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Sap information steward
1.
SAP BusinessObjects Information
Steward Michael Briles Senior Solution Manager Enterprise Information Management SAP Labs LLC June, 2011
2.
Agenda Challenges with Data
Quality and Collaboration Product Vision & Value Proposition Solution Today – Key Capabilities Demonstration Q&A © 2011 SAP AG. All rights reserved. 2
3.
Challenges with Data
Quality and Collaboration
4.
Business Challenges with
Data Quality and Data Integration Projects Today No environment for business users to collaborate with IT regarding data issues Not sure what the business definition is No consistent repeatable way to measure and score data quality No clear strategy and discipline for improving data quality IT No ability to analyze data dependencies across systems Lack of visibility to where the numbers or data is coming from Minimal reuse of data assets; lots of data duplication © 2011 SAP AG. All rights reserved. and many more… BUSINESS USER 4
5.
Introducing SAP BusinessObjects Information
Steward Product Vision & Value Proposition
6.
Business Analytics Solutions
from SAP Most complete offering Analytic Applications By Industry Enterprise Performance Management Strategy Management Planning, Budgeting, and Forecasting Profitability and Cost Management By LoB Financial Services Public Sector and Healthcare Manufacturing Consumer Products Retail and Telco Utilities and more…. Service, Sales, and Marketing Procurement Supply Chain Finance Sustainability IT, HR, and more… Financial Consolidation Governance, Risk, and Compliance Enterprise GRC Access Risk Management Global Trade Services Continuous Transaction Monitoring Disclosure Management Enterprise Information Management Business Intelligence Reporting and Analysis Dashboards and Visualization Data Services Master Data Management Data Exploration Mobile Event Processing Content Management Information Governance BI Platform Data Warehousing Enterprise Data Warehousing © 2011 SAP AG. All rights reserved. High-performance Analytic Solutions Data Mart Solutions 6
7.
SAP BusinessObjects Information
Steward Product Overview Empower data stewards with a single environment to discover, assess, define, monitor, and improve the quality of their enterprise data asset Discover SAP BusinessObjects Information Steward Define Define business terms, validation rules, cleansing rules, models Discover & understand enterprise data (Data profiling, Metadata management) Define data ownership: Assign Catalog data assets data ownership, accountability, and roles Monitor & Remediate Monitor data quality © 2011 SAP AG. All rights reserved. Surface data quality score in business user applications Workflows to resolve data quality issues 7
8.
SAP BusinessObjects Information
Steward Single solution, multiple benefits Collaborative environment for your IT and business users EMPOWER SAP BusinessObjects Information Steward GOVERN IMPROVE © 2011 SAP AG. All rights reserved. 8
9.
Target Personas for
Information Steward Data Analyst/IT Data Steward Reviews data quality scorecard Defines rules Creates a project Reviews data quality dashboards Creates a connection Defines user security Configures Information Stewards application Schedules a task Analyzes Scorecard Defines a scorecard Analyzes profiling result © 2011 SAP AG. All rights reserved. IT Administrator Adds sources to the project 9
10.
SAP BusinessObjects Information
Steward Value propositions Improve information governance and quality EMPOWER GOVERN IMPROVE © 2011 SAP AG. All rights reserved. Empower Business Users Bridge gap between business and IT with collaborative solution for driving information management initiatives Govern Enterprise Information Enable effective data governance with the industry’s first combined data profiling, metadata management, and data quality monitoring solution Improve Information Transparency Give instant visibility into data quality levels and origins with end-to-end impact analysis and data lineage 10
11.
Empower Business Users What’s
new with SAP BusinessObjects Information Steward No other competitor offers a single business user-oriented solution for metadata management, data profiling and data quality monitoring EMPOWER Share information regarding governance and data quality metrics while also tracking progress toward quality goals View data quality reports via dashboards and scorecards, or via sophisticated inquiries into data origins and lineage Enable business users to visualize how data quality is impacting business © 2011 SAP AG. All rights reserved. View how information measures up against information governance rules and standards Increase efficiency and reduce costs with one solution for data profiling, metadata management, and data quality monitoring 11
12.
Govern Enterprise Information What’s
new with SAP BusinessObjects Information Steward Good data governance depends on creating consistent rules and guidelines about who can access, change, add, share, or integrate enterprise information GOVERN Help pinpoint error hot spots, which often indicate areas in which governance controls must be refined or adjusted Trace data lineage all the way from a report down to a source, gaining a better understanding of your complete business intelligence environment © 2011 SAP AG. All rights reserved. Define data ownership in accordance with your organization’s needs, roles, and accountability principles Create business term glossary with “metapedia”. Integrates and consolidates metadata from many sources, linking business terms with data elements so business people can better understand data definitions 12
13.
Improve Information Transparency What’s
new with SAP BusinessObjects Information Steward Gain reliable insight in your Enterprise information quality and integrated transparency on bad data root cause and usage IMPROVE Comprehensive visibility into data quality at all levels of the information management landscape Scorecard visualizations of data quality from various perspectives and levels High-level data quality scorecards Validation rules oriented dashboard Table/column data quality dashboard © 2011 SAP AG. All rights reserved. Analyze root cause with drill down capability from scorecards and dashboards to rules, data profile, data and business terms Impact analysis that allow you to assess the merits of changes in your data structures and sources, resulting in reduced risk and improved data quality 13
14.
Available Today SAP BusinessObjects
Information Steward 4.0 Key Capabilities
15.
How can Business
and IT Users Leverage SAP BusinessObjects Information Steward? Apply “balanced scorecard” towards data quality performance Measure and track data quality performance against metrics Anticipate and spot data quality weakness Data Profiling Analyze if data matches business definitions and expectations Validate data completeness, sparseness, redundancy, pattern distribution Analyze cross system data dependencies using business views Validation Rules Work with IT to define data validation rules Apply validation rules against sources to continuous monitor data quality Reuse validation rules in data migration and integration Metapedia Work with business users to define and agree on business terms Link business terms to data elements to assist business users understand data definitions Metadata management SAP BusinessObjects Information Steward Data Quality Scorecard Trace data lineage from BI reports to data sources Assess impact of data quality or changes Reuse data assets that is available © 2011 SAP AG. All rights reserved. 15
16.
Key Software Components
of SAP BusinessObjects Information Steward Data Profiling DQ Monitoring New functionality added to metadata management © 2011 SAP AG. All rights reserved. Metadata Analysis Cleansing Rules Existing SAP BusinessObjects Metadata Management capabilities Part of SAP BusinessObjects Data Services and DQM functionality surfaced on IS Business Term Taxonomy Existing SAP BusinessObjects Metadata Management capabilities 16
17.
Key Software Components
of SAP BusinessObjects Information Steward Data Profiling DQ Monitoring New functionality added to metadata management © 2011 SAP AG. All rights reserved. Metadata Analysis Cleansing Rules Existing SAP BusinessObjects Metadata Management capabilities Part of SAP BusinessObjects Data Services and DQM functionality surfaced on IS Business Term Taxonomy Existing SAP BusinessObjects Metadata Management capabilities 17
18.
Use Cases for
Data Insight Data profiling and data quality monitoring Key Drivers Improve information trustworthiness Continuously improve data quality Provide visibility into quality of data Reduce risks for propagating bad data Find data anomalies and remediate data issues Easily understand data and its relationships Create data mapping rules for data integration Define data cleaning and validation rules Show ROI for data quality initiatives Quantify impact of poor data on business Speed up data integration projects with better DQ information Validate governance controls are effective on data quality (for example: investment in MDM) © 2011 SAP AG. All rights reserved. 18
19.
Visualization of Data
Quality High-level balanced data quality scorecard Drill into scorecard details Scorecard to measure DQ from a Data Steward’s perspective Key Quality Dimensions (KPI for data) Latest quality score Data quality score metrics © 2011 SAP AG. All rights reserved. Quality trend 19
20.
Visualization of Data
Quality Validation rules oriented dashboard Select Key data domain, Quality dimension, Rule, and Rules binding to analyze data quality based on any combination of these attributes View validation rule definition Switch to Workspace to profile data and create validation rules Analyze sample failed data Analyze impact of failed data © 2011 SAP AG. All rights reserved. 20
21.
Visualization of Data
Quality Data quality scores and trend at table, column, and rule level Table level score measures number of rows that passed all rules Column level score measures number of rows that passed all rules for this column Rules level score measures rows that passed this rule Detailed statistics of number of failed and total rows © 2011 SAP AG. All rights reserved. Data quality trend over different time ranges Sample failed rows for analysis of the last rule execution 21
22.
Interactively Identify Data
Quality Problems Multi-column data profiling Address profiling measure % valid addresses, % invalid addresses, % can be corrected © 2011 SAP AG. All rights reserved. Dependency profiling measures the degree to which two sets of values are related on one another Redundancy profiling measures the degree of data overlap between two data sets Uniqueness profiling measures the degree of uniqueness of one or more columns of a table 22
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Interactively Identify Data
Quality Problems Table/column data profiling Summary indicators for low cardinality, uniqueness and sparseness Tools for analyzing sample profiling result rows © 2011 SAP AG. All rights reserved. View column properties, value, string, completeness, and distribution profiling statistics Drill from profiling result to into value distribution Drill from value distribution to sample profiling result rows 23
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Interactively Identify Data
Quality Problems Data redundancy There can be multiple advanced profiling tests (tasks) for a table Visualize data relationship Drill into sample data © 2011 SAP AG. All rights reserved. 24
25.
Key Software Components
of SAP BusinessObjects Information Steward Data Profiling DQ Monitoring New functionality added to metadata management © 2011 SAP AG. All rights reserved. Metadata Analysis Cleansing Rules Existing SAP BusinessObjects Metadata Management capabilities Part of SAP BusinessObjects Data Services and DQM functionality surfaced on IS Business Term Taxonomy Existing SAP BusinessObjects Metadata Management capabilities 25
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Use Cases for
Metadata Management BI-centric metadata management “Where did this number come from?” Key Drivers Understand entire BI environment Trace data lineage from a report to sources Change impact analysis for source to reports and users Manage metadata from various data sources, data integration technologies, and BI systems Lower “How will this change in the source impact my BI reports?” © 2011 SAP AG. All rights reserved. TCO by tracking usage and promote reuse of data and reports Improve decision making and regulatory compliance 26
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SAP BusinessObjects Metadata
Management Overview Consolidate, Integrate, Audit, and Trust your Metadata BI Systems Metadata Integrators Metadata Repository Consolidates Analysis Central Repository metadata from various BI related sources Integrates Databases Consolidate Audit metadata in a central metadata repository Relates ETL Integrate Modeling Tools ■ ■ ■ ■ ■ Custom Attributes Annotations, Metapedia Supplements metadata with custom attributes, annotations Creates Business Metadata © 2011 SAP AG. All rights reserved. Impact Usage Lineage Trends Search metadata to enable auditing, usage, change impact, and data lineage analysis Universe Creation universe from relational objects 27
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Metadata Integrators Metadata Management
Integration to: BI Systems Metadata Integrators bundled with Information Steward Databases Metadata Integrators SAP Software: BI Platform, Data Services, Data Federator and SAP NEtWeaver BW NON SAP Software: CWMXML (CWM), RDBMS: MSSQL Server, DB2, Teradata and JDBC Sources Other Metadata Integrators available * ETL Modeling Tools Altova Borland CA COBOL Embarcadero EMC Gentleware Silverun Knightbridge (HP) IBM Informatica Micsosoft MicroStrategy NoMagic OMG Oracle SELECT SPARX Systems SUN Sybase Teradata Tigris Visible Systems Corp W3C * Other metadata integrators available via Meta Integration Technology, Inc. (MITI) © 2011 SAP AG. All rights reserved. 28
29.
Key Software Components
of SAP BusinessObjects Information Steward Data Profiling DQ Monitoring New functionality added to metadata management © 2011 SAP AG. All rights reserved. Metadata Analysis Cleansing Rules Existing SAP BusinessObjects Metadata Management capabilities Part of SAP BusinessObjects Data Services and DQM functionality surfaced on IS Business Term Taxonomy Existing SAP BusinessObjects Metadata Management capabilities 29
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Cleansing Package Builder
(CPB) Key Drivers Empowers data stewards/domain experts to develop custom data cleansing solutions for any data domain Cleansing Package Builder is available within Information Steward © 2011 SAP AG. All rights reserved. 30
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Why Do We
Need Cleansing Package Builder? Unique data for ‘non-party’ data elements Parsed Output Product Category Glove Size Large Material Synthetic Leather Trademark Pro-Fit 2.3 Series Cuff Style Elastic Velcro Palm Type Ultra-Grip Color Black Vendor Mechanix Wear Standard Description Glove – Synthetic Leather, Black, size: Large, Cuff Style: Elastic Velcro, UltraGrip, Mechanix Wear Input Data Glove ultra grip profit 2.3 large black synthetic leather elastic with Velcro Mechanix Wear © 2011 SAP AG. All rights reserved. 31
32.
Key Software Components
of SAP BusinessObjects Information Steward Data Profiling DQ Monitoring New functionality added to metadata management © 2011 SAP AG. All rights reserved. Metadata Analysis Cleansing Rules Existing SAP BusinessObjects Metadata Management capabilities Part of SAP BusinessObjects Data Services and DQM functionality surfaced on IS Business Term Taxonomy Existing SAP BusinessObjects Metadata Management capabilities 32
33.
Use Cases for
Metapedia Business term encyclopedia Key Drivers Enable business users to understand data attributes used in BI environments with business user oriented descriptions Central location for defining standard business vocabulary (words, phrases, or business concepts) © 2011 SAP AG. All rights reserved. Promote proactive data governance with common understanding and agreement on business concepts Organize business terms into categories that align with business subject matter or lines of business 33
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Why SAP? The best
choice for EIM One place for data stewards and business analysts to collaborate and govern their data asset First and only integrated solution - metadata management, business glossary, data quality assessment, data quality monitoring, and cleansing package builder solution Various perspectives to understand and analyze trustworthiness of data Easy and secure access to a rich set of metadata data sources © 2011 SAP AG. All rights reserved. 35
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Information Steward Services
- Migration For the migration from Data Insight to Information Steward we have created three migration packages at fixed fee & fixed scope.* Small Complexity Medium Complexity High Complexity • Number of sources < 3 • Number of column queries <10 • Referential Integrity Test = 10 • Custom queries = 0 • Number of sources < 10 • Number of column queries <100 • Referential Integrity Test = 10 • Custom queries < 30 • Various complexity • Number of sources <25 • Number of column queries <300 • Referential Integrity Test = 10 • Custom queries < 70 • Various complexity 15 days 50 days 120 days * Pricing being finalized. Meta Data Management upgrade not included. © 2011 SAP AG. All rights reserved. 36
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Information Steward Services
– Quick Start Our Quick Start Package is design for green-field implementations to assist our customers to quickly take advantage of IS 4.0; fixed fee and fixed scope.* Quick Start Package • Install IS environment • Knowledge transfer • Setup and execute data profiling jobs • One data domain from two source systems • Configure CPB dictionaries based on the profiles • Design DQ and other dashboards 10 days * Pricing being finalized. © 2011 SAP AG. All rights reserved. 37
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Further Information SAP Community
Network Business Analytics community http://www.sdn.sap.com/irj/boc EIM page http://www.sdn.sap.com/irj/boc/nw-informationmanagement EIM discussion forums http://forums.sdn.sap.com/index.jspa#4 Social Media Twitter http://twitter.com/sapmdmgroup http://twitter.com/sapcommnet Facebook https://www.facebook.com/sapcommunitynetwork Upcoming Webinars Business Analytics Webinar Series http://www.sdn.sap.com/irj/scn/business-analytics-webinars © 2011 SAP AG. All rights reserved. 38
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Thank You! Contact information: Michael
J Briles Senior Solution Manager – Enterprise Information Management E-mail: michael.briles@sap.com
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