By Paulraj Ponniah
Cutting-edge content material and counsel from an information warehousing expert—now multiplied to mirror box trends
information warehousing has revolutionized the way in which companies in a large choice of industries practice research and make strategic judgements. because the first variation of Data Warehousing Fundamentals, a variety of organisations have applied facts warehouse platforms and reaped huge, immense merits. Many extra are within the means of doing so. Now, this new, revised variation covers the fundamental basics of information warehousing and enterprise intelligence in addition to major fresh developments within the box.
the writer offers an stronger, entire evaluation of knowledge warehousing including in-depth motives of serious concerns in making plans, layout, deployment, and ongoing upkeep. IT pros desirous to get into the sphere will achieve a transparent realizing of strategies for info extraction from resource structures, info detoxing, info alterations, information warehouse structure and infrastructure, and many of the equipment for info supply.
This useful Second Edition highlights the parts of knowledge warehousing and enterprise intelligence the place high-impact technological development has been made. Discussions on advancements contain facts marts, real-time details supply, facts visualization, standards collecting tools, multi-tier structure, OLAP functions, net clickstream research, info warehouse home equipment, and information mining recommendations. The publication additionally includes assessment questions and routines for every bankruptcy, acceptable for self-study or school room paintings, examples of real-world events, and several other appendices with beneficial details.
in particular written for pros liable for designing, enforcing, or keeping facts warehousing structures, Data Warehousing Fundamentals provides agile, thorough, and systematic improvement ideas for the IT specialist and an individual operating or gaining knowledge of in info management.Content:
Chapter 1 The Compelling desire for Datawarehousing (pages 1–21):
Chapter 2 Datawarehouse: The construction Blocks (pages 23–44):
Chapter three tendencies in Datawarehousing (pages 45–70):
Chapter four making plans and undertaking administration (pages 71–97):
Chapter five Defining the enterprise specifications (pages 99–120):
Chapter 6 necessities because the driver for Datawarehousing (pages 121–138):
Chapter 7 Architectural parts (pages 139–161):
Chapter eight Infrastructure because the starting place for Datawarehousing (pages 163–192):
Chapter nine the numerous position of Metadata (pages 193–221):
Chapter 10 ideas of Dimensional Modeling (pages 223–248):
Chapter eleven Dimensional Modeling: complex themes (pages 249–279):
Chapter 12 info Extraction, Transformation, and Loading (pages 281–314):
Chapter thirteen info caliber: A Key to luck (pages 315–337):
Chapter 14 Matching info to the periods of clients (pages 339–372):
Chapter 15 Olap within the Datawarehouse (pages 373–406):
Chapter sixteen Datawarehousing and the internet (pages 407–427):
Chapter 17 information Mining fundamentals (pages 429–460):
Chapter 18 The actual layout technique (pages 461–487):
Chapter 19 Datawarehouse Deployment (pages 489–509):
Chapter 20 progress and upkeep (pages 511–525):
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Extra info for Data Warehousing Fundamentals for it Professionals, Second Edition, Second Edition
This was mainly because of the very nature of the process of making strategic decisions. Information needed for strategic decision making has to be available in an interactive manner. The user must be able to query online, get results, and query some more. The information must be in a format suitable for analysis. 10 THE COMPELLING NEED FOR DATA WAREHOUSING In order to appreciate the reasons for the failure of IT to provide strategic information in the past, we need to consider how IT was attempting to do this all these years.
Supermarts 32 DATA WAREHOUSE: THE BUILDING BLOCKS are carefully architected data marts. You implement these supermarts, one at a time. Before implementation, you make sure that the data content among the various supermarts are conformed in terms of data types, field lengths, precision, and semantics. A certain data element must mean the same thing in every supermart. This will avoid spread of disparate data across several data marts. A data mart, in this practical approach, is a logical subset of the complete data warehouse, a sort of pie-wedge of the whole data warehouse.
The promises of early data warehouse environments to provide user-friendly tools for the masses remained unfulfilled. EVOLUTION OF BUSINESS INTELLIGENCE The initial challenges following the adoption of early data warehousing systems forced companies to take a second look at providing decision support. Companies began to perceive that the goal of decision-support systems is twofold: transformation of data to information; derivation of knowledge from information. Each of these two aspects needs to be emphasized and strengthened appropriately to provide the necessary results.