“Using Google App Engine and Google Cloud SQL make our applications go live in half the time and have provided us with hassle-free control over all processes.”
"We've built Bigbasket from the ground up using Google Maps Platform. It makes sure we have the right customer locations and deliver to them on time. We couldn't have started Bigbasket without Google Maps. It helps us to be fast and efficient, and make sure our customers get what they've …
“We’re looking into providing them with Chromebooks as a potential way to do that. The fact that so many of our employees are already familiar with Google definitely helps.”
“SADA suggested a phased in, launch and learn method, building on experience through waves of implementation across our global user base. Through this, we fine-tuned our training and change management to make each wave of go-live better each time. In addition to onsite training, we added online reference tools, webcasts, …
“The Google Cloud Professional Services team was instrumental in driving the success of some key projects for the GO-JEK data science team. Ultimately, thanks to Google Cloud Professional Services, we had a deeper understanding of Google technologies, greater collaboration, smarter designs, and a faster time to market.”
“At 17 Media, we extensively use containerization for fast development and testing. With Google Kubernetes Engine, our development cycle experienced an 80 percent increase in overall speed. Google Kubernetes Engine fits our requirements perfectly. Moreover, Google Cloud data processing products such as BigQuery and Cloud Dataflow enable us to better …
“We moved our services to Google Kubernetes Engine as it allows us to deploy containerized applications, monitor and control our environments from a dedicated console, and scale according to user demand.”
“We thought if we could be a member of the community that embraces the innovation captured in Google Cloud Platform products, we could continually improve our ability to seize opportunities and solve problems for our clients.”
“This innovation cycle allows us to run very hard at opportunities and have confidence that what we deliver with Google Cloud Platform will benefit us and our clients.”
“With our previous infrastructure, it took about three weeks to set up our Hadoop cluster, and we spent five hours a week on maintenance. It took only a few minutes to get up and running on Google Cloud Bigtable, and we don’t spend any time maintaining it. It just runs.”
“We create risk profiles of third-party sellers, so our customers know who is representing their products, how their products and IP are being represented, and their customer’s experience. When a customer has a poor experience from a counterfeit branded product, the brand may lose a customer, but the marketplace operator …
“With the feedback classification model we’ve built, and by leveraging Google Compute Engine and Cloud Dataproc, we can perform an analysis of more than 160 million customer reviews of more than 2 million sellers in just under 4 hours, which is phenomenal.”
“The big challenge in our sector at the moment is personalization: tailoring a website to a visitor’s interests, in order to enhance conversion rates and customer satisfaction. To make the modifications as targeted and pertinent as possible, an enormous volume of data is required to develop sophisticated, automated algorithms.”
“Now, at every stage, we can manage and update the pipeline without interrupting the service. Cloud Dataflow does its job perfectly: it handles everything automatically so we can be sure of every cluster and really stand by the quality of our data.”
“Monetization was a key selling point of Apigee for us. Being able to get started with Apigee, sign up, break out our APIs into set packages, and have developers come in and purchase—it’s been a great tool for us.”
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