Drive business process improvement and performance with high quality data
|
|
- Shana Stone
- 8 years ago
- Views:
Transcription
1 Drive business process improvement and performance with high quality data Adam Bracey Solutions Architect (317)
2 Impact of Poor Data Quality Lack of Trust or Confidence in data for BI and DW Most BI and DW users have absolutely no control over the operational systems and processes that capture the majority of the data required within their environments. They can only wait until this dirty data flows downstream throughout the enterprise and comes to rest in the polluted lakes that fill most DW/BI environments. Rob Karel, Forrester, January 2008 Information Managers: Deliver Trusted Data with a focus on Data Quality 2
3 Agenda Benefits of Trusted Data in the Data Warehouse Where does Data Quality Fit? Difficulties in Implementing Trusted data Informatica Approach 3
4 Benefits of Trusted Data in the Data Warehouse Improve confidence in Data Warehouse & BI reporting Fulfill compliance requirements (reducing risk) Reduce rework due to poor data quality Re-use of Data Quality services, built for the Data Warehouse, across other projects 4
5 Delivering Value to our customers Data Migration and Consolidation BI and DW Operational Data Quality MDM Data Governance Cloud Data Quality Regulatory Compliance Reduce costs through standard process for data migration for more than 70 legacy systems Regulatory Compliance Reduce global risk with timely and trusted data for IAS IFRS Data Quality Center of Excellence Delivered a 2,000 percent return on investment All Payor Database Understand true cost of healthcare by delivering Single view of Patient to the public, & healthcare providers Improve Supply chain Saved $1.4m in mailing costs. Reduced SKUs through visibility of inactive parts by 50 percent Rapid business value Maximize online sales with correct location with geocoding - globally 5
6 SWIFT NACHA HIPAA Data Quality: Where it fits? Data Intelligence DQ Reporting & Metrics Enterprise Applications BI Tools Single View of X Regulatory Reporting Front End Y Data Storage Data mart Data mart Data mart EDW DB Data Integration Data Quality Matching Scorecarding Cleansing Enrichment ODS Load Transform Extract Data Profiling: Analyse & Align Data Sources Application Database Unstructured Partner Data Cloud Computing Data Quality Firewall 6
7 Data Quality Dimensions Data Profiling Column Profiling Relationship Redundancy What is the data s physical characteristics? Across multiple tables? What relationships exist in the data set? Across multiple tables? What data is redundant? Orphan Analysis Completeness What data is missing or unusable? Conformity What data is stored in a non-standard format? Data Quality Consistency Accuracy What data gives conflicting information? What data is incorrect or out of date? Duplication What data records are duplicated? Integrity What data is missing important relationship linkages? Range What scores, values, calculations are outside of range? 7
8 Difficulties in Implementing Trusted Data Hard to find the problems, hard to fix them Lack of comprehensive tools End user tools not appropriate for business users Unable to apply and standardize data quality rules across applications Bad data flows from application to application, causing projects and processes to fail. Poor data quality costs millions. 8
9 Informatica Approach: The right people, process and tools Unified role-specific tools for all stakeholders Comprehensive support for all data and all purposes Open to all applications Business Analyst/ Data Steward Line of Business Manager IT Centralized Data Quality Rules Rules Rules Rules Data Quality Customer Order Product 9
10 Continuous Data Quality Improvement For all Users Line of business manager Scorecards Data Steward 1. Profile 2. Establish Metrics and Define Targets Browser-based tool 6. Monitor Data Quality Versus Targets Data Quality 3. Design and Implement Data Quality Rules IT Developer 5. Review Exceptions 4. Deploy Data Quality Services Eclipse-based development environment 10
11 Requirements to delivery trusted data? Data AnalysisParsing Address Matching Monitoring & & Discovery and Validation De-duplication & Standardization Reporting And do this for all data types 11
12 Data Analysis and Discovery Be able to identify patterns, formats, schema, and data quality issues Drill down into actual data Create rules by example as you profile the data 12
13 Parsing & Standardization The key objectives in data standardization are: to transform and parse data to multiple fields to correct completeness, conformity, and consistency problems to standardize field formats 13
14 Address Validation Validate or correct addresses for over 240 countries Have reference data from international postal agencies Validate WW data in one environment Be continuously maintained with WW post offices and databases 14
15 Match and De-Duplicate All Data Types Highly accurate matching requires consideration of multiple attributes using multiple rule sets Use confidence levels to automate life cycle processes Consider over 60 cultural variations for name matching Match data in spite of poor quality 15
16 Monitoring Quality Stakeholders need to be aware Current quality metrics Alerts if quality thresholds are not being met Delivery of reports and alerts must be web based 16
17 Difficulties in Implementing Trusted Data Hard to find the problems, hard to fix them Lack of Comprehensive Tools Comprehensive support for all data and all purposes End User Tools Not Appropriate for Business Users Unable to apply and standardize data quality rules across applications Bad data flows from application to application, causing projects and processes to fail. Poor data quality costs millions. 17
18 Business Empowerment Simple-to-use browser-based tools Designed for the tasks and skills of business data stewards and analysts Purpose-built, web-based UI for fast ramp-up Scorecarding & trending View business, not technical, representations Interact with data directly through profiling, rule validation, and scorecarding Business Manager Analyst & Steward Work with relevant data to meet business needs while reducing reliance on IT 18
19 Business Empowerment Interactive specification by example Ease of use for business through specification by example Access data & data profiles Specify rules by example Immediately validate rules Specify changes & corrections Analyst & Steward Developer & Architect Work with relevant data to meet business needs while reducing reliance on IT 19
20 Unified role-specific tools for all stakeholders Productive development environment with mid-stream profiling for IT developers Full palette of data quality transformations One click from profiling to rule configuration Mid-stream profiling Reusable rules IT Developer Seamless integration with PowerCenter and Data Services Enables developers to rapidly profile the output of any transformation at any stage of any mapping to instantly test and debug their logic. 20
21 Mid-Stream Profiling Profile at any point in the data flow Developer & Architect Profile Source Profile Target For IT: Accelerate the deployment of data quality projects. Profile anywhere in between 21
22 Difficulties in Implementing Trusted Data Hard to find the problems, hard to fix them Comprehensive support for Lack of Comprehensive Tools all data and all purposes End Unified User Tools role-specific Not Appropriate tools for for Business all stakeholders Users Unable to apply and standardize data quality rules across applications Bad data flows from application to application, causing projects and processes to fail. Poor data quality costs millions. 22
23 Centralized, Reusable Rules BI Application Customer Service Portal Sales Automation Application Enforce data quality standards across the organization Centralized data quality rules Rules Rules Rules Rules Customer Order Product Invoice 23
24 Used Across all Interactions Operational Integration At Point of Entry Batch Feeds & Data Warehouse For the business: Support data governance by enforcing consistent data quality rules across all applications. Centralized data quality rules Rules Rules Rules Rules Customer Order Product Invoice For IT: Accelerate the deployment of common data quality rules across all applications. Reduce costs through reuse. 24
25 Solution: Informatica Data Quality Comprehensive support for Lack of Comprehensive Tools all data and all purposes End Unified User Tools role-specific Not Appropriate tools for for Business all stakeholders Users Unable to apply and standardize data Open quality to all applications rules across applications Bad Using data Informatica flows from Data application Quality ensures to application, that your causing organization projects and is using processes the most to fail. trusted, Poor timely, data quality and relevant costs millions. data 25
26 How to overcome the challenges of implementing data quality? Lack of clear ownership of data quality between IT and the business Lack of Data Governance processes Lack of Technical integration between DI and DQ Lack of understanding of how best to implement data quality processes Role based tools to empower the business Business IT collaboration framework Unified DI and DQ with Informatica Platform Expand existing PC team experience by up skilling for data quality 26
27 Summary - Long Term Approach to Data Quality You can t fix it just once You won t be successful just writing a few scripts Create a partnership between Business & IT Support quality for ALL data types Enable Proactive Monitoring Empower Business / Stewards to do more Provide Exception Management Facility 27
28 The Data Integration Company 28
29 Frequent Requirements 29 29
30 Using Informatica Analyst Tools to Profile Your Data 100% browser-based Drill-through analysis Data Steward Right-click to create data quality scorecards Increase productivity and efficiency by enabling the business to proactively take responsibility for data quality and reduce their reliance on IT. 30
31 Parsing & Standardization: Product Data Product ID Brand Description ipod 4GB, Red ipod Nano //Special Edt. Product_ID Brand Size Color Description IPOD 4GB Red 4 Gigabyte Nano Special Edition (Red) 31
32 Parsing & Standardization: Names and Contact Info ContactName Phone Judy Dent // Bob s Assistant FirstName MiddleName LastName Title Phone Judy Dent Bob s Assistant +1 (415)
33 Address Validation (before and after) Address1 Address2 Address3 Address4 Address KATY FRWY SUITE 333 HOUSTEN TX Street City County StateCode StateName ZIP ZIP4 Latitude Longitude 7887 Katy Freeway Suite 333 Houston Harris TX Texas Valid addresses keep costs down and helps ensure compliance 33
34 Using data regardless of it format or correctness SKU Description Size Price AP-2199 Sailors Desk Lamp 12 in AP2199 Nautical Lamp 12 inch PA-2119 Sailors Lamp 12 inch Intrinsically wrong (and potentially uncorrectable) data can still be valuable for Matching purposes Alternate or Nicknames Misspellings Invalid Data Name DOB Address City State Zip W. S. Harrison II PhD 1/33/1967 Medical Center,117/2A #17497 Jackson E. Hartford NY William Stuart Harison 1/3/ a Jacksen Rd. Easthartford CT William Stewart Harison 9/9/ Jackson Road. Suite 2A Hartford East CT Doctor Bill Harisen jr 1/13/ Jacson Room 2a HartfordCT 6984 Harrisen William Doctor 2a Jackson Rd # Hartford CT Highly accurate matching ensures the minimum number of duplicate master records Informatica Confidential 34
35 Monitoring the quality Easy-to-share browser-based scorecards for line of business managers Browser-based scorecards enabling you to: View and share data quality scorecards Drilldown to the actual records Line of business manager Take action to reduce the business impact Zero learning curve for business users to review and track data quality metrics, enabling data quality for the masses. 35
36 Business IT Collaboration to support data quality within the data warehouse Business Users Data Quality Stewards Rule Informatica Platform Shared Repository Shared Engine Data Analysts Developers Architects Mapplet SHARED Profiling, Reference Data, Rules, Notes, Results, Scorecards 36
37 How to overcome the challenges of implementing data quality? Lack of clear ownership of data quality between IT and the business Lack of Data Governance processes Lack of Technical integration between DI and DQ Lack of understanding of how best to implement data quality processes Role based tools to empower the business Business IT collaboration framework Unified DI and DQ with Informatica Platform Expand existing PC team experience by up skilling for data quality 37
Proven Strategies for Data Governance Master Data Management and Data Quality. Wayne Pullam Product Specialist
Proven Strategies for Data Governance Master Data Management and Data Quality Wayne Pullam Product Specialist 1 2 Business Drivers Drive IT Initiatives Key to Success is a Focus on Quality Master Data
More informationData Virtualization and Data Quality Alex Bruschke Solution Architect - Informatica
Data Virtualization and Data Quality Alex Bruschke Solution Architect - Informatica Maximize & Unleash Information Potential Understand it Integrate it Cleanse it Relate it Secure it Act on it Across infrastructure,
More informationWhat s New with Informatica Data Services & PowerCenter Data Virtualization Edition
1 What s New with Informatica Data Services & PowerCenter Data Virtualization Edition Kevin Brady, Integration Team Lead Bonneville Power Wei Zheng, Product Management Informatica Ash Parikh, Product Marketing
More informationTrusted, Enterprise QlikViewreporting. data Integration and data Quality (It s all about data)
Trusted, Enterprise QlikViewreporting with Informatica data Integration and data Quality (It s all about data) Arjan Hijstek senior sales consultant Informatica Nederland bv ahijstek@informatica.com 06-22.454.327
More informationMeasure Your Data and Achieve Information Governance Excellence
SAP Brief SAP s for Enterprise Information Management SAP Information Steward Objectives Measure Your Data and Achieve Information Governance Excellence A single solution for managing enterprise data quality
More informationData Quality Management and Financial Services
Data Quality Management and Financial Services Loretta O Connor Data Quality Sales Manager Data Quality Divion May 2007 1 PG 961 Content Introduction Defining the Data Quality Problem Solutions for Data
More informationInformatica Data Quality Product Family
Brochure Informatica Product Family Deliver the Right Capabilities at the Right Time to the Right Users Benefits Reduce risks by identifying, resolving, and preventing costly data problems Enhance IT productivity
More informationBusiness User driven Scorecards to measure Data Quality using SAP BusinessObjects Information Steward
September 10-13, 2012 Orlando, Florida Business User driven Scorecards to measure Data Quality using SAP BusinessObjects Information Steward Asif Pradhan Learning Points SAP BusinessObjects Information
More informationData Quality Assessment. Approach
Approach Prepared By: Sanjay Seth Data Quality Assessment Approach-Review.doc Page 1 of 15 Introduction Data quality is crucial to the success of Business Intelligence initiatives. Unless data in source
More informationBuilding a Data Quality Scorecard for Operational Data Governance
Building a Data Quality Scorecard for Operational Data Governance A White Paper by David Loshin WHITE PAPER Table of Contents Introduction.... 1 Establishing Business Objectives.... 1 Business Drivers...
More informationDATA GOVERNANCE AT UPMC. A Summary of UPMC s Data Governance Program Foundation, Roles, and Services
DATA GOVERNANCE AT UPMC A Summary of UPMC s Data Governance Program Foundation, Roles, and Services THE CHALLENGE Data Governance is not new work to UPMC. Employees throughout our organization manage data
More informationData Integration Checklist
The need for data integration tools exists in every company, small to large. Whether it is extracting data that exists in spreadsheets, packaged applications, databases, sensor networks or social media
More informationData Virtualization for Agile Business Intelligence Systems and Virtual MDM. To View This Presentation as a Video Click Here
Data Virtualization for Agile Business Intelligence Systems and Virtual MDM To View This Presentation as a Video Click Here Agenda Data Virtualization New Capabilities New Challenges in Data Integration
More informationMaster Your Data and Your Business Using Informatica MDM. Ravi Shankar Sr. Director, MDM Product Marketing
Master Your and Your Business Using Informatica MDM Ravi Shankar Sr. Director, MDM Product Marketing 1 Driven Enterprise Timely Trusted Relevant 2 Agenda Critical Business Imperatives Addressed by MDM
More informationMergers and Acquisitions: The Data Dimension
Global Excellence Mergers and Acquisitions: The Dimension A White Paper by Dr Walid el Abed CEO Trusted Intelligence Contents Preamble...............................................................3 The
More informationSAP BusinessObjects Information Steward
SAP BusinessObjects Information Steward Michael Briles Senior Solution Manager Enterprise Information Management SAP Labs LLC June, 2011 Agenda Challenges with Data Quality and Collaboration Product Vision
More informationData Virtualization A Potential Antidote for Big Data Growing Pains
perspective Data Virtualization A Potential Antidote for Big Data Growing Pains Atul Shrivastava Abstract Enterprises are already facing challenges around data consolidation, heterogeneity, quality, and
More informationData Quality Dashboards in Support of Data Governance. White Paper
Data Quality Dashboards in Support of Data Governance White Paper Table of contents New Data Management Trends... 3 Data Quality Dashboards... 3 Understanding Important Metrics... 4 Take a Baseline and
More informationFive Fundamental Data Quality Practices
Five Fundamental Data Quality Practices W H I T E PA P E R : DATA QUALITY & DATA INTEGRATION David Loshin WHITE PAPER: DATA QUALITY & DATA INTEGRATION Five Fundamental Data Quality Practices 2 INTRODUCTION
More informationData Governance: A Business Value-Driven Approach
Data Governance: A Business Value-Driven Approach A White Paper by Dr. Walid el Abed CEO January 2011 Copyright Global Data Excellence 2011 Contents Executive Summary......................................................3
More informationData Governance: A Business Value-Driven Approach
Global Excellence Governance: A Business Value-Driven Approach A White Paper by Dr Walid el Abed CEO Trusted Intelligence Contents Executive Summary......................................................3
More informationDiscover, Cleanse, and Integrate Enterprise Data with SAP Data Services Software
SAP Brief SAP s for Enterprise Information Management Objectives SAP Data Services Discover, Cleanse, and Integrate Enterprise Data with SAP Data Services Software Step up to true enterprise information
More informationData Integrity and Integration: How it can compliment your WebFOCUS project. Vincent Deeney Solutions Architect
Data Integrity and Integration: How it can compliment your WebFOCUS project Vincent Deeney Solutions Architect 1 After Lunch Brain Teaser This is a Data Quality Problem! 2 Problem defining a Member How
More informationSelf-Service in the world of Data Integration
Self-Service in the world of Data Integration April 2011 San Francisco DAMA Meeting Diby Malakar Director Product Management 1 Agenda Introduction Business Problem Lean and Agile Data Integration Self-Service
More informationInformatica Data Quality Product Family
Brochure Informatica Product Family Deliver the Right Capabilities at the Right Time to the Right Users Benefits Reduce risks by identifying, resolving, and preventing costly data problems Enhance IT productivity
More informationInformatica PowerCenter Data Virtualization Edition
Data Sheet Informatica PowerCenter Data Virtualization Edition Benefits Rapidly deliver new critical data and reports across applications and warehouses Access, merge, profile, transform, cleanse data
More information5 Ways Informatica Cloud Data Integration Extends PowerCenter and Enables Hybrid IT. White Paper
5 Ways Informatica Cloud Data Integration Extends PowerCenter and Enables Hybrid IT White Paper This document contains Confidential, Proprietary and Trade Secret Information ( Confidential Information
More informationInformatica Master Data Management
Informatica Master Data Management Improve Operations and Decision Making with Consolidated and Reliable Business-Critical Data brochure The Costs of Inconsistency Today, businesses are handling more data,
More informationA Road Map to Successful Customer Centricity in Financial Services. White Paper
A Road Map to Successful Customer Centricity in Financial Services White Paper This document contains Confidential, Proprietary and Trade Secret Information ( Confidential Information ) of Informatica
More informationUsing SAP Master Data Technologies to Enable Key Business Capabilities in Johnson & Johnson Consumer
Using SAP Master Data Technologies to Enable Key Business Capabilities in Johnson & Johnson Consumer Terry Bouziotis: Director, IT Enterprise Master Data Management JJHCS Bob Delp: Sr. MDM Program Manager
More informationThree Fundamental Techniques To Maximize the Value of Your Enterprise Data
Three Fundamental Techniques To Maximize the Value of Your Enterprise Data Prepared for Talend by: David Loshin Knowledge Integrity, Inc. October, 2010 2010 Knowledge Integrity, Inc. 1 Introduction Organizations
More informationBusiness Performance & Data Quality Metrics. David Loshin Knowledge Integrity, Inc. loshin@knowledge-integrity.com (301) 754-6350
Business Performance & Data Quality Metrics David Loshin Knowledge Integrity, Inc. loshin@knowledge-integrity.com (301) 754-6350 1 Does Data Integrity Imply Business Value? Assumption: improved data quality,
More informationWhitepaper Data Governance Roadmap for IT Executives Valeh Nazemoff
Whitepaper Data Governance Roadmap for IT Executives Valeh Nazemoff The Challenge IT Executives are challenged with issues around data, compliancy, regulation and making confident decisions on their business
More informationService Oriented Data Management
Service Oriented Management Nabin Bilas Integration Architect Integration & SOA: Agenda Integration Overview 5 Reasons Why Is Critical to SOA Oracle Integration Solution Integration
More informationDATA GOVERNANCE AND DATA QUALITY
DATA GOVERNANCE AND DATA QUALITY Kevin Lewis Partner Enterprise Management COE Barb Swartz Account Manager Teradata Government Systems Objectives of the Presentation Show that Governance and Quality are
More informationData Integration Alternatives Managing Value and Quality
Solutions for Enabling Lifetime Customer Relationships Data Integration Alternatives Managing Value and Quality Using a Governed Approach to Incorporating Data Quality Services Within the Data Integration
More informationQuality Data for Your Information Infrastructure
SAP Product Brief SAP s for Small Businesses and Midsize Companies SAP Data Quality Management, Edge Edition Objectives Quality Data for Your Information Infrastructure Data quality management for confident
More informationLean Integration. into Business Value. John Schmidt VP, Global Integration Services Informatica
Lean Integration Translating an Innovative Agile Approach into Business Value John Schmidt VP, Global Integration Services Informatica 1 Discussion topics The Big Idea, and Why Lean The 7 Principles of
More informationEnterprise Data Governance
Enterprise Aligning Quality With Your Program Presented by: Mark Allen Sr. Consultant, Enterprise WellPoint, Inc. (mark.allen@wellpoint.com) 1 Introduction: Mark Allen is a senior consultant and enterprise
More informationChapter 6 Basics of Data Integration. Fundamentals of Business Analytics RN Prasad and Seema Acharya
Chapter 6 Basics of Data Integration Fundamentals of Business Analytics Learning Objectives and Learning Outcomes Learning Objectives 1. Concepts of data integration 2. Needs and advantages of using data
More informationBest Practices for Maximizing Data Performance and Data Quality in an MDM Environment
Best Practices for Maximizing Data Performance and Data Quality in an MDM Environment Today s Speakers Ed Wrazen VP Product Marketing, Trillium Software Rich Pilkington Director Product Marketing, Syncsort
More informationCompunnel. Business Intelligence, Master Data Management & Compliance (Healthcare) Largest Health Insurance Company in New Jersey.
Compunnel Business Intelligence, Master Data Management & Compliance (Healthcare) Largest Health Insurance Company in New Jersey Business Intelligence, Master Data Management & Compliance (Healthcare)
More informationJOURNAL OF OBJECT TECHNOLOGY
JOURNAL OF OBJECT TECHNOLOGY Online at www.jot.fm. Published by ETH Zurich, Chair of Software Engineering JOT, 2008 Vol. 7, No. 8, November-December 2008 What s Your Information Agenda? Mahesh H. Dodani,
More informationSAP Master Data Governance for Enterprise Asset Management. Dean Fitt Solution Manager, Asset Management Solutions, SAP SE Stavanger, 21 October 2015
SAP Master Data Governance for Enterprise Asset Management Dean Fitt Solution Manager, Asset Management Solutions, SAP SE Stavanger, 21 October 2015 What I ll Cover SAP solutions for Asset Information
More informationData Integration Alternatives Managing Value and Quality
Solutions for Customer Intelligence, Communications and Care. Data Integration Alternatives Managing Value and Quality Using a Governed Approach to Incorporating Data Quality Services Within the Data Integration
More informationThe Informatica Platform for Data Driven Healthcare
Solutions Brochure The Informatica Platform for Data Driven Healthcare Solutions for Providers This document contains Confidential, Proprietary and Trade Secret Information ( Confidential Information )
More informationComprehensive Data Quality with Oracle Data Integrator. An Oracle White Paper Updated December 2007
Comprehensive Data Quality with Oracle Data Integrator An Oracle White Paper Updated December 2007 Comprehensive Data Quality with Oracle Data Integrator Oracle Data Integrator ensures that bad data is
More informationAssessing and implementing a Data Governance program in an organization
Assessing and implementing a Data Governance program in an organization Executive Summary As companies realize the importance of data and the challenges they face in integrating the data from various sources,
More informationEnabling Data Quality
Enabling Data Quality Establishing Master Data Management (MDM) using Business Architecture supported by Information Architecture & Application Architecture (SOA) to enable Data Quality. 1 Background &
More information<Insert Picture Here> Master Data Management
Master Data Management 김대준, 상무 Master Data Management Team MDM Issues Lack of Enterprise-level data code standard Region / Business Function Lack of data integrity/accuracy Difficulty
More informationData Quality Where did it all go wrong? Ed Wrazen, Trillium Software
Data Quality Where did it all go wrong? Ed Wrazen, Trillium Software Agenda Examples of data quality problems Why do data quality problems occur? The impact of poor data Why data quality is an enterprise
More informationData Virtualization. Paul Moxon Denodo Technologies. Alberta Data Architecture Community January 22 nd, 2014. 2014 Denodo Technologies
Data Virtualization Paul Moxon Denodo Technologies Alberta Data Architecture Community January 22 nd, 2014 The Changing Speed of Business 100 25 35 45 55 65 75 85 95 Gartner The Nexus of Forces Today s
More informationElegantJ BI. White Paper. The Enterprise Option Reporting Tools vs. Business Intelligence
ElegantJ BI White Paper The Enterprise Option Integrated Business Intelligence and Reporting for Performance Management, Operational Business Intelligence and Data Management www.elegantjbi.com ELEGANTJ
More informationEnterprise Data Quality
Enterprise Data Quality An Approach to Improve the Trust Factor of Operational Data Sivaprakasam S.R. Given the poor quality of data, Communication Service Providers (CSPs) face challenges of order fallout,
More informationW H I T E PA P E R : DATA QUALITY
Core Data Services: Basic Components for Establishing Business Value W H I T E PA P E R : DATA QUALITY WHITE PAPER: DATA QUALITY Core Data Services: Basic Components for Establishing Business Value 2 INTRODUCTION
More informationImplementing a SQL Data Warehouse 2016
Implementing a SQL Data Warehouse 2016 http://www.homnick.com marketing@homnick.com +1.561.988.0567 Boca Raton, Fl USA About this course This 4-day instructor led course describes how to implement a data
More informationActivePrime's CRM Data Quality Solutions
Data Quality on Demand ActivePrime's CRM Data Quality Solutions ActivePrime s family of products easily resolves the major areas of data corruption: CleanCRM is a single- or multi-user software license
More informationInformatica Solutions for Healthcare Providers. Unlock the Potential of Data Driven Healthcare
S O L U T I O N S B R O C H U R E Informatica Solutions for Healthcare Providers Unlock the Potential of Data Driven Healthcare Informatica Solutions For Healthcare Providers Fundamental change in the
More information<Insert Picture Here> Extending Hyperion BI with the Oracle BI Server
Extending Hyperion BI with the Oracle BI Server Mark Ostroff Sr. BI Solutions Consultant Agenda Hyperion BI versus Hyperion BI with OBI Server Benefits of using Hyperion BI with the
More informationEnable Business Agility and Speed Empower your business with proven multidomain master data management (MDM)
Enable Business Agility and Speed Empower your business with proven multidomain master data management (MDM) Customer Viewpoint By leveraging a well-thoughtout MDM strategy, we have been able to strengthen
More information<Insert Picture Here> Oracle Master Data Management Strategy
Oracle Master Data Management Strategy Name Title The following is intended to outline our general product direction. It is intended for information purposes only, and may not be
More informationdbspeak DBs peak when we speak
Data Profiling: A Practitioner s approach using Dataflux [Data profiling] employs analytic methods for looking at data for the purpose of developing a thorough understanding of the content, structure,
More informationOracle BI Application: Demonstrating the Functionality & Ease of use. Geoffrey Francis Naailah Gora
Oracle BI Application: Demonstrating the Functionality & Ease of use Geoffrey Francis Naailah Gora Agenda Oracle BI & BI Apps Overview Demo: Procurement & Spend Analytics Creating a ad-hoc report Copyright
More informationWhy You Still Need to Master Your Data Before You Master Your Business (Intelligence) Business Imperatives Addressed By Reliable, Integrated View
Why You Still Need to Master Your Data Before You Master Your Business (Intelligence) Business Imperatives Addressed By Reliable, Integrated View David Jordan Data Management Product Specialist 1 2 A simple
More informationBest Practices for Deploying Managed Self-Service Analytics and Why Tableau and QlikView Fall Short
Best Practices for Deploying Managed Self-Service Analytics and Why Tableau and QlikView Fall Short Vijay Anand, Director, Product Marketing Agenda 1. Managed self-service» The need of managed self-service»
More informationUsing Metadata Manager for System Impact Analysis in Healthcare
1 Using Metadata Manager for System Impact Analysis in Healthcare David Bohmann & Suren Samudrala Sr. Data Integration Developers UT M.D. Anderson Cancer Center 2 About M.D. Anderson Established in 1941
More informationBuilding the Bullet-Proof MDM Program
Building the Bullet-Proof MDM Program Evan Levy Partner, Baseline Consulting www.baseline-consulting.com Copyright 2007, Baseline Consulting. All rights reserved. 1 Agenda Understanding the critical components
More informationMDM and Data Warehousing Complement Each Other
Master Management MDM and Warehousing Complement Each Other Greater business value from both 2011 IBM Corporation Executive Summary Master Management (MDM) and Warehousing (DW) complement each other There
More informationCustomer Centricity Master Data Management and Customer Golden Record. Sava Vladov, VP Business Development, Adastra BG
Customer Centricity Master Data Management and Customer Golden Record Sava Vladov, VP Business Development, Adastra BG 23 April 2015 What is this presentation about? Customer-centricity for Banking and
More informationImportance of Data Governance. Vincent Deeney Solutions Architect iway Software
Importance of Data Governance Vincent Deeney Solutions Architect iway Software Some Puzzles Which way is this guy looking? Copyright 2007, Information Builders. Slide 2 Some Puzzles Copyright 2007, Information
More informationTechnip Data Management Journey. IPMA Italy. Jean-Luc Brunat VP, Business Support Functions & Group Data Systems Group IT. Rome, December 3 rd 2013
Technip Data Management Journey IPMA Italy Jean-Luc Brunat VP, Business Support Functions & Group Data Systems Group IT Rome, December 3 rd 2013 1 Sezione Informatica This is Business Intelligence! 2 What
More informationMasterminding Data Governance
Why Data Governance Matters The Five Critical Steps for Data Governance Data Governance and BackOffice Associates Masterminding Data Governance 1 of 11 A 5-step strategic roadmap to sustainable data quality
More informationInformation Governance Workshop. David Zanotta, Ph.D. Vice President, Global Data Management & Governance - PMO
Information Governance Workshop David Zanotta, Ph.D. Vice President, Global Data Management & Governance - PMO Recognition of Information Governance in Industry Research firms have begun to recognize the
More informationCourse Outline. Module 1: Introduction to Data Warehousing
Course Outline Module 1: Introduction to Data Warehousing This module provides an introduction to the key components of a data warehousing solution and the highlevel considerations you must take into account
More informationwww.sryas.com Analance Data Integration Technical Whitepaper
Analance Data Integration Technical Whitepaper Executive Summary Business Intelligence is a thriving discipline in the marvelous era of computing in which we live. It s the process of analyzing and exploring
More informationHadoop Data Hubs and BI. Supporting the migration from siloed reporting and BI to centralized services with Hadoop
Hadoop Data Hubs and BI Supporting the migration from siloed reporting and BI to centralized services with Hadoop John Allen October 2014 Introduction John Allen; computer scientist Background in data
More informationQAD Business Intelligence
QAD Business Intelligence QAD Business Intelligence (QAD BI) unifies data from multiple sources across the enterprise and provides a complete solution that enables key enterprise decision makers to access,
More informationIntegrated Data Management: Discovering what you may not know
Integrated Data Management: Discovering what you may not know Eric Naiburg ericnaiburg@us.ibm.com Agenda Discovering existing data assets is hard What is Discovery Discovery and archiving Discovery, test
More informationHow to Create a Business Focused Data Quality Assessment. Dylan Jones, Editor/Community Manager editor@dataqualitypro.com
How to Create a Business Focused Data Quality Assessment Dylan Jones, Editor/Community Manager editor@dataqualitypro.com Why Do We Need a Data Quality Assessment? We need to perform a data quality assessment
More informationCourse Outline: Course: Implementing a Data Warehouse with Microsoft SQL Server 2012 Learning Method: Instructor-led Classroom Learning
Course Outline: Course: Implementing a Data with Microsoft SQL Server 2012 Learning Method: Instructor-led Classroom Learning Duration: 5.00 Day(s)/ 40 hrs Overview: This 5-day instructor-led course describes
More informationMethodology for Information Quality Management
Methodology for Information Quality Management Through 20 years experience working with customers to address their information challenges, Trillium Software has honed a proven methodology that positions
More informationMDM Challenges and Solutions from the Real World
MDM Challenges and Solutions from the Real World Toronto MDM Summit 2008 info@adastracorp.com www.adastracorp.com Agenda What is Master Data Management? Definitions by example How can I learn from the
More informationThe Butterfly Effect on Data Quality How small data quality issues can lead to big consequences
How small data quality issues can lead to big consequences White Paper Table of Contents How a Small Data Error Becomes a Big Problem... 3 The Pervasiveness of Data... 4 Customer Relationship Management
More informationData Governance. David Loshin Knowledge Integrity, inc. www.knowledge-integrity.com (301) 754-6350
Data Governance David Loshin Knowledge Integrity, inc. www.knowledge-integrity.com (301) 754-6350 Risk and Governance Objectives of Governance: Identify explicit and hidden risks associated with data expectations
More informationTHOMAS RAVN PRACTICE DIRECTOR TRA@PLATON.NET. An Effective Approach to Master Data Management. March 4 th 2010, Reykjavik WWW.PLATON.
An Effective Approach to Master Management THOMAS RAVN PRACTICE DIRECTOR TRA@PLATON.NET March 4 th 2010, Reykjavik WWW.PLATON.NET Agenda Introduction to MDM The aspects of an effective MDM program How
More informationImplementing a Data Warehouse with Microsoft SQL Server 2012 MOC 10777
Implementing a Data Warehouse with Microsoft SQL Server 2012 MOC 10777 Course Outline Module 1: Introduction to Data Warehousing This module provides an introduction to the key components of a data warehousing
More informationB2B Operational Intelligence
M A R C H 2 0 1 4 B2B Operational Intelligence This white paper describes how B2B Operational Intelligence safeguards your supply chain against non-compliant B2B data in the order lifecycle, ensuring that
More informationidashboards FOR SOLUTION PROVIDERS
idashboards FOR SOLUTION PROVIDERS The idashboards team was very flexible, investing considerable time working with our technical staff to come up with the perfect solution for us. Scott W. Ream, President,
More informationInfor CloudSuite Business
Business Achieve a next-generation business strategy in the cloud Whether you re providing services or moving inventory in your home-town, across the country or around the world with Infor CloudSuite Business,
More informationThe Informatica Solution for Improper Payments
The Informatica Solution for Improper Payments Reducing Improper Payments and Improving Fiscal Accountability for Government Agencies WHITE PAPER This document contains Confidential, Proprietary and Trade
More informationElegantJ BI. White Paper. Operational Business Intelligence (BI)
ElegantJ BI Simple. Smart. Strategic. ElegantJ BI White Paper Operational Business Intelligence (BI) Integrated Business Intelligence and Reporting for Performance Management, Operational Business Intelligence
More informationGovernment Business Intelligence (BI): Solving Your Top 5 Reporting Challenges
Government Business Intelligence (BI): Solving Your Top 5 Reporting Challenges Creating One Version of the Truth Enabling Information Self-Service Creating Meaningful Data Rollups for Users Effortlessly
More informationIBM InfoSphere Discovery: The Power of Smarter Data Discovery
IBM InfoSphere Discovery: The Power of Smarter Data Discovery Gerald Johnson IBM Client Technical Professional gwjohnson@us.ibm.com 2010 IBM Corporation Objectives To obtain a basic understanding of the
More informationQAD BUSINESS INTELLIGENCE
QAD BUSINESS INTELLIGENCE QAD BUSINESS INTELLIGENCE QAD Business Intelligence unifies data from multiple sources across the enterprise, providing a comprehensive solution that enables key enterprise decision
More informationInformatica Best Practice Guide for Salesforce Wave Integration: Building a Global View of Top Customers
Informatica Best Practice Guide for Salesforce Wave Integration: Building a Global View of Top Customers Company Background Many companies are investing in top customer programs to accelerate revenue and
More informationThe Key Components of a Data Governance Program. John R. Talburt, PhD, IQCP University of Arkansas at Little Rock Black Oak Analytics, Inc
The Key Components of a Data Governance Program John R. Talburt, PhD, IQCP University of Arkansas at Little Rock Black Oak Analytics, Inc My Background Currently University of Arkansas at Little Rock Acxiom
More informationData Warehouse and Business Intelligence Testing: Challenges, Best Practices & the Solution
Warehouse and Business Intelligence : Challenges, Best Practices & the Solution Prepared by datagaps http://www.datagaps.com http://www.youtube.com/datagaps http://www.twitter.com/datagaps Contact contact@datagaps.com
More informationMaster Data Management The Nationwide Experience. Lance Dacre Director, Data Governance
Master Data Management The Nationwide Experience Lance Dacre Director, Data Governance Agenda Finance FOCUS project Master Data Management Data Governance Assessment of Finance Function Availability of
More information1 2011 Oracle Corporation
1 2011 Oracle Corporation Введение в Oracle Enterprise Data Quality Александр Рындин Старший консультант 2 2011 Oracle Corporation Program Agenda About Datanomic Introducing Oracle Enterprise Data Quality
More information