On Demand
Are your MDM projects taking too long to go live? Challenges in engaging follow on users of the master hub? There are a number of reasons that an MDM project stalls, and considering these before deployment can help decrease time to value and increase acceptance.
David Loshin
Companies that fall into the “MDM early adopter” category are those that combined an understanding of MDM’s unique benefits with a clear set of business needs.
Jill Dyché
Peering under the hood of most organizations' application infrastructure reveals a variety of off-the-shelf tool suites, proprietary products, home-grown applications, and hundreds, if not thousands of desktop data assets such as spreadsheets, documents, and presentations.
David Loshin
If you missed our celebrated “Master Data Quality and Governance” event this past spring in Savannah, you’ll be happy to know that TDWI is taking the show OFF the road! That’s right, we are bringing the highlights of our conference to the web on July 14. Our co-chairs, Jill Dyche and Philip Russom, will be delivering highlights of their conference keynotes, followed by presentations from case study companies that illustrate master data management and governance programs in action.
Duration: Three hours
Philip Russom, Jill Dyché
Collaborative data integration is a collection of user best practices and software tool functions that foster collaboration among the growing number of technical and business people involved in data integration projects and initiatives.
Philip Russom
Putting data into a database and getting it back out are surprisingly different operations, despite the fact that both rely heavily on the capabilities of a vendor’s database management system (DBMS). Because these are two distinct “database workloads,” the common approach for many years has been to provide separate DBMS instances and server/storage hardware for application databases and data warehousing, each instance modeled and optimized for its primary workload. Yet, there are good reasons why some user organizations should consider consolidating the two database workloads onto a single database platform.
Philip Russom
There’s a dizzying array of approaches to master data management (MDM). You can build a solution yourself or acquire one from a vendor. The vendor’s solution may be a dedicated MDM application or a collection of functions within a larger tool. Your MDM solution can manage one data domain (customers, products, financials, etc.) or manage several. Your solution may focus on BI, operational applications, or both. And you could deploy multiple MDM solutions or just one central solution.
Philip Russom
What is a “customer” or a “product,” how are these data concepts defined, and how many places are these data concepts inadvertently replicated across the enterprise? Most organizations have many different applications supporting the functional requirements of specific operational processes.
David Loshin
The organically grown application landscape is rife with independent business processes, potentially working at cross-purposes. Aligning functional departmental systems with an enterprise information management strategy exposes opportunities for data sharing and information reuse, as well as improved collaboration reliant on a coherent centralized enterprise information asset. However, despite the approaches used for data extraction and data warehouse population, real time operational activities continue to create, modify, or retire data, leading to increasing inconsistency between data warehouse refreshes.
David Loshin
Early proponents of business intelligence focused on specific defined reporting and analysis activities, largely in the strategic arena. This may support senior management needs, but largely ignores the thousands of immediate decisions being made by individuals up and down the organizational chain.
David Loshin
Data integration has moved well beyond the ETL processes that create data warehouses. We are now able to enhance our architectures to integrate data in real time easily and with minimal impact on critical operational systems. From operational BI to service oriented architectures (SOA), application consolidation and even master data management (MDM), enterprises are well aware of the power of integrated information to streamline processes, reduce costs, and increase business efficiency. But to succeed, these projects must have steady and reliable delivery of timely business information from across the enterprise, which can be both expensive and resource-intensive. Through an expansion of the data integration architecture, we can reduce operational costs associated with data access and delivery while optimizing resource utilization. We can minimize the risk associated with accessing mission critical data while improving the capture and delivery of data from across the enterprise.
Claudia Imhoff, Ph.D.
Some people don’t believe data integration has architecture, under the assumption that data integration is a small component of a larger data warehouse architecture. If you fail to recognize the autonomous architectures that data integration has developed in recent years, you can’t address how architecture affects data integration’s scalability, staffing, cost, and ability to support real time, master data management, SOA, and interoperability with related integration and quality tools. And all these are worth addressing. This Webinar makes a case for data integration architecture, by defining what it does, where it’s going, and why you should care.
Philip Russom
TDWI's MDM Insight Online Event was held June 16 & 17 and attended by hundreds of people. The sessions taught attendees how master data management can help companies enhance business process efficiency, connect more effectively with suppliers and customers, and drive higher sales and profits.
Jill Dyché, Philip Russom
TDWI's MDM Insight Online Event was held June 16 & 17 and attended by hundreds of people. The sessions taught attendees how master data management can help companies enhance business process efficiency, connect more effectively with suppliers and customers, and drive higher sales and profits.
Jill Dyché, Philip Russom
Partnering companies have long exchanged data associated with supply chains and financial routing networks, and more recently with online trade exchanges, e-commerce, and business process outsourcing. Many large companies sync data across business units in a similar fashion. Applications for business-to-business (B2B) data exchange have been around for years, and many have been modernized by interoperating with platforms for enterprise application integration (EAI) and business process management (BPM). And they have begun incorporating the tools and techniques of data integration (DI). That’s so the applications can cope with the numerous data standards that are common in B2B data exchange, plus versions and variants of these. DI also gives B2B data exchange the BI, data quality, stewardship, and remediation functions it has lacked. When DI is used in this context, it’s called B2B data integration.
Philip Russom
The amount of operational and transactional data needing to be integrated and synchronized across enterprise applications continues to grow, resulting in stronger requirements for data synchronization tools and techniques. Data synchronization – or simply ‘data sync’ – is the process of making multiple data sources agree in terms of content (data values) and often structure (data models or schema). This TDWI Webinar follows a new TDWI Checklist report on Data Synchronization authored by Philip Russom, showcasing many of its valuable capabilities and popular use cases across the enterprise.
Philip Russom
In this webinar you will learn how to pull together the best and avoid the worst practices in master data management, based on Andy’s experience as an enterprise architect and as an industry analyst. The webinar will heavily rely on real life case studies of major MDM projects.
Andy Hayler
MDM is still one of the hottest topics in IT. In early 2009 TDWI announced its second on-line survey, developed in partnership with Baseline Consulting, the MDM Readiness Assessment survey, which takes a multi-disciplinary look at a company’s MDM readiness with the aim of targeting gaps and improvement opportunities. In this webcast survey authors Jill Dyche and Evan Levy will deconstruct the results of this first-of-its-kind survey. They will highlight findings across the survey’s eight categories—Scope, Perception, Data Quality, Change Management, Processing, Rules and Policies, Data Access, and Navigation—and explain why each of these categories informs a successful MDM program. They will also use the survey results to identify the six biggest barriers to MDM readiness. Take the survey, gauge your results, and attend this webcast to see how it all stacks up!
Jill Dyché, Evan Levy
Ever wonder what other companies are doing to manage master data? In advance of TDWI's Master Data Insight conference in March 2009, conference co-chairs Philip Russom and Jill Dyche will discuss the current state of MDM. Philip will discuss TDWI's latest research on the topic--TDWI surveyed 800+ data professionals and their business sponsors, and discovered that user organizations are managing master data more than ever before. Jill will relate those findings with where the early-adopter companies are in their MDM journeys. This webcast quantifies the current state of users’ practices for master data management (MDM), so attendees will have metrics for assessing the state of their own initiatives.
Jill Dyché, Philip Russom
Webinar covering how to prepare for dynamic data warehousing, plus related practices, like operational BI and on demand data integration
Philip Russom
Detailed profiling of the data in source and target systems is a prerequisite to successful projects for data integration, data quality, data warehousing, master data management, and so on. Yet, many technical users scrimp on data profiling by doing it rarely or shallowly, by profiling only known systems or small pieces of them, and by settling for profiles that not very insightful or actionable. These poor practices result in project overruns, the exclusion of important data, incomplete and inaccurate profiles, and severe productivity losses.
Philip Russom
This Webinar reviews components and capabilities needed to develop an MDM solution that can mature along with the needs of the client enterprise applications with which it is integrated.
David Loshin
The people who create sophisticated analytical models and those who manage corporate data warehouses rarely interact when they have every reason to. For years, analytical modelers have done their own data collection, integration, and scoring as part of the process involved in creating predictive models, however data management tasks have become a bottleneck impacting time to market.
Wayne Eckerson
Webinar series covering many topics pertaining to business intelligence and data warehousing, including data quality, data integration, MDM, data warehousing architecture, business intelligence architecture, BI tools and more.Brought to you by The Data Warehousing Institute.
This Webinar summarizes the key findings from the presentations and discussions that took place at the TDWI MDM Insights event, providing practitioners contemplating an MDM initiative a roadmap for delivering a successful solution.
Wayne Eckerson, Jill Dyché
This Webinar evaluates How data governance affects data-driven business initiatives, how data governance intersects with almost all data management practices, and organizational best practices for data governance committees and boards.
Philip Russom
Philip Russom
David Loshin
Jill Dyché
Philip Russom
David Loshin
Archived On-Demand Webinars