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SUCCESS STORY — GLOBAL SHIPPING COMPANY

Global shipping company — Data Science: from R&D to industrialization

In a highly competitive market, the shipping company chose to invest heavily in R&D. KPC frames, builds and industrializes its Data Science projects.

Data

Qlik

Data

The impact in numbers

5 years

of support

The impact in numbers

5 years

of support

The impact in numbers

5 years

of support

Background & core challenges

Innovation requests of every kind

A major player in international freight: shipping, port handling and inland logistics.

The innovation requests range from forecasting demand at a given moment to optimizing fuel consumption through the choice of shipping routes.

Translate the business problems into analytical challenges

Bring in heterogeneous data, including IoT

Deliver solutions the business can use, within the client's IT standards

Background & core challenges

Innovation requests of every kind

A major player in international freight: shipping, port handling and inland logistics.

The innovation requests range from forecasting demand at a given moment to optimizing fuel consumption through the choice of shipping routes.

Translate the business problems into analytical challenges

Bring in heterogeneous data, including IoT

Deliver solutions the business can use, within the client's IT standards

Background & core challenges

Innovation requests of every kind

A major player in international freight: shipping, port handling and inland logistics.

The innovation requests range from forecasting demand at a given moment to optimizing fuel consumption through the choice of shipping routes.

Translate the business problems into analytical challenges

Bring in heterogeneous data, including IoT

Deliver solutions the business can use, within the client's IT standards

Our approach

From framing to calculating the ROI

Example use cases: estimating mooring zones from AIS data, vessel occupancy rates 15 days out, route optimization based on weather, forecasting shipments and empty containers, detecting illicit trafficking in containers.

Oversight

Framing with IT and the business

Defining the needs and objectives with the IT and business teams, framing the Data Science projects, overseeing risk, cost and the unexpected.

Big Data & Data Science

Building the models

Bringing heterogeneous data into the Hadoop platform (Hortonworks), statistical models, Machine Learning and Deep Learning with R, Python, SAP Predictive Analytics, SAS and SPSS, with delivery through Qlik Sense.

Python

Hadoop

Qlik Sense

Industrialization

Industrialize

Packages and web applications for the business, integration into the client's IT environment, tracking the results, tuning the models and calculating the ROI.

Our approach

From framing to calculating the ROI

Oversight

Framing with IT and the business

Defining the needs and objectives with the IT and business teams, framing the Data Science projects, overseeing risk, cost and the unexpected.

Big Data & Data Science

Building the models

Python

Hadoop

Qlik Sense

Industrialization

Industrialize

Packages and web applications for the business, integration into the client's IT environment, tracking the results, tuning the models and calculating the ROI.

Our approach

From framing to calculating the ROI

Oversight

Framing with IT and the business

Defining the needs and objectives with the IT and business teams, framing the Data Science projects, overseeing risk, cost and the unexpected.

Big Data & Data Science

Building the models

Python

Hadoop

Qlik Sense

Industrialization

Industrialize

Packages and web applications for the business, integration into the client's IT environment, tracking the results, tuning the models and calculating the ROI.