Gartner: Master Data Management Functionality

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MDM solutions require tightly integrated capabilities including data modeling, integration, synchronization, propagation, flexible architecture, granular and packaged services, performance, availability, analysis, information quality management, and security. These capabilities allow organizations to extend data models, integrate and synchronize data in real-time and batch processes across systems, measure ROI and data quality, and securely manage the MDM solution.

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Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall Enterprise Architecture for enhanced business value and success.

How to identify the correct Master Data subject areas & tooling for your MDM...

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Master Data Management – Aligning Data, Process, and Governance

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Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.

Data Governance Best Practices

DATAVERSITY

To take a “ready, aim, fire” tactic to implement Data Governance, many organizations assess themselves against industry best practices. The process is not difficult or time-consuming and can directly assure that your activities target your specific needs. Best practices are always a strong place to start. Join Bob Seiner for this popular RWDG topic, where he will provide the information you need to set your program in the best possible direction. Bob will walk you through the steps of conducting an assessment and share with you a set of typical results from taking this action. You may be surprised at how easy it is to organize the assessment and may hear results that stimulate the actions that you need to take. In this webinar, Bob will share: - The value of performing a Data Governance best practice assessment - A practical list of industry Data Governance best practices - Criteria to determine if a practice is best practice - Steps to follow to complete an assessment - Typical recommendations and actions that result from an assessment

Master Data Management methodology

Database Architechs

Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data. Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.

Data Governance — Aligning Technical and Business Approaches

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Data Governance can have a varied definition, depending on the audience. To many, data governance consists of committee meetings and stewardship roles. To others, it focuses on technical data management and controls. Holistic data governance combines both of these aspects, and a robust data architecture and associated diagrams can be the “glue” that binds business and IT governance together. Join this webinar for practical tips and hands-on exercises for aligning data architecture & data governance for business and IT success.

3 Keys To Successful Master Data Management - Final PresentationJames Chi

8 Steps to Creating a Data Strategy

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Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.

Data Quality Best Practices

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Tackling Data Quality problems requires more than a series of tactical, one-off improvement projects. By their nature, many Data Quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process, and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.

Reference master data management

Dr. Hamdan Al-Sabri

Reference matter data management: Two categories of structured data : Master data: is data associated with core business entities such as customer, product, asset, etc. Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail. Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .

Strategic Business Requirements for Master Data Management Systems

Boris Otto

This presentation describes strategic business requirements of master data management (MDM) systems. The requirements were developed in a consortium research approach by the Institute of Information Management at the University of St. Gallen, Switzerland, and 20 multinational enterprises. The presentation was given at the 17th Amercias Conference on Information Systems (AMCIS 2011) in Detroit, MI. The research paper on which this presentation is based on can be found here: http://www.alexandria.unisg.ch/Publikationen/Zitation/Boris_Otto/177697

Emerging Trends in Data Architecture – What’s the Next Big Thing?

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Digital Transformation is a top priority for many organizations, and a successful digital journey requires a strong data foundation. Creating this digital transformation requires a number of core data management capabilities such as MDM, With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.

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A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.

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Business Intelligence & Data Analytics– An Architected Approach

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Business intelligence (BI) and data analytics are increasing in popularity as more organizations are looking to become more data-driven. Many tools have powerful visualization techniques that can create dynamic displays of critical information. To ensure that the data displayed on these visualizations is accurate and timely, a strong Data Architecture is needed. Join this webinar to understand how to create a robust Data Architecture for BI and data analytics that takes both business and technology needs into consideration.

Data Quality Best Practices

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Tackling data quality problems requires more than a series of tactical, one off improvement projects. By their nature, many data quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process and technology. Join Donna Burbank and Nigel Turner as they provide practical ways to control data quality issues in your organization.

Achieving a Single View of Business – Critical Data with Master Data Management

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Organizations today are critically reliant on data. However, as enterprise applications accumulate—often through digital transformation initiatives, new product launches, or mergers and acquisitions—business-critical data becomes increasingly siloed. As a result, organizations struggle to gain a complete view of customers, products, business partners, or other data domains scattered across legacy systems, cloud, databases, and spreadsheets—typically featuring unique ways of defining, modeling, and recording master data. Working with a network of vendors and suppliers, each with their own array of applications and data systems, only complicates the picture further. All of which inhibits an organization’s ability to realize value from their data. Master Data Management (MDM) allows organizations to consolidate data from multiple sources to create a single source of truth that provides a holistic view of enterprise-wide information. Join this webinar to discover how multi-domain MDM can eliminate the guesswork and uncertainty that results from data gaps and inconsistencies, paving the way for new, powerful insights through cross-domain intelligence. Topics covered will include: - Following a proven method to define and execute a data harmonization strategy that’s directly aligned with business objectives and outcomes - Establishing a ‘contextually relevant’ golden record of consistent, valid, and accurate data across domains, applications, and services - Creating linked relationships between data domains and surfacing up analytics on different data types to provide context and enable more informed decision-making - Ensuring that your data governance strategy both complements and supports your data harmonization and consolidation approach - Managing all administrative, stewardship, and governance functions across domains from a single user interface - Allowing various user personas to utilize data and collaborate effectively with structured operating models that are ‘fit for purpose’ - Ultimately achieving a single view of critical data and related data elements that is easy to navigate

Master Data Management's Place in the Data Governance Landscape

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For many organizations, Master Data Management is a necessity to ensure consistency and accuracy of essential business entities. It further plays alongside data architecture, metadata management, data quality, security & privacy, and program management in the Data Governance ecosystem. Join CCG's data governance subject matter experts as they overview the fundamentals of Master Data Management at our Atlanta-based Data Analytics Meetup. This event will discuss how to enable components of data governance within your organization and review how to best leverage Microsoft's SQL Server Master Data Services.

Improving Data Literacy Around Data Architecture

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Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.

Building a Data Strategy – Practical Steps for Aligning with Business Goals

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Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.

5 Level of MDM Maturity

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Gartner: Seven Building Blocks of Master Data Management

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Analytics Organization Modeling for Maturity Assessment and Strategy Development

Vijay Raj

The paper discusses Business Intelligence Organization Modeling as a concept along with practical implementation aspects with reference to Analytics and Business Intelligence Strategy in large enterprises. BI organization modeling revolves around the ability to model the patterns of BI prevalent within a corporate structure to assess organizational capability and maturity, and there by contributing towards BI strategy development and implementation. The paper also details Analytics & BI organization modeling in a predominantly SAP based enterprise ecosystem and is demonstrated with BI systems based on the SAP NetWeaver Business Warehouse (BW) using data discovery and machine learning techniques. The data discovery process for Analytics & BI organization modeling is carried out using SAP Lumira Data Visualization tool connected to an SAP NetWeaver BW based Global Enterprise Data Warehousing and Reporting System.

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In the beginning was the Word. What is the “Word”? For the purposes of this article, the “word” is Data or Information. It is the basis of all things. Why do we pay so much attention to things rather than the information about them? “Things” are what we can see. “Information” or “Data” about things is what we know about them. One thing may have different definitions, and its Information / Data may vary. These ideas really belong in a philosophy course. The better definition you have, the better you understand the thing itself. Data or Information about things is as important as the things themselves. If you have things but you don’t have information about them, you may have to consider that you don’t really have these things. This presentation is for people who think that Data or Information is an issue for them. For those who think they can own and not understand. This is Data Management for Dummies.

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