SUCCESSFULLY SCALE AND OPERATE DATA PRODUCTS WITH DATAOPS
Companies are increasingly faced with the daunting challenge of transferring their Data Analytics solutions to secure, robust and scalable business applications. Such a solution would typically require coordination and integration into the company’s existing IT, with these scalable Data products ultimately being operated professionally. DataOps (Data Operations) has established itself as the preferred method for achieving this result. DataOps enables us to develop, operate and continuously build upon marketable, rolled-out and productively utilized Data Products.
Our goal is to support you in securing smooth long-term operations, introducing processes and providing continuous optimization.
Data projects implemented
Use cases identified
AI and Data Experts
years of experience
Have you already implemented a Data Product or service in your company and now want to ensure that it runs smoothly? Our DataOps experts can support you in setting up processes for the stable operation of your systems while helping you to integrate them into established processes and teams.
In order to develop a Data Product into a robust, scalable and globally available business service, an operating concept or service model must be established. This includes management organization, processes, roles and responsibilities, governance (including reporting and SLA), as well as the required tool set. We offer assessment workshops to determine the current state within your company and to define a roadmap for the future, while supporting you with the help of established standards and methods in the subsequent implemented project. In the DevOps-phase the Data Project or platform is further refined and developed using tried and tested methods. Our service-catalog allows for the targeted and swift development of a service. Agreed-upon reaction and resolution times, as well as jointly-defined service levels come together to form a transparent service model, both in terms of cost and performance. The integration of offsite and shoring capacities results in economies of scale and cost reduction benefits.
Best Practice Methods
Data Science Use Cases
This webinar will explain which aspects to consider and how this has already been successfully implemented in reference projects. The Data Operations Assessment provides support in determining the status quo, fit-gap-analysis as well as in defining a roadmap for executing your next steps. The “Service Model Design” provides a concept for the standardization and professionalization of Data Operations. Potential cost reduction (e.g. through optimized sourcing approaches such as near/offshoring) are elaborated upon.
Why DataOps with [at]
Experts for DataOps
We have successfully conducted over 1.000 AI and Data Science projects. We still take care of maintenance and operation of many of these Data Products we developed.
Leader in AI and Big Data
We have been recognized as the # 1 Value Creator in machine learning by CRISP Research as well as a Big Data Leader in Germany by numerous experts.
Our DataOps Experts have your back 24 hours a day, seven days a week and are available to support you at anytime.
How fast can you start?
As a rule, we reserve the right to a ramp-up phase of 2 weeks from receipt of the order, but since our [at] colleagues coordinate very closely with our customers in advance of the project, a project start is usually possible within a few days.
Can you also support us in English?
Our employees implement projects in both German and English language.
What does Operations mean?
DataOps (Data Operations) is a widely used method to ideally support your company. We are looking for a secure, robust and scalable solution for your business applications. Continuous development and process optimization are part of our good service and ensure a smooth operation.
Which technologies do you primarily work with?
In order to be able to work with our customers as far as possible without restrictions, we work independently of technology and provide appropriate employees and experts for the most relevant data science tools and architectures.
Is the [at] only active in Germany or also worldwide?
The project focus of [at] is in the German-speaking area, we have already managed international projects and are happy to accept them.
How many sites do you have? Where are your sites located?
[at] currently has 6 locations in Germany, including Munich, Leipzig, Berlin, Cologne, Frankfurt and Stuttgart Further sites are planned for Switzerland and Austria in the coming yea
Is it possible to purchase licenses above [at] and does AT offer consulting services in this regard?
Yes, we offer licenses for different technologies, especially in the field of visualization.
We are very happy to advise you in advance and recommend the appropriate technologies for your challenges.
DataOps projects require agile working methods
Modern IT-projects require a new approach when it comes to maintenance and operation. This is due to agile methodologies as well as completely new technology. Current Data Projects and services based on Machine Learning or Artificial Intelligence no longer automatically end with the proof-of-concept. Rather, they are increasingly integrated into the ongoing operations of software-solutions, as is the case with AI-algorithms. As a result, Data Science services are in constant need of new fields of expertise, alternative know-how along with ever more agile working methods.
Operation and maintenance of these new products are extremely technically demanding, stretching the capabilities of classic service delivery models to their limits. Instead, they require a strong team of Data Scientists, Data Engineers, Data Designers and software developers
who are experienced in the implementation and maintenance of such demanding products. At the same time, companies have mastered and grown used to pre-established service models – mostly based on the Information Technology Infrastructure Library (ITIL). DataOps is the art of combining established approaches with up-to-date working methods.
Our Data Scientists have successfully implemented over 1.000 AI and Data Science projects. In addition, they possess ample experience in maintaining and operating the products they implement. You can take care of your core business, secure in the knowledge that our team of DataOps experts has your back 24 hours, seven days a week.
Data & AI Knowledge
Creating joint value from Data & AI