DATA QUALITY AND DATA INTEGRATION

Data Quality and Data Integration



Data Quality and Data Integration

Introduction

The study is related to the, are data quality and data integration two different things or the same and can we have one without the other. In relation to this, whether data quality or data integration is more significant is a fair question, which is really not that easy to answer. In order to best address, are data quality and data integration two different things, it becomes necessary to discuss both data quality and data integration to ensure that there is a full understanding of both of them. From that point, it can be seen where they come together and whether one can function appropriately.

Discussion

Data Quality

Data Quality refers to the processes, techniques, algorithms and operations to improve the quality of existing data on companies and organizations. However, data quality generally refers to improving the quality of the data of natural persons and legal entities, they are probably the data they tend to degrade more and whose most striking lack of quality on productivity of organizations (IBM InfoSphere, 2011). The main benefits of data quality are;

- Save direct costs to avoid having duplicate information and thus avoid sending letters replicated to the same customer.

- Enhance marketing activities and management: improved file normalization and data analysis enables precise segmentation for your marketing and management gain in accuracy and efficiency.

- Optimizing the acquisition and retention of clients with the correct data, improved response rates and the customer feels completely identified with the company.

- Improve corporate image: the customer only receives the shipment applies, once and with correct data.

- Improve service: faster identification of the client calling a call center, reducing waiting times, leaving the operator time to focus on the business message (Mailvaganam, 2011).

The data quality management is a method of information management with the objective to manage and compare data across different information systems or databases of a company. In general, it is to transform data into useful information quality that are critical to the company.

Data Integration

Data integration is the process of combining data of different themes, content, scale or spatial extent, projections, acquisition methods, formats, schema, or even levels of uncertainty, so that they can be understood and analyzed. There is often a common display method used with integrated data sets, which, although they are not fully processed, allows information to be passed between them. Integrating different types of data in a GIS often provides more information and insight than can be obtained by considering each type of data separately. Data Integration is the process of combining data from different sources for their consistent representation in the broad sense, the process of establishing a regular exchange of data between various companies.

In order to make informed decisions, organizations need a reliable system of data. Such a system should include both current and historical data from operating systems to be able to identify trends and predict future results. The technology of data integration is the key ...