eLearningCurve

Getting value from Business Intelligence requires a big-picture view of how information can and should be managed. In this Webcast, industry expert Mark Peco explains how many organizations suffer from a limited perspective on what constitutes decision support. He then offers some tips on how to make sure your company sees the big picture, and then moves carefully and thoughtfully toward realization of quality decision support.

Selecting a software vendor can be downright daunting, which is why savvy organizations employ a thoughtful framework to the selection process. As a former vendor co-founder and long-time IT analyst, Andy Hayler has seen and participated in the procurement cycle from several sides of the fence. In this special Learning Curve Webcast, Andy will share his time-tested methodology and framework for comparing and contrasting software vendors. His evaluation process includes a balance of technical, commercial, and functional criteria to seek a good match to the needs and constraints of your organization. The framework and the process positions you to quickly create a short-list of vendors and then to conduct a detailed evaluation of short-listed products. Purchasing tips will help you to save money at the procurement stage.

In today's increasingly competitive global marketplace, certification can help you separate from the pack! That's why eLearningCurve will soon roll out the Certified Information Management Professional Program. In this Learning Curve Webcast, you'll hear Dave Wells, Education Director for eLearningCurve, explain the nature and roadmap for this new certification program.

A well designed data model is the cornerstone to building business intelligence and data warehouse applications that provide significant business value. Effective data modeling results in transforming data into an enterprise information asset that is consistent, comprehensive and current. Data is transformed from operational or source systems into a data warehouse and often data marts or OLAP cubes for analysis. Register for this Learning Curve Webcast to hear data modeling expert Rick Sherman offer an overview of the fundamental techniques for designing a data warehouse, data marts or cubes that enable business intelligence reporting and analytics.

Professional education comes in many forms these days, including in-person conferences, Webcasts and eLearning. Each of these modes offers a unique value proposition, such as the networking value of conferences, the concise nature of Webcasts, and the in-depth content of eLearning. However, each mode also has drawbacks: conferences tend to be expensive; Webcasts often gloss over important subjects; and eLearning can lack the personal interaction of live events.

Conceptual Data Modeling using the UML standard is a key method for getting a handle on the data requirements of an organization. Effective conceptual data modeling results in maximum benefits from information assets by increasing shared use and avoiding redundancy. Data that is relevant, timely, consistent, and accessible has increased value to the organization.

Data Governance is a burgeoning discipline in the field of information management, as organizations move past Data Administration and into the world of multiple data owners, stewards, and specialists, ultimately culminating in executive level Data Officers. Data is now seen as an asset that must be effectively understood, captured, maintained, parsed, and collaborated upon by all levels of the organization. Thus there is great opportunity in Data Governance, but also the need for education and experience in the trenches. In that service, education specialist David Wells presents eLearningCurve’s Data Governance Curriculum.

Public and private organizations face a common challenge in resolving inconsistent and redundant data, which is often spread across departments, business units, and other divisional lines. While this problem is typically acknowledged and at least partially understood by those working within the organization, it typically takes IT and business specialists applying experientially informed skills to rectify the systems creating the bad data and create a high-quality data resource. Former DAMA President and Lifetime Achievement Award Recipient Mike Brackett has precisely the expertise and experience needed for successfully enacting Data Resource Quality Improvement projects. In this episode of eLearningCurve’s Webcast series, Mike gets down to brass tacks on the identification, definition, and impact of disparate data, as well as common architectural and managerial mistakes and best practices in pursuing Data Resource Quality Improvement.

Very few organizations have a well defined data strategy. In many cases, data is considered the province of the department that creates it and is often jealously guarded. A data strategy should result in the development of systems that pose less risk and provide a higher success rate. Furthermore, a data strategy can provide a CIO with an effective rationale to counter arguments for immature technology or competing data strategies that are inconsistent or otherwise suboptimal. Register for this Learning Curve Webcast to learn from expert data strategist Sid Adelman, who will outline the key elements to consider when designing a enterprise data strategy. He'll pay particular attention to the fundamental role of metadata: what it is, where to get it, how to capture it, and how to manage it over time. This Webcast is brought to you by eLearningCurve. Webcast duration is just 20 minutes, so don't be late! All events are archived.

Career planning for Information Management professionals has two distinct dimensions: knowing what you have to offer, and knowing what employers want. In this webcast, IT career advisor Jennifer Hay looks at both dimensions. A review of hot jobs in the Information Management industry paints a picture of what employers seek, followed by a look at the capabilities and skill sets you need to succeed in those job roles. Hay will then discuss her proven IT career assessment tool that explores the motivations, skills, talents, and preferences that make you unique as an IM professional. The assessment helps you understand what you do and why you do it well. The hot jobs review provides the perspective of what is needed. Matching the two can help you make the most of your career choices. Webcast attendees will receive free access to the assessment tool for a period of two weeks from Sept. 18 through October 2.

One of the most common and important activities in data management, data profiling is the process of analyzing actual data and understanding its true structure and meaning. Data profiling is the first critical step in many IT projects, and is truly the key ingredient to successful data quality management. Tune in to this episode of The Learning Curve to hear data quality management guru Arkady Maydanchik cover the what, why, when, and how of data profiling. Data profiling techniques of varying levels of complexity will be discussed, as will topics related to the gathering, analysis, organization and performance of data profiles and data profile initiatives.

Getting started with any major initiative can be difficult, and data governance is no exception. Last week, eLearningCurve instructor Maria Villar outlined the major elements of a data governance program. In this episode of The Learning Curve, her partner, Theresa Kushner, introduces you to how others have already started this journey. In the case study portion of this training, you are introduced to elements of a program dedicated to governing customer data. Designing and implementing a Data Governance Organization Model will help your organization get on the right track for saving money and improving data-related processes. Ideally, a Central Governance Team will report to senior management, and serve as a liaison to various data experts from across the enterprise. That's just one aspect of successful data governance.

Selecting an MDM vendor can be a daunting task, unless you have an insider showing you the way. That's exactly what Andy Hayler does in this episode of The Learning Curve. The former founder of MDM stalwart Kalido, Andy is now an independent analyst, using his inside knowledge of the industry to help clients navigate the increasingly complex waters of Master Data Management. Tune into this Webcast to hear Andy take the guesswork and uncertainty out of the vendor selection process. He'll outline his structured process for product evaluation, which includes technical, commercial and functional criteria. This Webcast offers a preview of Andy's full-length course at eLearningCurve.com. The in-depth workshop offers a framework that describes the model of an ideal MDM product. The framework and the process, when combined with a survey of the MDM market, positions you to quickly create a short-list of vendors and then to conduct a detailed evaluation of short-listed products.

A data governance program should encompass all of the policies, standards, processes, people, and technology that are essential to managing critical data assets. Successful data governance programs are matched to an organization's culture, information maturity, priorities, and sponsorship. Tune into this episode of The Learning Curve to hear Data Governance expert Maria Villar, who will outline some of the key components of this growing discipline. You'll learn the business case for Data Governance, which types of data should be governed, and implementation fundamentals for successful governance, including standards and policies, processes, people and technology.

One profession that continues to grow in this difficult economy is Data Quality. More and more organizations are recognizing the value of Data Quality initiatives, and as a result, there are jobs to be had. But what kind of jobs? And what are the necessary skills to get those jobs? Tune into this episode of The Learning Curve to find out!

As today’s business environment continues to evolve and grow ever more complex and competitive, data integration is required to coordinate master data and achieve a single, consistent view of organization’s core business entities. MDM solutions enable master data synchronization, combining disparate applications and business units under the umbrella of a formal management system. Business approval, business process change, and capture of master data at optimal, early points in the data lifecycle are essential to achieving true enterprise master data. William McKnight’s Introduction to Master Data Management provides the tools necessary for real world MDM solutions.

Master Data Management (MDM) presents even well seasoned data management professionals with unique and complex challenges that might not be fully foreseen from the outset of the project. The intricacies of managing identities and hierarchies, and resolving conflicts among disparate data sources, make MDM an ambitious but potentially fruitful undertaking; particularly in light of the far-reaching and multifaceted implications that MDM has on organizations. MDM guru Andy Hayler brings his experience and expertise to the table in this episode of eLearningCurve’s Webcast series. Andy will discuss MDM’s relation to other IM disciplines, the concepts and terminology of MDM, architectural options for MDM implementation, advice on building a business case for MDM, and best (and worst) MDM practices.

Given the scale and complexity of the data quality field, data quality practitioners need a strong understanding of the fundamental concepts, principles, and terminology that are common in quality management. Building upon that foundation, they need to understand how quality management concepts and principles are applied to data and learn the language utilized in the data quality world. In this episode of The Learning Curve, data quality visionary David Wells provides an overview of the concepts, principles, practices, and terminology of the data quality field. Webcast duration is 20 minutes.

With the advancing of time and cumulative growth of corporate databases comes an endless process of upgrading and redesigning the programs responsible for data integration, as well as the databases themselves. The typical result of these dynamics is that information systems get better, while data quality deteriorates. Without a comprehensive data quality-monitoring program, bad data spread like viruses. In this episode of The Learning Curve, data quality guru Arkady Maydanchik discusses various practices that can be put in place to mitigate the problem and maintain high data quality through data integration. Webcast duration is 20 minutes.

Given the far-reaching and long-lasting implications of data models, and the temporal and financial realities of the environments that models are typically constructed in, the importance of effectively creating an objective measure of data model quality comes to light. In this episode of The Learning Curve, data quality specialist Steve Hoberman will provide insight into the tools and techniques needed to strengthen data models. In this 20-minute Webcast, he will outline the creation and application of data model scorecards and the use of automated tools to enforce modeling best practices and standards.