June 12, 2021

Taking A Tour Of The Google Cloud Platform For Data And Analytics

53 minutes

Summary

Google pioneered an impressive number of the architectural underpinnings of the broader big data ecosystem. Now they offer the technologies that they run internally to external users of their cloud platform. In this episode Lak Lakshmanan enumerates the variety of services that are available for building your various data processing and analytical systems. He shares some of the common patterns for building pipelines to power business intelligence dashboards, machine learning applications, and data warehouses. If you’ve ever been overwhelmed or confused by the array of services available in the Google Cloud Platform then this episode is for you.

Announcements

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Your host is Tobias Macey and today I’m interviewing Lak Lakshmanan about the suite of services for data and analytics in Google Cloud Platform.

Interview

Introduction

How did you get involved in the area of data management?

Can you start by giving an overview of the tools and products that are offered as part of Google Cloud for data and analytics?

How do the various systems relate to each other for building a full workflow?

How do you balance the need for clean integration between services with the need to make them useful in isolation when used as a single component of a data platform?

What have you found to be the primary motivators for customers who are adopting GCP for some or all of their data workloads?

What are some of the challenges that new users of GCP encounter when working with the data and analytics products that it offers?

What are the systems that you have found to be easiest to work with?

Which are the most challenging to work with, whether due to the kinds of problems that they are solving for, or due to their user experience design?

How has your work with customers fed back into the products that you are building on top of?

What are some examples of architectural or software patterns that are unique to the GCP product suite?

What are the most interesting, innovative, or unexpected ways that you have seen Google Cloud’s data and analytics services used?

What are the most interesting, unexpected, or challenging lessons that you have learned while working at Google and helping customers succeed in their data and analytics efforts?

What are some of the new capabilities, new services, or industry trends that you are most excited for?

Contact Info

@lak_gcp on Twitter

Website

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

Google Cloud

Data and Analytics Services

Forrester Wave

Dremel

BigQuery

MapReduce

Cloud Spanner

Spanner Paper

Hadoop

Tensorflow

Google Cloud SQL

Apache Spark

Dataproc

Dataflow

Apache Beam

Databricks

Mixpanel

Avalanche data warehouse

Kubernetes

GKE (Google Kubernetes Engine)

Google Cloud Run

Android

Youtube

Google Translate

Teradata

Power BI

Podcast Episode

AI Platform Notebooks

GitHub Data Repository

Stack Overflow Questions Data Repository

PyPI Download Statistics

Recommendations AI

Pub/Sub

Bigtable

Datastream

Change Data Capture

Podcast Episode About Debezium for CDC

Podcast Episode About CDC with Datacoral

Document AI

Google Meet

Data Governance

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The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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By Tobias Macey

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