Case Studies
Google Cloud certification training to improve a business’ services using machine learning
Kohga has been involved in the printing industry since its establishment, and has been in the field of digital contents since the dawn of the Internet in 1990. They now provide support for web production related work, from consulting to planning and output. Kohga’s motto is “a website that increases effectiveness”, and they provide SEO measures, access analysis, and follow-up contributions by experts from each department. As a first step to further accelerate the use of Google Cloud and strengthen the service in the chatbot tool of the in-house developed service, the planning and production department will be informed about the impressions of receiving the training provided by Cloud Ace and the subsequent effects. We interviewed Mr. Kensaku Kikuiri, director of the planning department. We asked him about Kohga’s efforts in accelerating their use of Google Cloud for the chat bots used in their in-house developed services, as well as their experience from their training, provided by Cloud Ace as a first step in strengthening their services.
Mr. Kensaku Kikuiri, Planning and Production Department, Kohga
Challenges and objectives before taking the training
We implemented Google Cloud around 3 years ago. However, we were not able to utilize the functions and services to their full potential. So we wanted to thoroughly understand Google Cloud, and develop it as the first step in full-scale introduction.
At the same time, we had in-house developments for chatbots using Dialogflow.
"Sorewa" is a 24-hour, real-time chat support service that aims to increase customer contact points for companies and increase user satisfaction. We strongly felt the need to incorporate machine learning during updates in order to reduce the labor cost, promote work efficiency. This resulted in many within the company to advocate for the creation of cloud-based machine learning solutions, and we decided to take this course.
Regarding machine learning, we considered other products, but ultimately decided that Google Cloud is the best because it is easy to use and works well with Dialogflow.
I was studying machine learning on a personal initiative, but I felt that there were difficult hurdles with self-learning.
As a non-engineer with little knowledge I was fascinated during the certification training, in which the instructor supported me when I stumbled with the hands-on work. I wanted to experience optimization, deployment, and scaling of various types of production machine learning models, and to experience and deepen my understanding of actual operations, not just theory.
Effects and merits after taking the training
By understanding the whole first, I was able to learn the thinking process for tasks.
I have also acquired knowledge about the functions and features of machine learning related services on Google Cloud. I think I was able to learn not only the outline but also the pre-processing steps, such as data pre-processing.
In addition, after taking the training, interest in data analysis increased, the range of in-house solution studies expanded, and it led to new proposals for functions using BigQuery.
I would like to lead with examples, as I expect it will be an important step to introduce it in the company in the future.
Reasons for choosing Cloud Ace
Before, I had taken several free seminars and trainings with Cloud Ace, and the content was easy to understand and could be implemented immediately. In addition, the profile of the instructor and the course information are described in detail on the website, which gave me a sense of security even before the course.
Also, since it is training by a company that has a top-class track record as a vendor of Google Cloud, it is a place that we could trust.
Development after the course, future objectives and expectations
First of all, I would like to brush up the chatbot service developed in-house using Google Cloud. In addition, we will build services that utilize GA4 and CRM data using BigQuery as an analysis platform, activate the study of solutions based on AutoML and Vertex AI, increase the range of solutions using Google Cloud, and suggest the appropriate cloud services in response to customers’ needs.