Data and Analytics Cloud Specialists accelerating your Digital Transformation.
Flexibly adapting to new business models, a constant stream of innovations, and extreme scalability continue to challenge even the most advanced enterprises. Winners today are reinventing how to use technology to their advantage. A first-class Enterprise Data Cloud is at the heart of this transformation.
Build a scalable Data Science platform for advanced analytics. Build and deploy predictive models for batch, interactive and streaming applications. Use the latest AI/ML libraries and packages and embed them in your business process so you create a truly intelligent enterprise: optimize forecasts across complex supply chains. Personalize marketing and sales. Detect product defects faster and with greater accuracy. Optimize pricing, promotions, shelf and replenishment across billions of SKUs. Infuse simplistic business processes with intelligent decision-making.
A cloud data platform needs to Ingest data from many data sources. Data formats can vary from highly structured to unstructured. To ensure high data quality, data pipelines must systematically validate all incoming data and handle all exceptions and violations. Data can be stored in files, NoSQL-scale-out-databases or classic RDBMS. A powerful Data Warehouse provides low-latency queries and intuitive reporting functionality.
Capture machine and sensor data and send them to the cloud. Store high-frequency device data in scale-out databases or cost-efficient object storage. Detect data quality issues or threshold violations in high-speed data-in-motion. Create and deploy machine learning models to optimize maintenance or predict product quality. Run advanced analytics on streaming data. Monitor devices and operations via intuitive dashboards and push alerts and notifications to users in real time.
Cloud computing has its own rules and requires particular skills. We are carefully developing and nuturing our own expertise to optimize your cloud deployments.
Not every organization really has a Big Data challenge, every data lake contains data sets that are too big for processing with a single server. It is essential to understand all the options for multi-node- and cluster computing in order to process small big data.
Selecting the best mix of open-source software and cloud-native proprietary services. Finding the best trade-off between portability, convenience and rich functionality might the single most important success factor to minimize vendor-lock-in and to preserve all future options for your Data + Analytics cloud.
To benefit from cloud scale effects and its lower costs it is necessary to consume resources much smarter than on-premise: dedicated resources for continuous workload, on-demand whenever it is needed, spot deployments for long-running batch jobs and serverless functions for burst-outs.
Managing Artificial Intelligence and Machine Learning are different from classic software engineering or data warehousing. Data-driven, predictive applications require specialized tools and need to be managed accordingly: from integrating intelligent functions into your business processes to ensuring model performance meets your business requirements.
Digital products don’t exist in isolation. Classic systems-of-record still contain critical information about customers, products and transactions. We help you integrate them with your data and analytics cloud to fully contextualize the data.
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Cloud computing ushers in a new age of enterprise computing.
But a simple lift-and-shift approach comes with many risks.
Read our Cloud Risk Analysis report to learn about the top 5 cloud risks.
This is why we highly value our competence portfolio and manage it strategically. We are constantly observing the market and update our core skills to make sure we can always offer our clients the best advice.
Start your cloud journey with Wireframe.digital now.
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