Mark Rittman is joined in this episode by Jordan Tigani, Director of Product Management at Google for Google BigQuery, to talk about the history of BigQuery and its technology origins in Dremel; how BigQuery has evolved since its original release to handle a wide range of data warehouse workloads; and new features announced for BigQuery at Google Next’19 including BI Engine, Storage API, Connected Sheets and a range of new data connectors from Supermetrics and Fivetran.
Mark Rittman is joined in this 50th Episode Special by our original guest on the first episode of Drill to Detail, Stewart Bryson, to talk about developing agile BI applications using FiveTran, SnowflakeDB and Looker and his recent work developing a BI solution for Google Play Marketing using Google Data Studio and Google Cloud Platform. We're also joined later in the show by Alex Gorbachev from Pythian, our mystery guest who Stewart then interviews flawlessly armed only with a set of questions given to him as the guest was unveiled ... though be sure to listen past the final closing music for the bonus out-takes.
Mark Rittman is joined by Will Davis from Trifacta to talk about the public beta of Google Cloud Dataprep, Trifacta's data wrangling platform and topics including metadata management, data quality and data management for big data and cloud data sources.
- Google Cloud Dataprep on Google Cloud Platform
- "Google Cloud Dataprep: Spreadsheet-Style Data Wrangling Powered by Google Cloud Dataflow"
- "A New Cloud-Based Data Prep Solution from Google & Trifacta"
- Trifacta website
- "A Breakthrough Approach to Exploring and Preparing Data"
- Trifacta platform architecture
- "Garbage In, Garbage Out: Why Data Quality Matters"
- "How to Put an Effective Metadata Strategy in Place"
Mark is joined in this episode by Google Cloud Platform Developer Advocate Felipe Hoffa, talking about getting started as a developer using Google BigQuery along with Google Cloud Dataflow, Google Cloud Dataprep and Google Cloud Platform's machine learning APIs.
Mark is joined by returning special guest Dan McClary to talk about data modeling and database design on distributed query engines such as Google BigQuery, the underlying Dremel technology and columnar storage format that enables this cloud distributed data warehouse-as-a-service platform to scale to petabyte-size tables spanning tens of thousands of servers, and techniques to optimize BigQuery table joins using nested fields, table partitioning and denormalization.
- Dremel: Interactive Analysis of Web-Scale Datasets
- BigQuery under the hood
- Inside Capacitor, BigQuery’s next-generation columnar storage format
- Drill To Detail Ep.2. 'Future Of SQL On Hadoop', With Special Guest Dan McClary
- Google BigQuery, Large Table Joins and How Nested, Repeated Values and the Capacitor Storage Format (and Looker) Saves the Day
Mark Rittman is joined by Alex Olivier from Qubit to talk about their platform journey from on-premise Hadoop to petabytes of data running in Google Cloud Platform, using Google Cloud Dataflow (aka Apache Beam), Google PubSub and Google BigQuery along with machine learning and analytics to deliver personalisation at-scale for digital retailers around the world.