Data Strategy
Fully exploit the potential of your data
Data Strategy: Why It Is So Important for Companies
A well-thought-out data strategy is now more important than ever! To remain competitive in the midst of change, companies must engage with their data, understand it, and adapt and optimize their actions. A data strategy is a long-term plan that outlines how a company can use its data profitably to contribute to strategic business goals. The plan includes the processes and human resources required to manage the organization and defines technologies that will be used to collect and apply data. Such a plan makes work easier for everyone involved in collecting, analyzing, and evaluating data.
Develop Your Individual Data Strategy with Arvato Systems
Companies can pursue two different strategic approaches: The centralized or the decentralized Data Strategy. If responsibility for data lies in one hand, the company seeks a centralized approach. In this way, they avoid data silos, but also slow down internal processes. On the other hand, the decentralized data strategy, such as the data mesh principle, distributes responsibility within the team. Employees are given more freedom, but this comes with data governance requirements, which go hand in hand. The two strategies are not mutually exclusive; the right balance is crucial. We will be happy to advise you on how this balance can be achieved for your individual strategy.
What sets us apart is our many years of experience in developing and implementing data strategies. We identify weaknesses, take on business objectives and provide support with expertise and best practices.
What Are the Benefits of a Data Strategy?
Important Factors of a Data Strategy
Data goals
The focus should be on the question of what the company wants to achieve with the data. Which goals should be achieved, which problems should be solved?
Data sources
Where does the data come from? Companies should not only keep an eye on processing, but also on data quality and security.
Data organization
The organization of the data in relation to the business strategy is just as important. Are data domains defined? Has governance been implemented?
Data consolidation
How is data from different data sources consolidated? How do companies deal with different types and formats?
Data analysis
The right tools and methods are crucial for data analysis. Companies should define in advance which ones are to be used.
Data culture
How is data literacy promoted? Decisions should always be based on sound and trustworthy data.
Developing a Data Strategy with Arvato Systems
Carry out analysis
As part of our data strategy consulting, we support our clients in analyzing the current situation and determining the maturity level with the active involvement of employees and stakeholders.
Achieving goals
We look at your individual application scenarios and together we formulate concrete and realizable target images that contribute to your business goals.
Set up for the future
In order to realize a sustainable business model, we provide modern state-of-the-art concepts and accompany you on the way to implementation.
All-round support
In addition to developing a data strategy, we automate your work processes and offer you ongoing support from our experienced experts.
Why Arvato Systems?
Arvato Systems is an expert for your data & AI roadmap and offers you a project success guarantee based on many years of experience and intensive technology partnerships with the leading hyperscalers Microsoft, SAP, Google and AWS. We are happy to accompany you on your path to becoming a data-driven company. In doing so, we remain technology-neutral and focused on the business benefits so that we can offer you tailor-made solutions. Our goal is to increase the value of data for your company by optimizing your data volume, data quality and data usage and developing an individual data strategy together with you. For successful implementation, we offer a broad portfolio that includes various data platforms such as data warehouses, data lakes, data lakehouses, data mesh and IoT data platforms as well as self-service BI & analytics tools. We also address topics such as data governance with data catalog solutions and data quality management, master data management and reference data management.
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