The specialist area of Enterprise Data Management (EDM) focuses on the structured, logical and business-wide setup, management and monitoring of data and data quality. Realdolmen implements solutions in the following areas, both on-premises and in the cloud. We can provide you with our expertise in each of these separately, or across the board; much will depend on the organization's strategy or the driver for change, whether legal or other reasons.
Data quality is an important prerequisite for good data analysis, because it is the principle of "garbage in, garbage out" that applies. Many companies today are still wrestling with data quality problems, such as duplicate, inconsistent or incomplete data. However, good data are important to be able to deliver reliable information and make the right decisions. Our expertise can help companies by using audits, algorithms and standardization to improve their data quality, and also by monitoring their data quality actively and pro-actively.
Master Data Management
Master Data Management (MDM) starts with data quality, but then goes to the next level in the data hierarchy and centralizes master data (reference data) such as customers, suppliers and items. Many companies still struggle with the fragmentation of their IT landscape, where different critical data is stored in different silo applications. By capturing their master data from across all the different systems, then integrating and managing it in a single central location, they can obtain a reliable and above all, uniform view of their data. The final goal is arrive at so-called "golden records". These are unique records that contain the most complete information available about a certain master data item, like a 360 degree view of a customer. Which data is processed as master data varies of course by company and by sector. It depends which data play a key role in the company's business activities.
For data governance, structural clarity is the watchword, and monitoring of data boils down to implementing a strategic data policy for stakeholders and managers, with standards, work flows and policies.
Sometimes it is a law or regulation that forces companies to think about better data management. The new European privacy legislation, GDPR, requires new procedures, for example, for the collection and storage of personally identifiable information (PII). The right to be forgotten is also included in the new legislation. The GDPR can then be used as an opportunity or "pilot" in this respect, in order to organize your customer data, rather than seeing it as an additional cost, given that certain analysis approaches for e.g. PII are an inherent part of any MDM implementation.
Whenever you move to a new IT system, for whatever reason, there is a need for data migration. Maintaining data quality is one of the priorities here. Our experts can map out your data migration path and use ETL to ensure it is implemented seamlessly. ETL stands for "extract, transform and load": taking the data from a source, converting the data using defined rules, or combining data from different sources and then uploading the data and storing it in the new system.
An important component of Master Data Management is Metadata Management. Metadata Management means managing the "data about data". It enables both the business and IT to maximize the business value of their information sources, by giving them a comprehensive and clear overview of the metadata within their organization. This can be used as the basis for data intelligence applications for data analysts, data scientists, data stewards and data engineers who are working on big data analysis, data governance, cloud and application modernization and data security.
Our experts can integrate any types of data sources: ranging from Excel, PDF or Word files, to databases and cloud platforms, even to hybrid platforms. We offer both on-premises and cloud solutions, or a hybrid combination.