Data Governance
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Data & Analytics
Using (business) data efficiently
Business decisions are based on data. It is quite a challenge to manage data cross-departmentally, to protect it, to use it profitably, and while doing so, to adhere to statutory requirements such as Sarbanes-Oxley (SOX), Basel II or HIPAA. According to a 2008 Gartner study, only 10 % of all businesses succeed in their first attempt to implement efficient processes that master this challenge.
What does Data Governance mean?
Data Governance provides a set of regulations describing how to handle data. In this context, data is put in the same category as assets that are used across processes, departments and even companies (e.g. partnerships). This task focus combines organisational forms, processes, guidelines (e.g. standardised data definitions), technologies and different statutory basics. Data Governance is an important component of Corporate Governance and complements IT-Governance.
With Data Governance regarding data, the following principles are defined:
- Availability
- Quality
- Traceability
- Consistency
- Security
- Auditability
Organisational conditions
Data Governance affects the whole company. Establishing Data Governance starts at the top level of the hierarchy and is strategically transferred to the lower levels. Conflicts of interest between different units are often encountered here and require somebody with overall responsibility (Data Governor) at the top level. The actual framework is prepared by the so-called Data Governance Board. This includes representatives of the interested groups involved who provide for company-wide applicability. Furthermore, the responsibility for specific data, e.g. customer information, product information, etc. may be handled by individuals (Data Stewards) and an Integration Competency Centre (ICC) for all Data Integration concerns can be established. Successful Data Governance is in tune with the individual features of a company.
Master data: the backbone of business data
Master data describes business objects (e.g. customer, product, material). The formal properties of these objects and their stability are mandatory company-wide. The master data provides the framework for transactions or transaction data prior to orders, purchases or bookings. Inconsistencies lead to inefficient processes and the higher costs associated with them. Clearly defined responsibilities for creating, maintaining and deleting master data are essential for high quality and traceability. These requirements are covered by Master Data Management (MDM).
Data Governance with noventum
Specific measures at the company (e.g. compliance, data quality or system consolidation) are the first correct steps towards efficient data utilisation. The path to active Data
Governance requires:
- Determining the normative and statutory foundations
- Reviewing the organisational aspects
- Planning and assessing the security components in information management
- Architecture and implementation of technical processes (e.g. MDM)
- Adherence to data protection guidelines
- Setting up a continuous improvement process
- Auditing the implementation achieved
With its methodology, noventum addresses all aspects of implementation and optimisation of Data Governance and, in addition provides support in cases of an optional certification in accordance with ISO 27001. Based on a comprehensive analysis of the current situation, a comparison between statutory foundations and standards is performed. The target concept is defined in interaction with the customer and suitable measures are selected with respect to organisation, guidelines, processes and technology. noventum ensures that this is done in accordance with additional Data Governance aspects. With noventum, verifiable achievement of objectives as well as the implementation of continuous monitoring (when required) are the final measures of a Data Governance implementation.
