Business Intelligence is experiencing a rapid transformation. The focus is shifting from the evaluation of historical data stored in Data Warehouses to Big Data and Predictive Analytics - the "glimpse into the future". Successful Business Intelligence effectively combines both approaches. Our consultants understand both worlds and assist you in your projects.
Modern procedures and new technologies are the foundation for optimized added value.
Whether we are talking about classic business intelligence in the data warehouse or advanced analytics in Hadoop or Spark, the analysis of historical data is needed for various reasons. Common examples of this are KPI reporting and Management Cockpits. The integration of new data sources with the latest technologies enables data-driven decisions and process optimization. The combination of these solutions provides new insights for departments and management - the "glimpse into the future".
This topic raises a variety of questions:
- Which questions can be answered with the latest methods?
- Which processes are required for this?
- What needs to be done with regard to data protection and security?
- Which possibilities exist for the optimal combination of data warehouses and Hadoop clusters?
We understand the interdependencies at the different levels and consider different aspects of your challenges.
Agile methods, expertise and technical affinity.
Our consulting spectrum includes the development of modern data warehouses and analytics solutions. We combine the necessary tools, infrastructure and industries for optimal solution development. Our deep understanding of agile methods enables us to work product-centered and deliver results early on. Our in-depth knowledge of enterprise architecture management ensures the optimal integration of all BI components within your company.
Are reports and their underlying KPIs transparent and consistent? Are evaluations based on historical data successful or can we look further into the future using algorithms? Which roles will be required in the BI environment to optimally cover business requirements?
Get recommendations for your business intelligence projects with our maturity level analysis.
Successful data warehouse projects require sound expertise and an efficient approach. In data warehousing, we rely on Data Vault methodology. Thereby, data models remain flexible and scalable, agile procedures are supported, and project results become tangible at an early stage. As certified Data Vault developers, Scrum Masters and experienced project managers, we support you in the implementation of your data warehouse projects - independent of the database, automatable and cost-efficiently.
In cooperation with our Swiss partner 2150 GmbH, we developed the Datavault Builder™, an enterprise tool for visual data warehouse design. From staging to the business layer, data is extracted from any source and made available for reporting tools such as Qlik or Tableau. This enables agile data warehouse development and delivers results that can be seen at an early stage - automated and cost-efficient. Experience the advantages of our tool in a reference project in the field of life sciences.
Can we convince you of the advantages of Datavault Builder™ in a 3-day proof-of-concept?
We design and implement sustainable Hadoop architectures. On-premise or cloud-based. Centrally or globally distributed. Scalable and secure. Our certified Hortonworks architects support the design of the Hadoop infrastructure and accompany their big data use cases in tool selection, data ingestion, data governance and data security. Learn more about our services using the example of a reference project.
From use case generation to production start-up - our data science team accompanies you from the very beginning. Together we define the factors for success and deliver immediately applicable results.
Appropriate visualization included. Python, R, SPSS, Spark, Hadoop or D3 are just a few of the tools we use for data science issues. Try us out in a use case.
When a system gets replaced, existing data will be migrated to the target landscape. Data migrations are complex projects with special features. Data consistency and quality play an important role. Costly manual reworking is avoided by good preparation and high quality of the migration. This saves resources for the company after the go-live. Technical conditions - such as the overall duration of the migration - must also be considered.
Our consultants are experienced in a variety of source systems. They understand the numerous aspects of data migration projects, on a business as well as a technical level. With our approach, tried and tested in various migration projects, we accompany your project from kick-off to the hypercare phase. Learn more from one of our reference projects.