for implementing additional pipelines.

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Machine Learning Jumpstart

This 10 day engagement will focus on machine learning training, project planning, and use case review sessions with high-level architecture guidance and recommendations on best practices.

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Custom Statement of Work

Our Professional Services Experts have proven success in delivering full life-cycle projects to meet complex, very specific and targeted requirements. Contact us so we can develop a customized Statement of Work for you.

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Resident Solutions Architects | Data Engineers | Data Scientists

Highly Experienced & Technical resources with strong Leadership & Consulting skills

Databricks & Spark Experts

  • > 10 years of experience
  • Strong big data background
  • Hands-on implementation skills

Project Planning & Execution

  • Assist with Design & Architecture
  • Help align project to platform capabilities
  • Provide inputs to project timelines and resource needs

Implementation & Production planning

  • Architect solutions for scalability
  • Assist with prototype development
  • Address DevOps integration requirements

Assist in implementing a COE

  • Develop common standards & frameworks
  • Be available as a resource for multiple teams
  • Facilitate interactions with other Databricks teams

Profile of a Principal Consultant

PhD. Computer Science and Mathematics, B.Eng. Software Engineering Certified Databricks developer for Apache Spark 2.0

  • 5+ years Software Engineer
  • 9+ years Data Scientist and Data engineer
  • 4+ years Spark/Scala in ML applications and ETLs
  • 5+ years AWS

Past projects include:

  • Recommendation engine (Lufthansa)
  • IOT project (HP)
  • ETL and analytics for Genomic data (Regeneron)

Profile of a Lead Data Scientist

M.S. in Computer Science from UCLA, focus on Distributed Machine Learning

Certified Databricks trainer

  • Intro to Apache Spark
  • Scalable Machine Learning
  • Spark Performance Tuning
  • Deep Learning courses

Past projects include:

  • Convert existing pandas/scikit-learn/R workloads over to Spark and SparkML
    • Significant time reductions: some greater than 100x!
  • Develop customizable NLP pipeline
  • Chatbot sentiment analysis
  • Predict hospital demand/resource allocation

Profile of a Resident Solutions Architect

Databricks Spark developer, MS Computer Science

3+ years of Spark development experience; worked on big data projects at Microsoft, MapR and Teradata, prior experience with Hadoop as well as traditional databases

Hands-on design and development experience in Scala & Python; 3 years of building and maintaining data pipelines processing 100s of GBs per day

Past projects include:

  • Migration of SAS financial application to Databricks, ETL and performance tuning
  • Built a Social listening platform for an Entertainment company using Flume/Hive
  • Built a Kafka/Storm based streaming pipeline for a finance company

Love from our Clients

Benefits of Engaging Databricks

Engagement Timeline

Multiple skills: Spark & Databricks available in a single resource
Aligned with our customer’s goal to make project successful
Ability to bring in additional and unique expertise as needed
Backed by industry-leading engineers and technical resources during the project
Intensive transfer of knowledge and best practices, focused on the unique characteristics of your implementation and project goals
Reduced implementation times

Let’s get started

Contact us for more information or to stay informed about our professional services.

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Services Jumpstart

Overview

The Databricks Jumpstart Packages are service offerings to help our customers accelerate their project timelines and apply best practices by working closely with industry leading consultants from the Databricks Professional Services team.

Scope of work

The engagement will focus on general onboarding, project planning and use case review sessions with high-level architecture guidance and recommendations on best practices

  • Setup environment to support development, testing and production rollout
  • Define and design a reference architecture that is scalable, has high levels of automation, supports large throughput of data and exploits the capabilities of the Databricks platform to the maximum extent
  • Assist with development of a reference implementation to act as a template for further development
  • Evaluate and make recommendations to support DevOps automation
  • Assist with project planning, kickoff and onboarding of users
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Machine Learning Jumpstart

Overview

The engagement will focus on machine learning training, project planning, and use case review sessions with high-level architecture guidance and recommendations on best practices.

Scope of work

Machine Learning Training (3 days)

  • 3 day private class
  • Intro to Apache Spark, SparkML, fundamentals of Machine Learning/Deep Learning and best practices
  • Learn how to scale existing single-node work loads across a Spark cluster
  • Hands on labs with SparkML, MLflow, Keras and Horovod for distributed model training/inference

Machine Learning Consulting (7 days)

  • Convert existing single-node pipelines to Spark
  • Provide data science expertise
  • Tune Machine Learning jobs
  • Design model deployment architecture

Delivery

Services will be delivered on-site at the client’s premises or online via web conferencing by qualified Databricks personne. The customer’s Databricks platform must be deployed prior to engagement and adequate access provided to Databricks resource. Client to reimburse Databricks for reasonable travel expenses subject to client’s travel expense policy.

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