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Analytical base table

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201: 62:: who is the subject (describing subject characteristics related to the organization, such as socio-demographic-geographic data, events, etc.), and what does the subject do (describing characteristics of subject behavior, product purchase, product usage, payment behavior, relationship instances, etc.). 55:) and stores all data (variables) describing this subject. If for example the subject is a customer then the record may be referred to as a customer analytic record or "CAR". 110:"Fundamentals of Machine Learning for Predictive Data Analytics Chapter 2: Data to Insights to Decisions - John Kelleher and Brian Mac Namee and Aoife D'Arcy" 222: 109: 32:) is a flat table that is used for building analytical models and scoring (predicting) the future behavior of a subject. 85: 175: 161: 251: 211: 65:
Analytical base tables may be developed as a more general instance applicable to solving general
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problems, but more often it is developed for solving very specific business problems.
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Bohe, Astrid; Cervini, Gianluca; Zobi, Gianluca (2013-08-28).
59: 134:"Digital consumer data model and customer analytic record" 225:
to it so that it can be listed with similar articles.
35:A single record in this table is referred to as an 243: 131: 58:Basically, there are two categories of 244: 47:), and represents the subject of the 194: 13: 210:needs additional or more specific 14: 263: 199: 176:"The customer analytic record" 168: 125: 119: 102: 78: 1: 72: 7: 10: 268: 156:Cite journal requires 90:documentation.sas.com 22:analytical base table 26:analytic base table 240: 239: 223:adding categories 86:"SAS Help Center" 37:analytical record 259: 235: 232: 226: 203: 195: 190: 189: 187: 186: 172: 166: 165: 159: 154: 152: 144: 142: 141: 129: 123: 117: 116: 114: 106: 100: 99: 97: 96: 82: 267: 266: 262: 261: 260: 258: 257: 256: 252:Database theory 242: 241: 236: 230: 227: 216: 204: 193: 184: 182: 174: 173: 169: 157: 155: 146: 145: 139: 137: 130: 126: 120: 112: 108: 107: 103: 94: 92: 84: 83: 79: 75: 41:analytic record 18:database theory 12: 11: 5: 265: 255: 254: 238: 237: 207: 205: 198: 192: 191: 167: 158:|journal= 124: 118: 101: 76: 74: 71: 9: 6: 4: 3: 2: 264: 253: 250: 249: 247: 234: 224: 220: 214: 213: 208:This article 206: 202: 197: 196: 181: 177: 171: 163: 150: 136:. EP2631851A1 135: 128: 122: 111: 105: 91: 87: 81: 77: 70: 68: 63: 61: 56: 54: 50: 46: 42: 38: 33: 31: 27: 23: 19: 228: 209: 183:. Retrieved 179: 170: 149:cite journal 138:. Retrieved 127: 121: 104: 93:. Retrieved 89: 80: 64: 57: 44: 40: 36: 34: 29: 25: 21: 15: 231:March 2024 212:categories 185:2024-05-14 140:2024-05-14 95:2024-05-14 73:References 49:prediction 180:Capgemini 246:Category 219:help out 67:business 53:customer 51:(e.g. a 217:Please 20:, the 113:(PDF) 162:help 60:data 221:by 39:or 30:ABT 24:or 16:In 248:: 178:. 153:: 151:}} 147:{{ 88:. 45:AR 233:) 229:( 215:. 188:. 164:) 160:( 143:. 115:. 98:. 43:( 28:(

Index

database theory
prediction
customer
data
business
"SAS Help Center"
"Fundamentals of Machine Learning for Predictive Data Analytics Chapter 2: Data to Insights to Decisions - John Kelleher and Brian Mac Namee and Aoife D'Arcy"
"Digital consumer data model and customer analytic record"
cite journal
help
"The customer analytic record"

categories
help out
adding categories
Category
Database theory

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