Data management
We deal with processes such as acquiring, filling, validating, storing, and processing business data to ensure a fast transition to a new system.Data Integration & Access
Data integration involves combining data from several disparate sources, which are stored using various technologies and provide a unified view of the data.
Data integration becomes increasingly important in cases of merging systems of two companies or consolidating applications within one company to provide a unified view of the company's data assets. The later initiative is often called a data warehouse.
The benefit of a data warehouse enables a business to perform analyses based on the data in the data warehouse.
Data Quality
Quality data is useful data. To be of high quality, data must be consistent and unambiguous.
When data is of excellent quality, it can be easily processed and analyzed, leading to insights that help the organization make better decisions. High-quality data is essential to business intelligence efforts and other types of data analytics, as well as better operational efficiency.
Data Preparation
Data preparation involves the rationalization and validation of data to make sure data is formatted consistently and that the data will be understood once removed from its source. It can involve changing the formats of dates, for example, or deleting duplicate fields.
Data preparation efforts are often needed during the integration of disparate applications that occur during merger and acquisition activities, but also when siloed data systems within a single organization are brought together for the first time in a data warehouse or big data lake/repository.
Data Governance
Data Governance is a collection of practices and processes which help to ensure the formal management of data assets within an organization.