Bi and Data Sharing Sherman

8/9/2019 Bi and Data Sharing Sherman

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Data Warehousing 101

Howard Sherman

Director Business Intelligence

xwave


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AgendaAgenda

Introduction

Definitions

Why Create a Data Warehouse Complexities You Will Encounter

Best Practices

Questions


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xwave Overviewxwave Overview

Full services IT solutions provider - we fulfill the completerange in enterprise system requirements.

Our legacy is as a high quality systems integration companywith deep infrastructure and product fulfillment capabilities.

Possess extensive COTS and custom development experience;leveraging the best of breed in applications and businessprocesses.

Focused on key industries in which we have relevant

experience. xwave is a $346M division of Bell Aliant Regional

Communicationsan ICT provider with more than 10,000employees, 100-plus years of customer service and aninternational client list.


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The BI Practice at xwaveThe BI Practice at xwave

Over 65 BI Professionals with Access to ManyMore

Specialized and Certified BI Consultants

End to End Capabilities

Experienced in a Full Range ofTools/ProductsIncluding: Cognos, Business Objects, CA, Oracle,Microsoft and Trillium

Over 10 Years of Experience Delivering IndustryLeading BI Solutions


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DefinitionsDefinitions

Business Intelligence n.Process of assembling disparate data,transforming it to a consistent state forbusiness decision making, and empoweringusers by providing them with access to thisinformation in multiple views.

Data Warehouse n.A collection of corporate information,derived directly from operational systems

and some external data sources. Its specificpurpose is to support business decisions, notbusiness operations.


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Why Create a Data Warehouse?Why Create a Data Warehouse?

To perform server/disk bound tasks associated with querying andreporting on servers/disks not used by transaction processing systems.

To use data models and/or server technologies that speed up queryingand reporting and that are not appropriate for transaction processing.

To provide an environment where a relatively small amount ofknowledge of the technical aspects of database technology is requiredto write and maintain queries and reports and/or to provide a meansto speed up the writing and maintaining of queries and reports bytechnical personnel.

To provide a repository of "cleaned up" transaction processing systemsdata that can be reported against and that does not necessarilyrequire fixing the transaction processing systems.


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To make it easier, on a regular basis, to query and report data frommultiple transaction processing systems and/or from external datasources and/or from data that must be stored for query/reportpurposes only.

To provide a repository of transaction processing system data thatcontains data from a longer span of time than can efficiently be heldin a transaction processing system and/or to be able to generatereports "as was" as of a previous point in time.

To prevent persons who only need to query and report transactionprocessing system data from having any access whatsoever to

transaction processing system databases and logic used to maintainthose databases.

To perform complex joins, transformations and business logic onceand not every time a new report is created.


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Performance- Operational and Data WarehouseSystems

Simplify - Make Complex Data from ManySystems Available in One

Accuracy - Standardize and Cleanse

Business Value - Provide the Foundation for the Business

to Have Access to Information to MakeTimely, Informed Decisions


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Complexities of Creating a DataComplexities of Creating a DataWarehouseWarehouse

Incomplete errors

Missing Fields

Records or Fields That, by Design, are not Being

Recorded

Incorrect errors

Wrong Calculations, Aggregations

Duplicate Records

Wrong Information Entered into Source System


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Complexities of creating a DataWarehouse

Incomprehensibility errors

Multiple Fields Within One Field

Inconsistency errors

Inconsistent Use of Different Codes

Overlapping Codes

Inconsistent Grain of the Most Atomic Information


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Best Practices

Data Warehousing is a process and not a project

Complete requirements and design

Prototyping is key to business understanding

Utilizing proper aggregations and detailed data

A full iterative approach is essential

Training is an on-going process

Build data integrity checks into your system


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Questions or Comments?

Thank You

Documents

Bi and Data Sharing Sherman