Data Profiling .

• Data Profiling

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Business intelligence Amount and quality of available data

1 Before implementation it is a good idea to do data profiling

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Business intelligence Amount and quality of available data

1 Data Profiling: check inappropriate value, null/empty

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Data quality - Overview

1 Data profiling - initially assessing the data to understand its quality challenges

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Extract, transform, load - Challenges

1 The range of data values or data quality in an operational system may exceed the expectations of designers at the time

validation and transformation rules are specified. Data profiling of a source during

data analysis can identify the data conditions that must be managed by

transform rules specifications. This leads to an amendment of validation rules explicitly

and implicitly implemented in the ETL process.

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Extract, transform, load - Virtual ETL

1 By using a persistent metadata repository, ETL tools can transition

from one-time projects to persistent middleware, performing data

harmonization and data profiling consistently and in near-real time.

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Extract, transform, load - Tools

1 Many ETL vendors now have data profiling, data quality, and metadata capabilities

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Data profiling

1 Data profiling is the process of examining the data available in an

existing data source (e.g. a database or a file) and collecting statistics and

information about that data. The purpose of these statistics may be

to:

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Data profiling - Introduction

1 Thus the purpose of data profiling is both to validate metadata when it is available and to discover metadata

when it is not

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Data profiling - How to do Data Profiling

1 Normally purpose-built tools are used for data profiling to

ease the process

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Data profiling - When to Conduct Data Profiling

1 An additional time to conduct data profiling is during the data

warehouse development process after data has been loaded into

staging, the data marts, etc

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Data profiling - Benefits of Data Profiling

1 Although data profiling is effective, then do remember to find a suitable

balance and do not slip into “analysis paralysis”.

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Surveillance - Data mining and profiling

1 Data profiling can be an extremely powerful tool for psychological and social network

analysis

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Prototype - Data prototyping

1 To achieve this, a data architect uses a graphical interface to interactively develop and execute transformation and cleansing rules using raw data. The resultant data is

then evaluated and the rules refined. Beyond the obvious visual checking of the data on-

screen by the data architect, the usual evaluation and validation approaches are to use Data profiling software and then to insert the resultant data into a test version of the

target application and trial its use.

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Data loading - Virtual ETL

1 By using a persistent metadata repository, ETL tools can transition

from one-time projects to persistent middleware, performing data

harmonization and data profiling consistently and in near-real time.

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Angoss - Software

1 * KnowledgeSEEKER is a data mining product. Its features include data profiling, data visualization and

decision tree analysis.[http://www.comsol.ch/conte

nt.php?si=317id=132anzeige=Angoss%20Products COMSOL ONLINE -

ANGOSS - Knowledge Engineering] It was first released in 1990.

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Angoss - Software

1 * KnowledgeSTUDIO is a data mining and predictive analytics suite for the model development and deployment

cycle. Its features include data profiling, data visualization, decision tree analysis, predictive modeling,

implementation, scoring, validation, monitoring and scorecard

development.

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Integration competency center - Central services ICC

1 It also offers more support for development projects, providing

management, development resources, data profiling, data

quality, and unit testing

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IBM Infosphere - IBM InfoSphere software

1 * IBM InfoSphere Information Analyzer [

http://www-01.ibm.com/software/data/infosphere/information-analyzer/ IBM - Data Profiling, Data Rules and

Quality Monitoring - InfoSphere Information Analyzer - Software] to

profile and track data quality

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Talend - Data management

1 * Talend Open Studio for Data Quality: an open source data profiling

tool that examines the content, structure and quality of complex data

structures

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Oracle Warehouse Builder - Features

1 Further it offers capabilities for Relational model|relational,

Dimensional modeling|dimensional and metadata modeling|metadata data modeling, data profiling, data

cleansing and data auditing

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Oracle Warehouse Builder - History

1 The 10gR1 release was essentially a certification of the 10g database, and

the 10gR2 release (code named Paris) was a huge release

incorporating a wide spectrum of functionality from dimensional modelling to data profiling and

quality

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Data quality assurance

1 'Data quality assurance' is the process of Data profiling|profiling the data to discover inconsistencies and other anomalies in the data, as well

as performing data cleansing activities (e.g. removing outliers,

missing data interpolation) to improve the data quality .

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Data quality assurance - Overview

1 #Data profiling - initially assessing the data to understand its quality challenges

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Data movement - Virtual ETL

1 By using a persistent metadata repository, ETL tools can transition

from one-time projects to persistent middleware, performing data

harmonization and data profiling consistently and in near-real time.

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Jumper 2.0 - Features

1 * User published data profiling

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Information Server - Architecture overview

1 :*Understand — data profiling and metadata creation to understand the

content, quality, and structure of information as it resides in source

systems

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Information Server - History

1 The core technologies of an information server are not new. Data integration

technologies like extract, transform, and load (ETL), data cleansing and matching (both

relational and probabilistic approaches), data profiling, and data federation or replication

have been around for many years. Reputable vendors and several discrete but inter-related markets focus on solutions for these differing styles of data integration (ETL, data quality,

data replication, data federation, etc.).

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Covert surveillance - Data mining and profiling

1 Data profiling can be an extremely powerful tool for psychological and social network

analysis

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