Molecular Algorithm: A Better Approach for Data Integration

Molecular Algorithm Architecture of Data Integration

Traditionally, the problem of combining heterogeneous data sources under a single query interface is not a new one. The rapid adoption of databases after the 1960s naturally led to the need to share or merge existing repositories. This merging can be done at several levels in the database architecture. Utilization of various extraction techniques is done through extracting data from a wide variety of sources. However, different sources often have different schemas, access methods, and coverage. It may lead to ineffective data integration and indefinite query results.

Molecular algorithm provides solution for these problems. The process of this algorithm starts in the user’s query. It will be passed down in the process for reformulation of subgoals of the query and prepare it for execution. Then, when it is finished reformulating, it will be executed. The results will be coming from different data sources. It will be transported in a process for conjugation of data wherein the union of each data to become one unique data will occur. Eventually, it will become one sole data which will be the result for the user’s query.

Molecular algorithm has efficient query execution and dynamic formulation. It has reliable data methods and proficient data security. This algorithm has uniform data source access and proficient data security. It has fast query results and definite integration schemes.

Objectives of the study:

• To have a comparison between molecular algorithm and data warehousing.
• To corroborate the advantages and drawbacks of molecular algorithm