How LINE Adopted Datalore as Its New Data Analysis Platform
Have you ever struggled to keep up with the growing demand for data analysis in your organization? LINE Corporation (now LY Corporation), a Japanese internet company known for its communication app, went through similar challenges as it saw its data analysis needs grow beyond the resources available.
Explore the LINE Corporation story and discover how they freed up internal development resources using Datalore.
Could you please introduce yourself?
My name is Seongduk Cheon. I am a Senior Manager at LINE Corporation, leading an organization called the Data Platform Department. Our mission is to democratize the use of data and provide a platform for users within the company to analyze data.
What kind of projects is LINE involved in?
We provide services in various areas such as media, commerce, and fintech, based on the communication application “LINE” which has 193 million MAUs (monthly active users) globally and 94 million MAUs in Japan.
The Data Platform Department provides users with a platform for collecting, storing, managing, and analyzing data from LINE’s various services. Called IU or Information Universe, this is the company-wide data infrastructure that contains the data of various businesses.
Problems to solve
What made you look for Datalore or alternative solutions? What challenges did you face?
In recent years, the demand for data analysis within the company has increased. Requests for notebook solutions have grown well beyond simple query execution, especially from data scientists and machine learning engineers. OASIS, the in-house notebook solution we had been using, lacked the development resources to meet these diverse needs.
We began evaluating new notebook solutions, and Datalore was one of the candidates.
During the evaluation process, we found that Datalore’s UX was familiar to our developers, and the report-sharing functionality was easy to use.
Thanks to the collaboration of our engineering team and the Datalore development team, we managed to satisfy our workflow and data governance requirements:
- Client mode support for Spark
- Support for native R packages
- Enhanced audit logging
- Fine-grained permission management for reports and workspaces
These features were critical for us, and we decided to choose Datalore as our data science platform.
“We are also pleased to see that Datalore is being used by many more users than we initially expected, including those in roles other than data engineering and data science. Ultimately, we expect Datalore to be used by several hundred users in LINE.”
— Seongduk Cheon, a Senior Manager at LINE Corporation
The Datalore experience
Who uses Datalore in your team?
Although Datalore was deployed in LINE quite recently, nearly half of the data analysis teams within both the LINE Group and the Group companies are using Datalore as of March 1, 2023. We are also pleased to see that Datalore is being used by many more users than we initially expected, including those in roles other than data engineering and data science. Ultimately, we expect Datalore to be used by several hundred users in LINE.
Has the onboarding process changed after adopting Datalore?
First, the barriers to the introduction of Datalore were not high. While we received some questions from users at the beginning, the familiar UI/UX made it easy for those who had been using our in-house solutions, OASIS and Jupyter, to get started.
Second, the biggest challenge for our users was executing jobs in Spark’s client mode. Through the collaboration of our development and Datalore support teams, we managed to solve this issue.
Third, there was a gap between the Datalore product concept and LINE data governance in terms of authority management, which brought some difficulties. Thanks to collaborative discussions with the Datalore development team, we were able to clear this gap and officially adopt Datalore.
What kind of data do you work with? How do you share the results of your work?
Since we are a data infrastructure provider, we don’t know the details of the data. Those who have access to IU (Information Universe) import and analyze data through Datalore.
We usually share results of our work by publishing Datalore report links to organization wikis, and we find the reporting features very useful.
“Since Datalore has just been deployed, we managed to free up internal development resources when we decided to switch from our in-house data science platform to Datalore. We also managed to satisfy our data governance requirements, which was critical for LINE compliance policies.”
— Seongduk Cheon, a Senior Manager at LINE Corporation
How do you think LINE will benefit from using Datalore?
Since Datalore has just been deployed, we haven’t had a quantitative evaluation for the returned value yet. However, we managed to free up internal development resources when we decided to switch from our in-house data science platform to Datalore. We also managed to satisfy our data governance requirements, which was critical for LINE compliance policies.
We expect that the introduction of Datalore’s notebook solution will promote data-driven decisions by those who have a role in data analysis within the LINE Group. If the results of data analysis can be deployed smoothly and quickly in the various business divisions of LINE, it will contribute to the business by enabling faster PDCA cycles and more data-driven decision-making.
Get Datalore for your team
Are you ready to advance your data analysis practices like LINE Corporation has? Schedule a demo with us to discover how Datalore can help you on this journey.
The Datalore team
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