Case Studies

Systematically Gaining Practical Skills and Knowledge on Google Cloud Products to Increase Performance

Members of Unerry

CTO Mr. Seika Ito

(From left)

Beacon Bank Operations dpt, data scientist, Mr. Yu Okayasu

Beacon Bank Operations dpt, data analyst, Mr. Shunta Sumikawa

Technical dpt, Mr. Hiroyasu Kuratani


Unerry developed and operates the activity data platform “Beacon Bank”, with around 2.1 mln GPS beacons nationwide. Unerry extracts data from society using proprietary IoT sensors and captures the flow of people in real time, utilizing this data for solutions such as promotions that are optimized in real time. Unerry wanted to optimize operations using Google Cloud, so we had them take Cloud Ace’s training course.

Pre-training objectives and goals

Mr. Okayasu:

The amount of activity data gathered by Beacon Bank, such as location and purchase data, was becoming very large. It was taking more and more time to extract, analyze and develop a model for the extracted data, so decreasing the time it took for these was one objective. On the other hand, since Google Cloud has many products and plans for diverse use cases, we decided to take this training in order to learn Google Cloud with the aim of designing the best architecture down the road.

In addition, our company’s members had various levels of understanding about Google Cloud, and this was producing wasteful communication. We thought that by taking the training course, we could increase the base level of understanding for all members.

Mr. Sumikawa:

Google Cloud has many products that change over time, and many new ones are added every day. We feel that catching up to these will be difficult. In addition, when we tried looking for guidance on what products to use, there was basically nothing that told us how to choose. All the documents we could find were about the functions and use of a single product, making it difficult to search through.

We believed that by changing the situation, we could focus on the analysis operation. We wanted to take the areas where we could automate the process, such as model creation and operation, to make it more efficient.

Effects and merits of training

Mr. Okayasu:

Searching for products for every case was costing us a lot, but through the training, we were able to gain knowledge and standardize our patterns (to a certain extent). This allowed us to speed up our operations by 3~4 times, and we were able to use that time for other tasks.

For example, by using BigQuery ML, we were able to pre-process, build a model, tune, and deploy using just one SQL.

Mr. Sumikawa:

Through the training, instead of suggesting solutions that are specific to the issue, I am now able to propose solutions that take a wide range of possibilities into account.

By learning about a variety of things, like data pipelines and data warehouse architectures, I am now able to think about things in the context of the whole system.

In addition, we are now able to widen the scope of analysis, and this has been useful in analyzing data. It is helpful for operations like analysis using natural language processing API, and developing algorithms using BQML within our team.


Mr. Kuratani


For our objective of utilizing the knowledge we collect, our training allowed us to experience the necessary tasks like defining product requirements, designing architectures, service-level design for product development, and others. Listening to the voices of Cloud Ace’s engineers who actually work on-site helped us gain even more useful skills.

Why they chose Cloud Ace

Cloud Ace has many engineers who have been named Google Cloud Top Engineers, and we were attracted by the fact that we could receive support for projects after the training.

Objectives and hopes after taking the training

Mr. Ito:

We took training related to security, and we got a lot of useful information and skills in a manner that was very easy to understand.

Our company had a lot of individual strengths, but the company’s expansion meant that we needed to work as a team. By taking Cloud Ace’s training, we want to standardize and improve our level of knowledge as a whole.

Mr. Okayasu:

We would like to continue learning skills and knowledges on Google Cloud’s products. We especially want to focus on BigQuery and Vertex AI, in order to speed up and level up our analysis and algorithm development.

Training they received

Through lectures, demos and hands-on labs, gain first-hand experience into designing data processing systems, building end to end data pipelines, analyzing data, implementing and structuring ML, un-structuring, and streaming data.