The document discusses Data Mining Query Language (DMQL), which is based on SQL and allows users to define data mining tasks. DMQL can be used to specify data mining primitives and define data warehouses and data marts. The syntax of DMQL is presented, including commands to use a database or data warehouse, specify attributes or dimensions, and filter from relations using conditions. An example DMQL query is provided to select from multiple tables and group results by date. References on data warehousing, OLAP, and data mining concepts are also listed.

1. Er. Nawaraj Bhandari
Data Warehouse/Data Mining
Chapter 6:

2. Data mining query language(DMQL)
 It was proposed by Han, Fu, Wang, et al. for the DBMiner data mining system.
The Data Mining Query Language is actually based on the Structured Query
Language (SQL).
 Data Mining Query Languages can be designed to support ad hoc and
interactive data mining. This DMQL provides commands for specifying
primitives.
 The DMQL can work with databases and data warehouses as well. DMQL can be
used to define data mining tasks. Particularly we examine how to define data
warehouses and data marts in DMQL.

3. DMQL Syntax
 use database database_name
 or
 use data warehouse data_warehouse_name
 in relevance to att_or_dim_list
 from relation(s)/cube(s) [where condition]
 order by order_list
 group by grouping_list
 Example
 Use database ABCompany_db
 In relevance to I .name,I.price, C.income, C.age
 From customer C, item I, purchases P, items_sold S
 Where I.item_ID=S. item.JD and S.trans_ID =P.trans_ID and P .custJD=C.cust_ID and C. country –
“Sri Lanka” Group by p.data

4. References
1. Sam Anahory, Dennis Murray, “Data warehousing In the Real World”, Pearson
Education.
2. Kimball, R. “The Data Warehouse Toolkit”, Wiley, 1996.
3. Teorey, T. J., “Database Modeling and Design: The Entity-Relationship Approach”,
Morgan Kaufmann Publishers, Inc., 1990.
4. “An Overview of Data Warehousing and OLAP Technology”, S. Chaudhuri,
Microsoft Research
5. “Data Warehousing with Oracle”, M. A. Shahzad
6. “Data Mining Concepts and Techniques”, Morgan Kaufmann J. Han, M Kamber
Second Edition ISBN : 978-1-55860-901-3

5. ANY QUESTIONS?