With the Data Solutions Blueprints©, we are targeting primarily – but not exhaustively – high-complex use-cases from emerging industries.
In these industries, we have vast volumes of data, rising velocities, and growing varieties of unstructured data formats. These attributes accentuate the need for robust and scalable analytical data infrastructure, Artificial Intelligence and Machine Learning models, and business applications to transform data into insights and actions.
DataStema and partners have extensive experience in Industrial IoT (IIoT) and predictive analytics in the automotive industry, aviation manufacturing, industrial automation, and FMCG.
We provided custom solutions from conception, design, implementation, and personnel training. We implemented simulation systems for airport freight terminals and automatic ground traffic control aircraft for the European Consortium in the EU Transportation projects.
DataStema uses modern technologies and implementation solutions: Cloud, Data-Driven Architecture, and Event-Driven Systems – to cite a few, combined with scalable infrastructure and top hardware. Our experience with industrial systems and Big Data is the key to successful implementation.
Beyond the engineering aspect of these use-cases, we always focus on The Customer. By joining sensors and edge data with customer data, companies can provide innovative and targeted services and products to their customers; to create better experiences and drive engagements.
Our clients range from SMEs to big corporations and national state agencies from the EU and USA.
The Electric Vehicles (EV) use-cases aim to extend conventional cars by implementing an ecosystem that enables interactions between actors ranging from designers and manufacturers to drivers and services providers. A data analytics solution can provide real-time control of the smart car data stream, enabling personal, relevant, and timely services from different perspectives.
Data collected from people's driving habits and information about vehicle conditions are analyzed to understand the driver, which would help the automakers develop the vehicle reflecting the customer's needs.
The use of space technologies in communications, agriculture, forestry, transportation, and other global economic sectors increases productivity and becomes more efficient.
By exploring and analyzing all of the information satellites can collect, space data has the potential to revolutionize how we understand a wide array of industries and environmental changes.
Space data describes the camera and sensor information gathered by satellites combined with location-based data sources gathered via traditional geospatial techniques to extrapolate patterns and create AI/ML models.
Farmers can use satellite data in agriculture to better understand what factors influence crops' growth – weather patterns, exposure to sunlight, air quality, or pest activity.
In transportation services, your maps should be up-to-date and as detailed as possible to effectively set up logistics. Space data can be fed into the complex Geographical Information Systems to optimize the way the whole supply chain does.
Computer vision and data analysis technologies, coupled with drone technology commoditization, will allow businesses to create value by harnessing new insights.
Essential investment in AI/ML analytics use-cases is to efficiently use large data sets collected by the drones in an automated way with less/no human interaction.
Both autonomous and manual drone passes will enable businesses to collect data from previously inaccessible areas at scale.
The use of AI/ML algorithms already ranges across many verticals prominent in the drone industry, including agriculture, construction, transportation, and safety & security.
Wearables improve users' lives in several ways for health and fitness, personal abilities, self-confidence, and infotainment.
When collecting monitoring data, wearable devices provide local processing capabilities and grant access to cloud functionalities for storage purposes or advanced analytic features. Analytics turn collected data into the foundation needed for actionable insights providing additional consumer and company benefits.
Interactive dashboards and visualization tools facilitate the aggregation, analysis, and interpretation of the data collected.
Companies can create marketing offers customized to each consumer by analyzing the data captured by wearable technologies.
In the long run, the data collected could be further processed to infer information about the users' physiological conditions or determine specific behavioral patterns.
A Customer Data Platform (CDP) enables marketers to create a unified view of the customer – Customer 360° – by gathering data from software deployed throughout the organization and/or external data sources.
CDPs can consolidate and normalize disparate sets of data collected across multiple sensors and touchpoints into an individual profile representing the customer, lead or prospect and make this data available to other systems that deliver campaigns, webpages, announcements, alerts, and other interactions.
CDPs come with data analytics capabilities that may allow marketing end-users to define and create customer segments, track customers across channels and get insights into customer interest and intent from customer behavior and trends.
Using AI/ML predictive models for revenue attribution and surface insights about audiences, CDPs can proactively offer suggestions about the Best Next Action to move a prospect through their purchase journey.
Our Private HPC solution's main objective is to empower small and medium enterprises and startups to access affordable, modern, and user-friendly High Performing Computing resources installed at their desk or in the data center.
Modern personal computers' fast increasing hardware capacities equipped with chip multiprocessor CPUs, massively parallel GPUs, and filtering FPGAs have made large-scale sensors and geospatial data processing and analytics possible in a Private HPC environment.
Private HPC is a perfect fit for your in-house projects, from Data Analytics to fully-fledged AI/ML models that require bespoke hardware solutions with a good balance of CPUs, GPUs, FPGAs, and ASICs accelerators.
Our Private HPC solutions are highly configurable, considering client use-cases, data processing needs, the complexity of the AI/ML algorithms, the execution time window, and the existing solution's hardware limitations (if any).
You may rent, lease, or buy our AI/ML Private HPC solutions with many favorable features: low initial and operational costs, good support for data management, and excellent support for numeric modeling and interactive visualization.
We offer you support and help in your Private HPC journey