Technological Thoughts by Jerome Kehrli

Data management comprises all the disciplines related to managing data as a valuable resource.
Data Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise.

During my MS studies, I followed two interesting lectures related to Data Management.

• Introduction to Data Mining (Summary)
• Introduction to Information Retrieval (Summary)

Data Mining is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. In the context of Data Mining, Data Warehouses (DW) form an important aspect. Data Warehouses generalize and consolidate data in multidimensional space. The construction of DW is an important pre-processing step for data mining involving data cleaning, data integration, data transformation.
I have summarized all the notes I have taken during the Introduction to Data Mining lecture as well as some of my solutions to the exercises within the following document : Summary of the Data Mining Lecture.

Information retrieval (IR) is finding material (usually documents) of an unstructured nature (usually text) that satisfies an information need from within a large collections (usually stored on computers). Information Retrieval is a field concerned with the structure, analysis, organisation, storage, searching and retrieval of information.
Here as well I have summarized the notes taken during the lecture within the following document : Summary of the Information Retrieval Lecture.