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Department of Artificial Intelligence and Data Science <\/strong>Organized guest lecture for III AI&DS Students for the course of The students gained valuable knowledge on how to design and implement schemas, as well as how <\/p>\n Department of Artificial Intelligence and Data Science Organized guest lecture for III AI&DS Students for the course of \u201cCCS341 Data Warehousing\u201d in the topic \u201cDimensional Modeling and its Schema\u201d on 16.10.2024 between 09.30 A.M to 11.00 A.M in Engineering Seminar Hall. The expert member Dr. S.Nickolas, Professor, Department of MCA, National Institute of Technology (NIT), […]<\/p>\n","protected":false},"author":32,"featured_media":27145,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[87],"post_folder":[],"class_list":["post-27144","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-events","tag-ai"],"yoast_head":"\n
\n\u201cCCS341 Data Warehousing\u201d in the topic \u201cDimensional Modeling and its Schema\u201d on 16.10.2024 between
\n09.30 A.M to 11.00 A.M in Engineering Seminar Hall. The expert member Dr. S.Nickolas, Professor,
\nDepartment of MCA, National Institute of Technology (NIT), Trichy, Tamil Nadu delivered his lecture.
\nThe guest lecture covered the following key topics in Dimensional Modeling and Schema:
\nIntroduction to Dimensional Modeling:<\/strong> The speaker began by explaining the concept of Data
\nwarehouse and followed by dimensional modeling, its importance in data warehousing, and how
\nit helps in simplifying complex queries in a data warehouse environment.
\nSchemas in Data Warehousing:<\/strong> The session covered the three main types of schemas\u2014Star
\nSchema, Snowflake Schema, and Galaxy Schema. The speaker illustrated how these schemas
\nare used to organize and structure data for better accessibility and analysis.
\nStar Schema<\/strong>: The simplest schema with a central fact table connected to multiple dimension
\ntables. The advantages of using star schema in terms of query performance and simplicity were
\nemphasized.
\nSnowflake Schema:<\/strong> An extended version of the star schema where dimension tables are
\nnormalized. The speaker discussed scenarios where snowflake schema could be more efficient in
\nreducing data redundancy.
\nGalaxy Schema:<\/strong> Also known as a fact constellation schema, the speaker explained how
\nmultiple fact tables are connected through common dimension tables, making this schema
\nsuitable for large-scale data warehouses.<\/p>\n
\nto optimize data retrieval in real-world data warehouse environments. The interactive Q&A session
\nallowed students to clarify doubts and understand the challenges faced by industries in this domain.<\/p>\n![\"\"](\"https:\/\/care.ac.in\/engineering\/wp-content\/uploads\/sites\/7\/2024\/10\/WhatsApp-Image-2024-10-19-at-10.18.21-AM-scaled.jpeg\")
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