Why Data Analytics?
- Understand how the different variables in your municipality interact and what influence they have.
- Know when it is the right time to make organisational and operational changes and when not to.
- Respond when societal and economic changes require it.
- Ensure that systems consistently provide data for decision-making.
- Control whether the decisions made lead to success or not.
We have the answer for your problems.
ManageNow® for Data Analytics (MN4DA) is our ready-to-run software solution for aggregating and analysing a wide variety of data to address diverse urban issues. In addition to generating simple reports, MN4DA enables users to visualise data and results and to identify and quantify dependencies between different data sets through interactive dashboards and correlation analyses. Complementary machine learning capabilities can also be used to make predictions and trigger automated actions.
Our complementary data science services support the design and application of appropriate data analysis methods and modules. Customer-specific use cases are best developed within the framework of co-creation approaches.
We visualise your data according to your requirements.
Within our ManageNow® for Data Analytics platform user interface, we visualise your data using various graphical representations such as:
- Pie charts, line charts and bar charts
- Histograms and scatter plots
- Static counts, totals and averages
- Word clouds
- Location of geographical data on maps
- Time series charts
In addition, we are happy to create customised and usecase-specific dashboards for you.
We support all types of data.
With the combination of an open-source in-memory index database, a search engine and an open-source file system, MN4DA is able to store all types of data, such as static and dynamic data (streaming data), historical data, simulated data, real-time data, well-structured time series, semi-structured log files, unstructured documents or multimedia data. These data types can be stored in the distributed main memory and / or in a distributed persistent storage. The amount of data that can be stored in the distributed system is not limited, as MN4DA scales linearly with the number of nodes.
We offer flexible service models based on your needs.
Our service models are tailored to your individual needs. We offer:
- Platform | The data analytics technology MN4DA will be provided.
- Multi-cloud service | As a container solution, MN4DA can be run on and moved between any cloud-based and on-premise infrastructure.
- Managed service | We provide the platform and take full responsibility for its operation and maintenance.
- Consulting services | With our Data Science and Data Management Services, we support you in getting the most out of your data. In co-creation workshops, we derive use cases and recommendations for action together with you.
The technical setup
It only takes a few steps to be able to use ManageNow® for Data Analytics:
Traffic data platform
- The variety of road users is constantly increasing.
- Roads are overcrowded, emissions are increasing and there is a threat of fines and driving bans.
- The network of cycle paths is inadequate.
ManageNow® for Data Analytics
- Traffic, environmental, geospatial and urban data, external sensor data and additional information can be aggregated, graphed, analysed and correlated.
- Visual correlation and regression analyses help you to implement the best traffic-specific measures.
- Higher quality of life through less car traffic, less congestion, more effective utilisation of public transport and traffic routes as well as better air quality.
- Well-founded, data-based decisions can be made. The implementation and success of measures can be evaluated.
Smart waste disposal
- Waste bins are emptied according to set rhythms and routes.
- At individual hotspots, the bins are often overfilled.
- Refuse vehicles block traffic, cause noise and emissions.
ManageNow® for Data Analytics
- Using sensors, disposal bins become "intelligent" and continuously report their current fill level to MN4DA.
- When a certain fill level is reached, actions can be triggered.
- Using AI, it is possible to forecast fill levels taking various data into account.
- Higher efficiency and lower costs of waste disposal: Only the filled bins are given attention.
- Higher citizen satisfaction, as overflowing waste bins are a thing of the past..
- Minimised emissions due to optimised routes for the refuse collection vehicles.
- Traffic searching for parking spaces causes congestion and emissions.
- Unauthorised parking obstructs traffic.
- P+R parking spaces are overcrowded.
- Electric cars search for parking spaces with free charging columns.
ManageNow® for Data Analytics
- Sensors are used to record where free parking spaces can be found.
- It provides various information on parking space utilisation, free parking spaces, parking duration, etc.
- People looking for parking spaces can be navigated to the free spaces.
- Higher utilisation of parking spaces or charging stations through data-driven parking space management.
- Efficient identification and tracking of parking violators.
- Improved quality of life for citizens through reduced parking space search traffic.
Virtual Coffee Break
Watch the recording of our Virtual Coffee Break "Data is Queen: Intelligent data analysis for cities and municipalities" (in German) from 24.02.2021 here.
Moderated by Stefanie Horn (IT Consultant & Business Developer, Fujitsu), while Marco Brunzel (Head of Digitalisation and E-Government, Metropolregion Rhein-Neckar GmbH) and Dr Katrin Schleife (IT Consultant & Business Developer, Fujitsu) discussed the role of urban data and data ecosystems for smart cities and regions. Central questions were:
- Which data and analyses do cities and municipalities need in order to achieve added value for citizens and the administration?
- How do we get out of the data silos to enable data-driven decisions?
- How can we link data in a meaningful way to ensure sustainable mobility in cities and regions?
- How do we get key stakeholders to collaborate within Smart City ecosystems?
Cities on their way to intelligent mobility
Fujitsu is one of the world's leading providers of technological support for public administrations. Important portfolio components of the company are comprehensive solutions for the utilisation of immense amounts of data, such as those that arise in the field of urban mobility. This includes static data, for example on public transport routes, the location of bus stops, access roads and parking spaces, etc., but also vast amounts of dynamic data; for example, on the use of buses, trains or sharing vehicles (bicycles, e-scooters or e-cars, etc.) by citizens and on air quality. The aim is to use statistical methods and forward-looking technologies, such as AI and machine learning, to enable an intelligent analysis of all relevant data in order to make mobility in cities more sustainable and connected.
How data gets cities moving
Together with the decision-makers from the city and municipality, Fujitsu analyses which data is available in which quality as well as which data is additionally required for Smart City approaches.
This determines how the data can be sensibly collected, stored, integrated, analysed and visualised, and which platforms and solutions are suitable for use. With ManageNow for Data Analytics, Fujitsu offers a central data and analytics platform that, in combination with the expertise of Fujitsu Data Scientists, represents an all-round service for public and private organisations. City data dashboards can be used to visualise urban data and select it for more complex analyses. Of central importance in this context: the topic of data protection, which is a particular focus in the public sector. For Fujitsu ...