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Data Management on Cloud

End-to-end portfolio for intelligent IT and business models

Digitalization has ensured that almost everyone and everything leaves behind data. And there are more every day.

The variety of available data, such as product, customer, process and expiry and employee data, provides knowledge and information that can be the decisive advantage in international competition. Companies that quickly learn to generate knowledge and information from data can already operate significantly more successfully in the market today.

Now with Data Management on Cloud

Replace obsolete technologies.
Avoid large investments in new hardware or licenses.
Provide an adequate scaling strategy for data growth in the coming years.
Modernise the company-wide data architecture and enable innovative business models.

Requirements for Modern Data Management

Companies have to adapt to data, learn how to handle data and professionalize. In addition to individual measures, data management along the value chain must be considered.

Acquision & Processing

Storage

Analysis

Governance & Privacy

Effective data acquisition & processing

Structured and unstructured data of all formats must be able to be recorded and processed without any problems. This requires maintenance-free native interfaces for the efficient connection of source and target systems. 


For further processing of the data, the transmission speed and computing power must match the data volume.


Furthermore, the stability of the operation must be guaranteed. This can be achieved through a homogeneous technology stack and coordinated, automatically maintained services.

Efficient data storage

An ever-growing volume of incoming data must be securely stored and efficiently made available for job execution in seconds and for analysis workloads. The storage infrastructure has to adapt intelligently to the growing data volume. 


Partial data sets should be stored at optimal cost depending on the respective access frequency, without additional maintenance or operational effort. 

Intelligent analysis of data

It must be possible to analyse and evaluate data holistically and coherently, including machine learning and AI technologies. If this requires large data memories, these should only be available temporarily for the duration of the analysis in order to save costs. 


In order for data scientists to work efficiently with the latest versions of the tools for business insights and analysis, these should be available in environments suitable for collaboration. Without a maintenance window for installing patches or updates. 


Um den Aufwand von Datenanalysen, Prototypen und das Ausführen von datengesteuerten Anwendungen zu minimieren, bedarf es einer integrativen Umgebung, wobei die Entwicklung und Dokumentation mit den für Data Scientisten gängigen Sprachen und Werkzeugen erfolgen muss. Hierüber sollten auch interaktive Visualisierungen und Business-Intelligence Funktionen über alle Datenquellen entwickelt und verwaltet werden können, so dass Benutzer im Self-Service eigene Dashboards und Reporte erstellen und für interne und externe Konsumenten publizieren können. 
 

Comprehensive Governance & Privacy Management

An increasing number of stakeholders must be provided with simple yet secure and authorized access to the right data. At least the same level of data protection and data security should be applied as in an on-premise solution. In cloud environments, large cypersecurity teams operate state-of-the-art security controls down to hardware and firmware level to provide the highest level of data security. 


Date lifecycle management must ensure that changes and deletions of personal data are logged in compliance with DSGVO and passed on to downstream systems. 


Redundancy must ensure that the data is available and can be restored in an emergency in case of temporary hardware failures. To provide a further level of protection for local emergencies or natural disasters, it should be possible to replicate data across data centers or geographical regions. 
 

Modern Data Management Thanks to Cloud Infrastructure

The cloud is not only the right foundation for Modern Data Management because of its simple and fast scaling: Cloud platforms also provide a comprehensive set of ready-made services, frameworks and tools. The cloud enables you to upgrade your data management for the data age. We can help you with this!  


In order to position you successfully in the data-driven business, we look at the entire data value chain with you and offer you a comprehensive portfolio for your data-driven business - from infrastructure to individual use cases.

Your quick start - Data Management on Cloud Starter

With our entry-level package Data Management on Cloud Starter we implement your first concrete breakthrough to modern data management in just two steps. In an initial analysis, we gain an overview of your initial situation and evaluate a first concrete use case with you. Afterwards, we quickly implement this in a Proof of Concept (PoC).

Data Management on Cloud Starter

Initial Workshop
  • Introduction to Data & Analytics services and frameworks
  • Analysis of the existing data and system landscape
  • Analysis of potential technical hurdles and efforts
  • Evaluation of a relevant pilot use case 
  • Identification of required data sources
  • Solution concept
Implementation Pilot-Use Case
  • Setup of the Cloud account structure
  • Setting up a landing zone for raw data 
  • Data-Onboarding: Construction of necessary ETL pipelines
  • Creation of a rights and roles model

Your Long-Term Benefits

Competitive advantages through knowledge advantage
Agility through real-time information
Risk limitation through intelligent forecasts and predictions
Reliability and security through comprehensive governance concepts

We Are Your Partner for Data Management on Cloud

Multi-disciplinary everything from one source
Implementation strength thanks to AI Competence Cluster
Range and depth of services
Multi-cloud expertise

Our Multi-Cloud Expertise for You

Amazon Web Services
Google Cloud Platform
Microsoft Azure

Your Contacts for Data Management on Cloud

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Christian Scholz
Expert for the Google Cloud Platform
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Mathias Lopass
Expert for Microsoft Azure
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Tina Marx
Expert for Amazon Web Services