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44:51 Minutes
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The Strange Phenomenon AI Revealed at Ride-Hailing Company Go-Jek
Go-Jek, Indonesia’s first billion-dollar startup, has seen an incredible amount of growth in both users and data over the past two years. Many of the ride-hailing company’s services are backed by machine learning models hosted on Google Cloud Platform. Models range from driver allocation, to dynamic surge pricing, to food recommendation, and process millions of bookings every day, leading to substantial increases in revenue and customer retention.
By embracing Google Cloud, Go-Jek has overcome many of the technical challenges brought on by its rapid growth. BigQuery has become the cornerstone of their data foundation, scaling seamlessly to meet their immense data storage and processing needs.
Using Pub/Sub as an event stream and Dataflow for unified batch and stream processing has prevented inconsistencies in production data, while simultaneously reducing costs through intelligent resource allocation.
Together, these technologies allow Go-Jek to react immediately to real world events, whether by retraining models with ML Engine, or refreshing data in a low latency data store like BigTable.
Find out how Go-Jek leverages Google Cloud and other lessons they have learned scaling machine learning.
How Modern is Your Data Warehouse? Find Out With This Test

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10:00 Minutes
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As more and more businesses turn to advanced data analytics to help them make smarter decisions, run real-time analytics, and improve business operations, an increasing number are modernizing their data warehouses to make it all possible.
For many businesses, knowing how to modernize means understanding where their data warehouse sits on the spectrum between traditional and cutting edge.
To help, we collaborated with TDWI to offer the data warehouse maturity assessment. By answering a few questions on their current warehouse environment, businesses can get a customized report with helpful tips and recommendations.
A report card for your data warehouse
The data warehouse maturity assessment evaluates five different categories, assigning your business a rating for each that spans from “traditional warehouse” to “advanced/visionary.”
- Data diversity: How well does your warehouse support disparate data types, and does it provide users with a current and holistic view of data from a variety of internal and external sources?
- Infrastructure agility: How well does your warehouse support the various needs of your organization by allowing access from anywhere, ingesting data in real time, and separating storage from compute to enable independent scaling?
- Analytics support: How easy is it to adopt sophisticated analytical techniques at scale, such as machine learning, predictive analytics, deep learning, and IoT analytics?
- Collaboration and sharing: Can teams within your organization and beyond share information and work together quickly and easily using data from your warehouse, and is your data strategy aligned with your business goals?
- Security and governance: Are there tools and techniques in place to control data access, support data governance, and ensure compliance with data security standards?
In addition to the assessment you’ll also receive a detailed report with guidance and best practices that can help you determine your next steps in your modernization journey.
Getting started
Fill out a brief form to launch the survey, then take 15 minutes to answer a series of questions about the platforms, systems, and hardware you use to integrate, manage, and store business data for reporting and analytics. You’ll see your results right away.
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24:00 Minutes
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New Capabilities in Google Cloud Dataprep: A Must-Read for Data Teams
In this video, Bertrand Cariou, Sr. Director Product Marketing, Trifacta and Sean Ma, Sr. Director, Product Management, Trifacta take a deep dive into new capabilities for Cloud Dataprep.
They walk us through several new features to enable a wider range of use cases with Cloud Dataprep; and, major enhancements to existing features asked for by enterprises.
Some of the new capabilities include:
- New connectivity with Google Sheets, Microsoft Excel, Oracle, SQL Server, DB2, and Salesforce
- New Data Pipeline Orchestration & Alerting
- Advanced Performance Optimization
- Fine Grain Data Access through OAuth
The walkthrough will also host a demonstration that exemplifies the new capabilities in the product itself.
Finally, Bertrand and Sean show an end-to-end data pipeline example that connects diverse data sources from multiple flows into a sequence that can be designed in Cloud Dataprep and integrated with Cloud Functions.
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44:30 Minutes
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How Go-Jek, Indonesia’s First Billion-dollar Startup, Improved the Productivity of Data Scientists
Go-Jek, Indonesia’s first billion-dollar startup, has seen an incredible amount of growth in both users and data over the past two years. Many of the ride-hailing company’s services are backed by machine learning models hosted on Google Cloud Platform.
Models range from driver
But senior executives at Go-Jek realized something: One of their most important and expensive resources, data scientists, were spending far too much time cleaning data. That wasn’t part of their remit and resulted in a waste of time and money.
As a COO, this a major concern for any company undertaking a machine learning initiative. Data scientists are hard to come by and their salaries have been on the rise for the last few years. Yet according to some reports data scientists spend upto 80% of their time just preparing data—not creating models.
Watch how operational teams at Go-Jek combined the right Google tools and processes to improve the productivity of their data scientists.
Zeotap Uses Big Data to Enable Personalized, Precision Marketing at Scale

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5:30 Minutes
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Customers today expect brands to know what they want. In fact, Forbes cited that 71% of customers feel frustrated when the shopping experience is impersonal. From interests to purchase habits, companies need to target customers effectively in order to stand out from the plethora of competitors in the online marketplace.
“Our mission is to help brands engage customers with the most appropriate marketing messages at the right place and at the right time while respecting consumer privacy and ensuring regulatory compliance. The experience of Google Cloud in working with large-scale datasets makes the platform an excellent fit for us.”
—Projjol Banerjea, co-founder and Chief Product Officer, Zeotap
Leveraging first-, second-, and third-party data, Zeotap’s Customer Intelligence Platform (CIP)—a CDP with additional identity resolution and third-party data enrichment capabilities—allows brands to engage with their known and unknown users with tailored marketing messages and next best offers or actions. It also offers out-of-box algorithms for standard marketing use cases such as promoting a specific product that will resonate with audiences and custom algorithms for very niche and specific use cases.
“Our mission is to help brands engage customers with the most appropriate marketing messages at the right place and at the right time while respecting consumer privacy and ensuring regulatory compliance. The experience of Google Cloud in working with large-scale datasets makes the platform an excellent fit for us,” says Projjol Banerjea, co-founder and Chief Product Officer at Zeotap.
“With BigQuery, we are able to operate more efficiently, removing 80% of the operation load that we would otherwise have to manage on a different cloud provider. As a result, we get to build and deliver products faster.”
—Sathish K S, VP Engineering, Zeotap
Improving data processing to deliver products faster
The cloud-native company migrated from its previous provider to Google Cloud in October 2019 because it was attracted to the benefits of BigQuery as a serverless cloud data warehouse. This was a feature that wasn’t available with its previous provider.
Sathish K S, Engineering Vice-President at Zeotap says, “With BigQuery, we are able to operate more efficiently, removing 80% of the operation load that we would otherwise have to manage on a different cloud provider. As a result, we get to build and deliver products faster.” Since coming onboard BigQuery, Zeotap has been able to increase the speed of its product delivery by 40%.
BigQuery also offers a much higher query limit, which is helpful because Zeotap can converge all of its previous operation load across different platforms into one data warehouse without worrying about it being overloaded.
One of the key services Zeotap offers is customer relationship management (CRM) platform integration. Using Dataflow, Zeotap can easily stream first-party data into BigQuery at scale.
The data integration capabilities of Cloud Data Fusion also complements Dataflow to help Zeotap enhance its API offerings. To illustrate, an ecommerce company may use Zeotap’s internal API to understand their customer’s cart and check-out habits and add Zeotap’s extra layer of data intelligence to it, so they can improve their marketing efforts. Cloud Data Fusion enables a seamless flow of real-time data so that the company can deliver the relevant ads or suggest products just before they make a purchase, which increases the likelihood of them buying more.
Zeotap uses Dataproc and Pub/Sub to manage the large flow of data that goes in and out of its database. Because many of its customers are pushing data in real time, Pub/Sub acts as a queuing engine that feeds them into Dataflow. Likewise, the data from Dataflow is also being channeled back smoothly to the customer endpoints using Pub/Sub.
Being able to automate all of its processes benefitted the DevOps team, as they now have time to focus on developing and improving Zeotap’s product offerings instead of spending time and energy on operations.
Managing a full migration seamlessly
Today, all of Zeotap’s data is hosted on Google Cloud. The company began its lift and shift migration in October 2019 and was complete by April 2020. “We have close to 405 data pipelines, and even after the migration, we had to verify the right datasets. We had terabytes of data to move, and despite this, our operations were not affected,” says Aditya Chandra, Vice-President of Infrastructure and Security at Zeotap.
Apart from the BigQuery capabilities, there were other major things Zeotap looked out for in its decision to move to a new cloud provider. The functional parity of Google Cloud was important so that it did not have to rebuild many of its existing structures. Zeotap also didn’t want any drop in performance during and after the move to a new cloud provider. Finally, as a multi-region company, it used to have to spot instance problems and run them on demand, which had cost implications. With the move, it no longer had to face such issues.
“Whatever Spark code that was already running on our existing system had to be lifted and shifted into Dataproc without any library changes because 60% of our codebase is out of there. We’re glad that this was possible,” says Ameya Agnihotri, Chief Technology Officer.
Managing business continuity with a trusted partner
Zeotap now works with Rackspace Technology (Rackspace) as it continues to optimize its infrastructure operations. As a marketing and technology company, Zeotap needs niche expertise to manage big data processing issues.
Ameya Agnihotri shares, “Given its global expertise in dealing with on-premises as well as cloud solutions, Rackspace can really add value because they are better equipped to troubleshoot and handle complex data operations.” Zeotap has plans to explore more of Google Cloud’s artificial intelligence (AI) and machine learning (ML) capabilities, so having a partner in this journey will be valuable to the team.
With so much data on hand, security is paramount to Zeotap. It does a lot of internal security assessments daily. This is one of the areas where the team works with Rackspace to ensure that it adopts best practices and stays on top of the latest updates. With its ability to handle big data operations, Rackspace also acts as an extension of the Zeotap team that supports the infrastructure side of the business.
“The level of engagement from Google Cloud has been excellent, particularly the ability to bring in expertise from different parts of the organization. The personal touch meant we could reach product owners and managers of specific products. This kind of support is what we really value and appreciate.”
—Ameya Agnihotri , Chief Technology Officer, Zeotap
Future plans and collaboration with Google Cloud
Zeotap is currently exploring Cloud Bigtable and API Gateway as it continues to grow the business and explore new types of services to offer to its customers. Although it has a software-as-a-service (SaaS) offering for customers to self-serve, some may prefer to do a server-to-server integration so that they do not have to worry about the back end at all. For this reason, Zeotap is exploring the possibility of integrating these customers’ APIs in the back end of its API, using Google Cloud’s API Gateway features that are available out of the box. The company is also looking forward to the new features being released on BigQuery, as well as exploring more of the alerting and monitoring capabilities of Google Cloud.
“The level of engagement from Google Cloud has been excellent, particularly the ability to bring in expertise from different parts of the organization,” says Ameya. He shares that the team has had many fortnightly calls when there were issues to address, and the Google Cloud team would help to fix the problems. “The personal touch meant we could reach product owners and managers of specific products. This kind of support is what we really value and appreciate.”
With big plans ahead for Zeotap that include becoming a Google Cloud Technology Partner in the near future, Swapnasarit Sahu, Chief Data and Analytics Officer, is confident that the company has chosen the right cloud solution. “We see Google as one of the frontrunners in the space of AI and ML solutions, which can really help data scientists in developing new and more innovative products and solutions, and we look forward to building great products with them,” he says.
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1:30 Minutes
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AI-powered Cameras Help You Serve Your Pets Better. Learn How
Watch the video to learn how you can leverage Google Cloud platform and AI functions to build pet-detection cameras that can capture and send image-based alert messages on your phone to notify when your pets arrive or leave.
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