000 05229cam a2200505Ii 4500
001 ocn932289266
003 OCoLC
005 20190328114813.0
006 m o d
007 cr cnu---unuuu
008 151216s2016 ne ob 000 0 eng d
040 _aN$T
_beng
_erda
_epn
_cN$T
_dIDEBK
_dN$T
_dYDXCP
_dOCLCF
_dCDX
_dOPELS
_dB24X7
_dSTF
_dDEBSZ
_dAU@
_dOCLCQ
_dD6H
_dLIV
_dOCLCQ
_dU3W
_dWRM
_dCOO
_dOCLCQ
019 _a956740331
020 _a9780128053355
_q(electronic bk.)
020 _a0128053356
_q(electronic bk.)
020 _z9780128051856
035 _a(OCoLC)932289266
_z(OCoLC)956740331
050 4 _aQA76.9.D37
072 7 _aCOM
_x021030
_2bisacsh
082 0 4 _a005.74
_223
100 1 _aHaq, Qazi Muhammad Rashid Ul,
_eauthor.
245 1 0 _aData mapping for data warehouse design /
_h[electronic resource]
_cQamar Shahbaz Ul Haq.
264 1 _aAmsterdam :
_bElsevier,
_c2016.
264 4 _c�2016
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
588 0 _aOnline resource; title from PDF title page (EBSCO, viewed December 18, 2015).
504 _aIncludes bibliographical references.
520 _aData mapping in data warehouse lifecycle is the process of creating a link between two distinct data models' (source and target) tables/attributes. It is required at many stages of DW life-cycle to transform data from one state to another; every stage has its own unique requirements and challenges. This book provides basic and advanced knowledge about data mapping/data transformation. It contains real life scenarios that readers face and presents solutions/standard techniques across various domains. --
_cEdited summary from book.
505 0 _aFront Cover -- Data Mapping for Data Warehouse Design -- Copyright Page -- Dedication -- Contents -- 1 Introduction -- Definition -- 2 Data Mapping Stages -- Mapping from the Source to the Data Warehouse Landing Area -- Mapping from the Landing Area to the Staging Database -- Mapping from the Staging Database to the Load Ready or Target Database -- Mapping from Logical Data Model to the Semantic or Access Layer -- 3 Data Mapping Types -- Logical Data Mapping -- Physical Data Mapping -- 4 Data Models -- Definition -- Entity -- Relationship -- Attributes -- Normalized Data Model.
505 8 _aFirst Normal Form -- Second Normal Form -- Third Normal Form -- Dimensional Data Model -- Fact -- Dimension -- Measure -- Drill-Down and Roll-Up -- Star Schema -- Fact Tables -- Dimension Tables -- 5 Data Mapper's Strategy and Focus -- Mapper Who? How Does He or She Do It? -- 6 Uniqueness of Attributes and its Importance -- Telecom -- Manufacturing -- Finance -- Uniqueness in Data Warehouse -- 7 Prerequisites of Data Mapping -- Logical Data Model -- Entities and Their Description -- Attributes and Their Description -- Primary Key of Entities -- Relationship Between Entities.
505 8 _aCardinality of the Relationship -- Change Capture Column of History-Handled Entities -- Physical Data Model -- Source System Data Model -- Source System Table and Attribute Details -- Subject Matter Expert -- Production Quality Data -- 8 Surrogate Keys versus Natural Keys -- Natural Keys -- Surrogate Keys -- 9 Data Mapping Document Format -- Header-Level Rules -- Column-Level Rules -- Major Parts of the Data Mapping Document -- Data Mapping Columns Explained -- Change Date -- Subject Area -- Target Table Name -- Target Column Name -- Data Type -- PK -- Nullable -- Source System -- Record ID.
505 8 _aSource Table Name -- Source Column Name -- Data Type of Source Column -- Transformation Category -- Transformation Rule -- Updated By -- Mapping Priority or Sequence -- 10 Data Analysis Techniques -- Source Data Sample -- Direct Access -- Extraction from a Source -- Data Files -- What to Look For -- High-Level Inter-Source System Relationship -- Intra-Source System Table-Level Analysis -- Column-Level Analysis -- Uniqueness -- Full Row Duplicates -- Primary Key Duplicates -- Multiple Extracts -- Source System Updates -- History Pattern Analysis -- Type 0 -- Type 1 -- Type 2 -- Type 3 -- Type 4.
505 8 _aType 6 -- Temporal Database -- Transaction Time -- Definition -- Limitations -- Valid Time -- Definition -- Limitations -- History Data Verification -- SQL Tools -- Automatic Query Generators -- Aggregate Functions -- Window and Rank Functions -- Microsoft Excel and Other Tools -- Remove Duplicates -- Sort -- Pivot Tables -- 11 Data Quality -- What Is Data Quality? -- How Do You Benefit from Data Quality? -- Factors Determining Data Quality -- Accurate Data -- Complete Data -- Legible Data -- Relevant Data -- Reliable Data -- Timely Data -- Valid Data.
650 0 _aData warehousing.
650 0 _aData mining.
650 7 _aCOMPUTERS
_xDatabases
_xData Mining.
_2bisacsh
650 7 _aData mining.
_2fast
_0(OCoLC)fst00887946
650 7 _aData warehousing.
_2fast
_0(OCoLC)fst00888026
655 4 _aElectronic books.
776 0 8 _iErscheint auch als:
_aUl Haq, Qamar Shahbaz.
_tData mapping for data warehouse design
856 4 0 _3ScienceDirect
_uhttp://www.sciencedirect.com/science/book/9780128051856
999 _c247262
_d247262