Google Cloud Celebrates Journey of 3 Inspiring Founders for the Asian Pacific American Heritage Month
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May is Asian Pacific American Heritage Month —a time for us to come together to celebrate and remember the important people and history of Asian and Pacific Island heritage. This feature highlights three AAPI founders from the Google For Startups community.
Read on to learn how these three founders built their businesses, leverage Google tech, and suggestion they have for aspiring entrepreneurs.
CultivatePeople
Founder: Lola Han
Description: CultivatePeople’s compensation software, Kamsa, provides global market pay rate data and helps companies make data-driven salary decisions so they can attract and retain their most valuable asset: employees.
Why GCP: “CultivatePeople began using GCP when integrating SSO/SAML authentication after our SaaS product became a high priority. We were able to exceed our clients’ expectations and increase their level of trust in our platform’s capabilities. We’re currently investigating additional machine learning products, such as Cloud AutoML, that will allow us to quickly deliver exciting features.”
Note from the Founder: “I grew up with immigrant parents who value stability and are risk-averse. My parents discouraged me from starting my own company because they didn’t want to see me struggle financially or see my health suffer (due to stress). I felt strongly about what CultivatePeople could do, so I started the company as a sole founder in 2017 and watched it double in size year over year since. While the ones I love most may not have cheered me on initially, it was important for me to hang on to the encouraging words of former bosses, executives, and founders to keep me focused on my mission.
My advice for other AAPI founders is to be a “silent assassin” and believe in the mission and values of your organization. Always remember to stop along the way and:
1) Enjoy the journey by celebrating wins and giving yourself credit;
2) Follow your intuition—it’s (almost) always right;
3) Recognize and invest in your people regularly (ie. give increases more than once a year, if warranted);
4) Give regular words of affirmation to employees on even small achievements.”
Swit
Founder: Josh Lee and Max Lim
Description: Swit is a team collaboration platform that seamlessly combines team chat with task management by allowing teams to turn their conversations into trackable tasks and share tasks to chat with simple drag-and-drop functionality, ensuring everyone is on the same page and projects get done faster.
Why GCP: “Swit is a cross-category hybrid work tool for chat and tasks. This functionality requires more complicated and heavier architecture for performance. So, configuring and managing virtual machines was really challenging to scale up our systems, while handling occasional unexpected traffic surges and frequent updates. Eventually we divided our monolithic architecture into 35 microservices when we launched our official product. The migration to GKE took around one month, and it turned out to be well worth the effort—our systems became able to offer high scalability and enough resilience to keep its uptime no matter what happened. Now we’re operating 84 workloads and 252 microservices with high stability with remarkably low downtime – less than 0.00001%/year.”
Note from the Founder: “As an AAPI founder based in Silicon Valley, I feel proud of the work ethics and diligence fellow Korean American entrepreneurs and professionals have long demonstrated here. Especially with K-pop breaking into the mainstream, I feel even more proud of our culture that strives toward an absolute perfection molded through years of training and dedication. The mission-driven culture of Silicon Valley coupled with Google’s edging technology and creativity really helped us build a product that not only encompasses verticals but also transcends cultures. Swit is growing at an unprecedented rate, and we hope to join the long list of successful AAPI entrepreneurs here. Swit’s close network with the AAPI community wouldn’t have been possible without Google support. We are grateful for this collaborative environment, and we hope to become the next-generation ambassador for collaboration after Google.”
Check out more from Swit in their founder story.
WISY
Founder: Min Chen
Description: Wisy develops technology to bring digital efficiency into the physical world, supporting consumer products businesses and making them thrive in the new economy. All of us have a bad experience when we can’t find the product we want to buy. That is a $1.9T problem in the consumer-packaged goods industry that Wisy is solving with AI and analytics to help manufacturers and retailers sell more by reducing out-of-stocks and waste at a global scale.
Why GCP: “GCP has an intuitive, easy to use interface, was lower cost, and offered preemptible instances with flexible compute options. Some of the reasons why Wisy decided to use GCP include instance and payment configurability, privacy and traffic security, cost-efficiency, and Machine Learning.
Wisy has been able to advance quickly with product development, as well as collaborate better and iterate faster in the creation of our AI models, while reducing costs by 40%. At Wisy, we are solving a problem that affects everyone who shops at a store.“
Note from the Founder: “Two years ago, I moved to San Francisco to expand my second startup, Wisy. This is when I learned that my name ‘Min’ stands for ‘minority.’ I was born in China, raised in a Black community in Panama, received scholarships to attend both Carnegie Mellon and UC Berkeley. I worked for 20 years in several countries, but I have never felt so discriminated against due to my race, ethnicity, gender and age than during my time in Silicon Valley. However, this is also the place I learned that my diverse life experience is my competitive advantage. My background enables me to recruit and relate to people in different countries, create scalable and flexible products for multinational customers, and run global operations efficiently.
My recommendation to AAPI founders is to find strength in their multicultural background. Don’t hide what makes you unique, do not limit yourselves, and do not let others limit you. You will lose your edge when trading authenticity for validation. Be proud and own your story.”
If you want to learn more about how Google Cloud can help your startup, visit our Startup Program application page here and sign up for our monthly startup newsletter to get a peek at our community activities, digital events, special offers, and more.To learn more about how you can help #StopAsianHate during Asian Pacific American Heritage Month and beyond, visit their website here.
Google Migration and BigQuery Brings PedidosYa Closer towards its Goal of Becoming Data-driven
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Editor’s note: PedidosYa is the market leader for online food ordering in Latin America, serving 15 markets and over 400 cities. It’s also one of the largest brands within the German multinational company Delivery Hero SE. With over 20 million app downloads, PedidosYa provides the best online delivery experience through 71,000+ online partners, including restaurants, shops, drugstores, and specialized markets.
Having constant access to fresh customer data is a key requirement for PedidosYa to improve and innovate our customer’s experience. Our internal stakeholders also require faster insights to drive agile business decisions. Back in early 2020, PedidosYa’s leadership tasked the data team to make the impossible possible. Our team’s mission was to democratize data by providing universal and secure access while creating a comprehensive information ecosystem across PedidosYa. We also had to achieve this goal while keeping costs under control— even during the migration stage and removing operational bottlenecks.
Challenges with legacy cloud infrastructure
PedidosYa first built its data platform on top of AWS. Our data warehouse ran on Redshift, and our data lake was in S3. We used Presto and Hue as the user interfaces for our data analysts. However, maintaining this infrastructure was a daunting task. Our legacy platform couldn’t keep up with the increasing analytics demands. For example, the data stored on S3 complemented by Presto/Hue required high operational overhead. This was because Presto and our IAM (identity access management) didn’t integrate well in our legacy ecosystem. Managing individual users and mapping IAM roles with groups and Kerberos was operationally time-consuming and costly. Further, sharding access on the S3 files was far too complicated to enable seamless ACLs (access control lists).
There were also challenges with workload management. Our data warehouse had batch data loaded overnight. If one analyst scheduled a query to run during the overnight ETL (extract, transform, load) workload, it would disrupt the current ETL task. This could stop the entire data pipeline. We’d have to wait until data engineers intervened with a manual fix.
It was also difficult to understand whether a query error was due to performance issues or platform resource exhaustion. This lack of clarity affected our data analysts’ ability to autonomously improve querying efficiency. Data team members needed to manually inspect personal queries looking for performance issues. Also, the current architecture was prone to a ‘tragedy of the commons’ situation; it was seen as an unlimited and free resource. As a result, it was impossible to disentangle the infrastructure from different stakeholder teams, as all had very different needs.
The decision to modernize our data warehouse
Given the growing challenges from our legacy platform, our tech team decided to transform our analytics environment with a modern data warehouse. They required the following key criteria from their next data platform:
- Scalability – The ability to grow with elastic infrastructure.
- Cost control – Cost management and transparency. These factors promote efficiency and ownership—both key aspects of data democratization.
- Metadata management – Intuitive data platform focusing on users’ previous SQL knowledge. Plus, being able to enrich the informational ecosystem with metadata, to diminish data gatekeepers.
- Ease of management – The team needed to reduce operational costs with a serverless solution. Data engineers wanted to focus on their key roles rather than acting as database administrators and infrastructure engineers. The team also wanted much higher availability, and to reduce the impact of maintenance windows and vacuum/analysis.
- Data governance and access rights – With a growing employee base with varying data access requirements, the team needed a simple yet comprehensive solution to understand and track user access to data.
Migrating to Google Cloud
After exploring other alternatives, we concluded Google Cloud had an answer to each of our decision drivers. Google Cloud’s serverless, managed, and integrated data platform, coupled with its seamless integration across open-source solutions, was the perfect answer for our organization. In particular, the natural integration with Airflow as a job orchestrator and Kubernetes for flexible on-demand infrastructure was key.
We used Dataflow together with Pub/Sub and Cloud Functions for our data ingestion requirements, which has made our deployment process with Terraform seamless. Because we set up everything in our environment programmatically, operation time has diminished. Google Cloud reduced the deployment process from about 16 hours in our legacy platform to 4 hours. This is partly due to the friendliness of automating the deployment (such as schema check, load test, table creation, build.) process with Terraform, Cloud Functions, Pub/Sub, Dataflow, and BigQuery on GCP. Input messages processed with Dataflow allow us to abstract and plan the schema changes according to the needs of the functional team. For example, schema changes raise an alarm, and then we can modify the raw layer table schema. By doing this, we ensure that backend modifications that we don’t control do not affect upper layers.
A key reason why we picked Google Cloud was because of its advanced cost and workload management coupled with its transparent log analytics. This information gives us a complete view into any query performance issues to make improvements on the fly. Further, we achieved a significant amount of cost savings by consolidating multiple tools to BigQuery.With BigQuery, we’ve been able to reduce our total cost per query by 5x.
This was due to a number of reasons:
- Automating pipeline deployment made it much simpler to maintain the data processing processes.
- Analysts are conscious about what queries they’re running, resulting in running better, more optimized queries.
- Analysts use a Data Studio dashboard to see their queries and all the associated costs. As a result, there’s a lot more transparency for each persona.
With these changes, we can easily manage and assign costs associated with each workload with their own cost centers using specific Google Cloud projects.
Change management is always challenging. However, BigQuery is intuitive and doesn’t have a steep learning curve from Hue/Hive on SQL basics. BigQuery also allowed the team to expand its capabilities and enabled them to properly work with nested structures, avoiding unnecessary joins and improving query efficiency. Additionally, we now use Data Catalog as our unique point of truth for metadata management. This allows our team to break the data access barriers and enable federation of data across the organization. By using Airflow to orchestrate everything, we keep track of every data stream. With this information, each end user can see their regularly used data entities’ status via the dashboard. This also adds transparency to our everyday data processes.
Finally, with Google Cloud’s IAM rules applied across the different products, data sharing and access is close to a noOps experience. We have programmatically implemented access according to roles and level access within the company. This allows certain pre-validated roles to view more sensitive information. These solutions help drive a more automated data governance experience.
Up next: Google Cloud AI/ML
The new stack based on BigQuery has created significant productivity gains. Freed from the burden of operational management, PedidosYa’s data team can now focus on adding value through data tools and products.
- Our data engineers are better equipped to integrate constantly changing transactional and operational data.
- The dataOps team can automate the infrastructure and provide autonomy to the end user.
- Our data quality team can focus on bringing added value to data stakeholders.
- Data scientists and data analytics can spend more time analyzing data and less time asking data gatekeepers for data access.
PedidosYa can now democratize data access with a well-governed architecture. We are still at the beginning of our journey, but we are closer to achieving our vision of building a data-driven organization. Up next: expanding our artificial intelligence and machine learning capabilities.
Tune in to Google Cloud’s Applied ML Summit on June 10th, 2021, or listen on-demand later, to learn how to apply groundbreaking machine learning technology in your projects.
Sainsbury’s Uses AI to Figure Out How the World Eats
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Retail will forever be an industry that must constantly reinvent itself in response to, and anticipation of, ever-changing consumer demands.
Digital transformation is fueling these changes and we’ve previously spoken about how businesses including Ulta Beauty and Kohl’s are taking advantage of Google Cloud to put data at the center of what they do and deliver the best possible shopping experience and product offerings for their customers.
Leveraging Google Cloud machine learning platform, Sainsbury is able to develop predictive analytics models to spot trends and adjust inventory, providing shoppers with a better experience.
Sainsbury’s, one of Britain’s best-known supermarkets, is another great example of a business transforming the way it engages with its customers with the cloud.
With over 150 years of service, Sainsbury’s vision is to be the most trusted retailer, where people love to work and shop. It makes customers’ lives easier, by offering great quality and service at fair prices.
The food industry and the way that customers shop is rapidly changing. From foodie hashtags on Instagram, to the latest cooking fads, customers want to stay connected to the latest trends and Sainsbury’s is empowering them do that.
To help Sainsbury’s achieve this goal, its Commercial and Technology teams, in partnership with Accenture, are building cutting-edge machine learning solutions on Google Cloud Platform (GCP) to provide new insights on what customers want and the trends driving their eating habits.
With the help of Google Cloud Platform, we are generating new insights into how the world eats and lives, to help us stay ahead of market trends and provide an even better shopping experience for our customers.
–Phil Jordan, Group CIO, Sainsbury’s
Sainsbury’s solution relies on data from multiple structured and unstructured sources. Using Google Cloud’s powerful cloud-based analytics tools to ingest, clean and classify that data, and a custom-built front-end interface for internal users to seamlessly navigate through a variety of filters and categories, Sainsbury’s is able to gain advanced insights in real time.
As a result, Sainsbury’s has been able to develop predictive analytics models to spot trends and adjust inventory, providing shoppers with a better experience.
Phil Jordan, Group CIO of Sainsbury’s believes this project will have a big impact.
“The grocery market continues to change rapidly. We know our customers want high quality at great value and that finding innovative and distinctive products is increasingly important to them. With the help of Google Cloud Platform, we are generating new insights into how the world eats and lives, to help us stay ahead of market trends and provide an even better shopping experience for our customers.”
This project is also a great example of the successes Google Cloud customers have when they work with the company’s partners.
“We’re delighted to partner with Google Cloud to help the Sainsbury’s Commercial team apply predictive analytics to the identification of new and emerging trends in grocery,” says Adrian Bertschinger, Managing Director for Retail, Accenture.
“The food sector is experiencing significant, rapid disruption, and this new, cloud-based insights platform will help Sainsbury’s identify trends much earlier and adapt their product assortment in a faster, more informed way—all for the benefit of customers.”
Whatever the next food or shopping trend may be, Sainsbury’s is looking to the cloud to help them stay a step ahead.
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Digital transformation is about how digital technologies can connect people and processes to solve challenges that traditional methodologies could not.
While this transformation is imperative for businesses of all sizes, the Frost & Sullivan Enterprise Cloud Maturity Index (ECMI) assessment indicates that around 85% of CXOs want to digitally transform their enterprises, but only 39% of them have a clear plan to achieve this transformation.
Most business leaders are exploring new business ideas around cloud to extract better outcomes, increase productivity, create opportunities and redefine customer engagement processes as part of their internal strategies.
It has been proved time and again that enterprises need to bank on emerging technologies like cloud that provide ‘do more with less’ approach. Cloud has the potential to transform IT departments through infrastructure consolidation and optimization.
To understand the interest and level of cloud adoption in enterprises, Google Cloud partnered with Frost & Sullivan to recognize the unique business drivers and key challenges in Cloud adoption that come the enterprise way during their business transformation journey.
Read the report to find out the challenges, solutions and benefits of digital transformation and the cloud.
Quick Migration, Zero Outages and Cost Savings: Rossi Residencial’s SAP to Google Cloud Journey!
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After three migrations to different cloud providers, the company managed to migrate with no system outages for the first time, supported by partner Sky.One.
Results
- Migrated four SAP environments and four servers in just one month with no system outages
- Zero unavailability periods since migrating
- Less time spent worrying about operational issues increases the focus on business
50% savings on monthly cloud costs
Rossi Residencial, one of Brazil’s largest construction companies and real-estate developers, with around 150 employees, hundreds of business and engineering partners, and nationwide service, has used SAP solutions for financial management since 1999. Taxes, accessory obligations, accounting requirements, and other processes are managed through the system in an integrated and automated manner, which provides the business with crucial support.
Over the past few years, the company has begun to promote independent, sustainable business units to focus on strategic locations and products. This prompted its technology team to adapt as well, and they saw the cloud as an opportunity to add flexibility to SAP’s management.
“If I need to open a new branch or break ground on a project, the entire system core is already in the cloud and I don’t have to worry about local infrastructure,” explains Eduardo Araújo, Rossi’s IT Manager. “It also means our operational costs are significantly reduced.”
A few years ago, the company started working with the ECC component in the EHP 8 version, using modules such as FI (financial accounting), CO (controlling), MM (materials management) and TRM (treasury and risk management). But the dollar’s high exchange rate in 2020 increased costs with their then provider too much. The team was also not satisfied with the provider’s service, leading it to look for a new provider and a partner to support migration.
An essential requirement the new provider had to offer was high availability and scalability. Potential partners had to perform migration in a short time window (as the contract with the other service was about to expire) and be familiar with the previous provider to ensure the operation’s success. After spending some time searching, the company chose Google Cloud and Sky.One for the project.
“Out of the cloud options we researched, Google Cloud offered us the best financial conditions and a solution that truly catered to us. And out of the many partners we contacted, Sky.One offered the best work planning and service.”—Eduardo Araújo, IT Manager, Rossi Residencial
First migration with no system outages
The tight migration deadline meant the company would not have the time to install every app in Google Cloud from scratch, so Rossi asked the Sky.One team to mirror its entire previous architecture, that is, migrate the virtual machines from the company’s four SAP environments and four servers from other apps directly to Google Cloud.
After mapping the source structure in detail along with Rossi, the partner was able to complete migration planning in a month. “If you map before migrating and thus understand the customer’s environment well, you are able to prepare the destination so it has every integration and its respective access,” says Ricardo Nunes, Solution Expert at Sky.One.
The tool chosen to move the environments was Migrate for Compute Engine (previously known as Velostrata), which streamlines, facilitates and reduces risks for app migration to Google Cloud. Sky.One selected an expert in this solution to conduct the process, which was also supported by Google Cloud experts to make any needed adjustments.
The process took just a month to complete. The environments were successfully migrated with zero impact on operations, an unprecedented feat for the company. Now SAP environments run in a new infrastructure consisting of Compute Engine, a service for creating and running VMs, and Cloud Storage for data storage.
“This is the first time, after three previous migrations to private and public clouds, that our users have not felt any impact and we didn’t have system outages. It was a six-hands project that worked very well.”—Eduardo Araújo, IT Manager, Rossi Residencial
Flexibility to deal with every business need
Since the migration, Rossi has not suffered system outages or handled related user requests and incidents. Performance has remained high even after the team resized the VMs. The flexibility to add or subtract resources based on the company’s demands proved crucial. “Rossi operates in a segment with elasticity. In any given year, we can have two/three projects or ten. That’s why it’s important to have that resource in the cloud,” says Araújo.
Since the company does not operate 24/7, another benefit from migrating was the ability to schedule when to switch on and off servers, bringing cost savings. Furthermore, billing in reais at a fixed exchange rate with dollars led to a 50% cost reduction versus the previous provider.
The ease of integration between Google Cloud and SAP’s tools pleasantly surprised the team. “We were worried about potential incompatibilities, and we didn’t know if we would be able to work like before. Today we can work even better than before,” says the IT manager. According to Sky.One, the fine adaptation between the solutions becomes noticeable right after migration.
“Google Cloud’s solutions support all SAP migration steps, but after migrating we noticed that daily operations had become even more tightly integrated.”—Ricardo Nunes, Solution Expert, Sky.One
The cloud’s stability and security have streamlined the IT team’s daily routine. They no longer have to go to the company outside business hours to perform updates or repairs. Currently, employees can work remotely with peace of mind and maintain business continuity throughout Brazil.
With more time to focus on business needs instead of operational issues, the team is contemplating the addition of new Google Cloud tools. Rossi’s next challenge is to bolster its business operations and customer service even further using data analytics and AI solutions, making the most of its broad database.
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Driving Business Transformation in Manufacturing, Industrial, and Transportation Using Google Cloud and AI/ML
Google Cloud partners closely with manufacturing, industrial, and transportation organizations to drive business transformation.
In this video, Mandeep Waraich, Head of Product – Industrial AI, Google Cloud, shares customer stories as well as Google Cloud’s differentiated AI products and solutions.
Waraich covers the current state of automation and industrial efficiency and how artificial intelligence is revealing an entirely new universe of possibilities.
He also speaks about Google Cloud’s approach to bringing these AI technologies to the market, and Google Cloud’s “deploy anywhere” methodology that helps achieve the impact of AI at a global enterprise scale.
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