Data Management and Data Analytics
Structured data management is the basis for digitalization – from defining the strategy, through integration, governance and quality, refinement and visualization, to creating a new data architecture for the optimal use of company data.
Successful data management is an urgent requirement for companies to remain competitive in the era of digitalization and lays the foundation for successful digital transformation. With a data strategy that is tailored to the company, the business is optimally provided with data and supported in its daily work and its strategic decision making.
Data management issues are included in numerous technological project initiatives (e.g. big data, data lake, AI, machine learning) and ongoing banking implementations (BCBS 239, Intraday Liquidity, FinRep, GDPR). Our many years of experience show that all data-driven initiatives which are put into a company-wide context and coordinated contribute significantly to a project’s success. Our clients – banks, insurance companies and financial services providers – increasingly need to face the challenge of merging data from diverse sources, preparing it for analysis and enabling the development of new business models, products and customer services within a very short time. Optimization potentials exist in creating a reliable data source, high and immediate availability, more expedient quality and the ability to analyze data.
Business segments increasingly demand a target-driven data warehouse in order to achieve optimum support for resolving future-oriented issues. Data quality, i.e. integrity, trustworthiness and reliability of data, as the core and first step for a data warehouse, is to be achieved as a holistic task of the organization by integrating it into the processes and using appropriate software solutions.
Preparing and visualizing data in a business context and by the specialist department represent additional disciplines that demand high data quality. The specialist department is enabled to understand and optimize its own data and to generate insights from it. This not only saves time and money, but motivates departments to gather more data.
Through many years of project work our consultants have gained expertise in the most diverse requirements posed on modern data management solutions. They connect data from varied sources, integrate it into data models developed for them and use best practice methods to achieve maximum data quality, while always complying with and implementing the required governance and GDPR policies. They hold comprehensive knowledge of existing software solutions and are able to integrate them into existing on-premise and cloud architectures.
Their in-depth business knowledge in regulatory reporting, in regulations and in numerous other banking disciplines allows them to understand and analyze the needs of each specialist department. In doing so, they never lose sight of the strategy: creating a forward-looking data architecture / foundation that is able to generate added value from data and fulfills the most important disciplines:
findic’s range of services includes:
- support in all data management topics with the aim of increasing the informative value and integrity of data
- conceptual design and implementation of data intelligence to enhance the trustworthiness and reliability of data (glossary, catalog, lineage, metadata management)
- conceptual design and implementation of “voice-of-the-employee”, empowerment of specialist departments by means of data preparation, self-service BI and dashboards
- “data alignment for the future” – conceptual design and implementation of a forward-looking and analytics-enabled data architecture (ingestion, integration, data modeling, SSOT, MSOF)