About me
Self introduction
› Analysis to drive service/project growth.
› Analysis to promote business improvement within LINE Fukuoka Corp.
› Manage Analytical Projects / Products.
My Roles
Skills
› Data analysis processing using the R language in general.
MAEDA Kazuhiro
› Develop center – DataLabs – Data Analysis Team
› Team Manager, Data Scientist
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Agenda
› Introduction of LINE Fukuoka Corporation
› Issues in Operation Tasks of LINE Fukuoka
› VIIM Project
› Centralized Prediction Project
› In future direction
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Introduction of
LINE Fukuoka Corporation
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The 4 Roles of LINE Fukuoka
Our Business
Business Planning
Engineering
Creative Works
Operations
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Issues in Operation Tasks of
LINE Fukuoka
for ”always data driven”
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for “always data driven”
Three basic phases
the data
Collect
the data
Apply
the data
Analyse
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for “always data driven”
Three basic phases
Collect
Consolidate and manage
relevant data in one place
› Automatically collect
diverse data
› convert to an easy-to-
use format for analysis
Analyse
Analyze aggregated
data
› Calculate metrics to
deal with
› Visualization
› Extract issues
etc…
Apply
Implement Analysis
Results
› Planning of business
plans based on time-
series forecasts
› Apply machine learning
etc…
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The three NOs we had
Issues that Prevent Data Driven in LINE Fukuoka
NO integrated data collection for operations
NO metric measurement and/or visualization framework
NO cross-organizational projects in data application
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From NO to BUILD
Three approaches for data driven
BUILD integrated data collection for operations
BUILD metric measurement and/or visualization framework
BUILD cross-organizational projects in data application
Purposes of this project
› Consolidate and visualize data that
management and field members
can use to make decisions
› Based on visualized data, the
environment/system for
improvement measures and future
directions is constructed.
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Cross-Organizational Project Structure
› PM/PdM, requirements definition
› dashboard construction
Digital Planning Team
› application development
› construction of data acquisition systems
Global Operation Team
› overall system construction
› in-house IT support
Work Improvement Team
› data pipeline construction
› dashboard construction
Data Analysis Team
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Architecture of this system
Referred
DB
other
Products
Data Lake Data Ware House
CMS
CMS
Log data
DB
Files Storages
LINE Fukuoka DB
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Dashboard Visualization
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Achievements
Consolidate data from many departments into one place
Build a visualization platform for KPI metrics
Reduce field operational costs
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Time series forecast of workload
Centralized Prediction
Project
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Purposes of this project
› Established a framework for
predicting workload that affects
the operation
› Delivering more accurate
predictions using data science
techniques
Centralized
Prediction
Project
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Dashboard
Architecture of this system - batch
Input data
storage
manipulating
data
training, predicting
Raw data
Events
model: DeepAR, prophet,
etc…
predicted
result
Dashboard
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Online time series prediction tool
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Achievements
Provide accurate predictions
Flexible design for predictive systems
Both online and batch systems are available
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In future…
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Toward true data driven
Three approaches for data driven
Building a more efficient data management and operational structure
Building an integrated framework for time series forecasting
Streaming other operations using machine learning