Dataiku Case Studies Provincie Noord-Holland: Scaling Data Science in the Public Sector

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	Provincie Noord-Holland: Scaling Data Science in the Public Sector Dataiku

Provincie Noord-Holland: Scaling Data Science in the Public Sector

Dataiku

Technology Category	Analytics & Modeling - Big Data Analytics Analytics & Modeling - Machine Learning
Applicable Industries	Agriculture Cities & Municipalities
Applicable Functions	Logistics & Transportation Quality Assurance
Use Cases	Farm Monitoring & Precision Farming Predictive Maintenance Traffic Monitoring
Services	Data Science Services
Challenge	Provincie Noord-Holland (PNH), a province in the Netherlands, embarked on an initiative to become a more data-driven organization. However, they faced challenges in determining the necessary steps to achieve this goal, including the required technology and expertise, setting up experiments, and implementing new processes. They also faced unique challenges as a public sector organization, such as the need to consider regulations and societal impact when conducting experiments and working with data. Additionally, they had to work within a closed IT environment, limiting their access to data science tools. They also realized the need for data scientists and technology to help them succeed with their data science initiatives, and the importance of being both data and business-driven to generate positive performance and encourage buy-in among organization-wide stakeholders. Read More
About Customer	The province of Noord-Holland is one of the 12 provinces in the Netherlands and is arguably the most critical piece of the Dutch economy. The province has its own flag, coat of arms, and national anthem. PNH consists of the management, provincial officials, and the board that own policy and projects throughout the province. Core tasks of the PNH include but are not limited to the province’s environment, energy, and climate; spatial development and water management; regional accessibility and public transport; quality of public administration; cultural infrastructure and monument conservation; and regional economy. Nearly 1,400 total employees work for more than 2.8 million North Hollanders. Read More
Solution	PNH hired their first data scientist and began exploring their technical needs. They decided to invest in a data science platform that encourages collaboration on data experience. After using an initial license for several weeks and compiling positive feedback from various internal groups, they signed on as a customer with Dataiku. With Dataiku, PNH was able to make significant efficiency gains, foster a team-based approach to all data science initiatives, bring data analysis in-house, apply machine learning models for projects such as traffic lights optimization and biodiversity, and standardize its data analysis processes. They were also able to more easily answer internal queries and keep analysts and other team members in the loop, promoting cross-departmental involvement and communication. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Analytics & Modeling - Machine Learning

Applicable Industries

Agriculture

Cities & Municipalities

Applicable Functions

Logistics & Transportation

Quality Assurance

Use Cases

Farm Monitoring & Precision Farming

Predictive Maintenance

Traffic Monitoring

Services

Data Science Services

Challenge

Provincie Noord-Holland (PNH), a province in the Netherlands, embarked on an initiative to become a more data-driven organization. However, they faced challenges in determining the necessary steps to achieve this goal, including the required technology and expertise, setting up experiments, and implementing new processes. They also faced unique challenges as a public sector organization, such as the need to consider regulations and societal impact when conducting experiments and working with data. Additionally, they had to work within a closed IT environment, limiting their access to data science tools. They also realized the need for data scientists and technology to help them succeed with their data science initiatives, and the importance of being both data and business-driven to generate positive performance and encourage buy-in among organization-wide stakeholders.

About Customer

The province of Noord-Holland is one of the 12 provinces in the Netherlands and is arguably the most critical piece of the Dutch economy. The province has its own flag, coat of arms, and national anthem. PNH consists of the management, provincial officials, and the board that own policy and projects throughout the province. Core tasks of the PNH include but are not limited to the province’s environment, energy, and climate; spatial development and water management; regional accessibility and public transport; quality of public administration; cultural infrastructure and monument conservation; and regional economy. Nearly 1,400 total employees work for more than 2.8 million North Hollanders.

Solution

PNH hired their first data scientist and began exploring their technical needs. They decided to invest in a data science platform that encourages collaboration on data experience. After using an initial license for several weeks and compiling positive feedback from various internal groups, they signed on as a customer with Dataiku. With Dataiku, PNH was able to make significant efficiency gains, foster a team-based approach to all data science initiatives, bring data analysis in-house, apply machine learning models for projects such as traffic lights optimization and biodiversity, and standardize its data analysis processes. They were also able to more easily answer internal queries and keep analysts and other team members in the loop, promoting cross-departmental involvement and communication.

Impact #1	Significant efficiency gains, as in some cases its data analyses previously took years and now take only a few weeks.
Impact #2	Fostered a team-based approach to all data science initiatives.
Impact #3	Brought data analysis in-house, instead of having to use external services for it, which saves both time and resources.

Impact #1

Significant efficiency gains, as in some cases its data analyses previously took years and now take only a few weeks.

Impact #2

Fostered a team-based approach to all data science initiatives.

Impact #3

Brought data analysis in-house, instead of having to use external services for it, which saves both time and resources.

Benefit #1	Reduced time for data analyses from years to a few weeks.
Benefit #2	Saved time and resources by bringing data analysis in-house.
Benefit #3	Improved efficiency in traffic light optimization and biodiversity projects through machine learning models.

Benefit #1

Reduced time for data analyses from years to a few weeks.

Benefit #2

Saved time and resources by bringing data analysis in-house.

Benefit #3

Improved efficiency in traffic light optimization and biodiversity projects through machine learning models.

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Overview

Provincie Noord-Holland: Scaling Data Science in the Public Sector

Operational Impact

Quantitative Benefit