Welcome to the Research Center

Data requires a story; all stories require data.

In the digital economy, data is the new oil. Discovering a new insight from analyzing data is exciting – and just the beginning of the road to improvements in organizational performance. Getting started on that road requires presenting your data with a story that is compelling and builds support for your plan (and your career).

This two-part series on data storytelling will cover how to marshal your discovery into relevant points – the What, the So What, and the Then What – and how you can deliver them as a narrative to any audience in a way that resonates and inspires people to action. Designed to help both technical and non-technical thought leaders, the audience will learn techniques that are applicable to making any persuasive presentation that is backed by data and/or solid facts:

Part 1, Data Distillation: How to use visual and conceptual techniques to sort disparate data into key messages, based on context, content, and business implications.
Part 2, Data Story Delivery: How to target an audience and deliver a compelling narrative that builds support, engagement, and action.

A crucial element of most of today’s Enterprise Data Management solutions, a Data Warehouse enables an organization to enjoy increased data quality, improved business intelligence, and timelier access to data, among other benefits. An integrated Master Data Management (MDM) solution improves upon traditional Data Warehouse solutions by correlating data across siloed applications, improving segmentation and hierarchical aggregation, and empowering the business to directly manage this data without IT involvement.

In this educational presentation, Bryson Dunn, MDM Competency Director at Datasource, will explore:

- What is MDM?
- What is a “Golden Record”, and why is it important to your business?
- MDM implementation styles and architectural considerations
- Where MDM meets Data Warehousing
- Benefits of a consolidation style hub, and a reference architecture

Data requires a story; all stories require data.

In the digital economy, data is the new oil. Discovering a new insight from analyzing data is exciting – and just the beginning of the road to improvements in organizational performance. Getting started on that road requires presenting your data with a story that is compelling and builds support for your plan (and your career).

This two-part series on data storytelling will cover how to marshal your discovery into relevant points – the What, the So What, and the Then What – and how you can deliver them as a narrative to any audience in a way that resonates and inspires people to action. Designed to help both technical and non-technical thought leaders, the audience will learn techniques that are applicable to making any persuasive presentation that is backed by data and/or solid facts:

Part 1, Data Distillation: How to use visual and conceptual techniques to sort disparate data into key messages, based on context, content, and business implications.
Part 2, Data Story Delivery: How to target an audience and deliver a compelling narrative that builds support, engagement, and action.

Many organizations take a “top-down” approach to their data governance programs and view data governance with a broad lens from the onset. While this method can work in some cases, the complexity, cost, and enterprise-wide scope often prolong the initiative, drive it over budget, or make it largely ineffective. In this educational presentation, Datasource’s Russ Starck will share compelling evidence of why the approach of “bootstrapping” your data governance program is the way to go.

This bottom-up method involves choosing projects, processes, and business domains experiencing the most pain and therefore in need of immediate data governance. The initiative can then be streamlined out to the broader organization for a ripple effect of efficiencies and automation. In this webinar, the audience will learn the benefits of:

- Growing the initiative iteratively from the bottom-up
- Focusing your initial efforts on the departmental level: working in close collaboration with the business users who are closest to the data
- Documenting the procedures you create and incorporating them into the core policies and procedures
- Managing the balance between the desire for C-level involvement and the need to continue building from the grassroots level

The Cloud computing era continues to gain momentum and is positioned as the most efficient way to host a Business Intelligence solution. In this educational webinar, we’ll explore a Cloud BI use case across two different technology stacks, dive into user experience from implementation to data discovery, and share lessons learned for a smooth transition to the Cloud.

BI in the Cloud leverages rapidly-evolving Cloud services to deliver information quickly and securely, in a more cost-efficient manner. The technology replaces depreciating hardware and systems administration expense with a lower-cost solution, allowing architects to focus on data delivery instead of backend hosting. This is especially valuable for organizations that need to separate analytic solutions and those looking to decrease their cost of BI solution ownership.

In order to entice Cloud migration, Cloud BI vendors have greatly reduced the barrier to entry by providing zero-cost deployment capabilities, rapid scaling to align with business needs, advanced analytics, seamless integrations with disparate data sources, and new capabilities delivered weekly.

Datasource experts will demonstrate several Cloud BI options and discuss the value each solution can bring to your business. Attendees will learn how upgrading to a Cloud BI architecture will restructure licensing costs, reduce total cost of ownership, and enhance the organization’s analytic horsepower to decrease topline expenses and increase profits.

Over the past few years, Microsoft has enhanced its BI tools to incorporate a comprehensive offering to serve all user types – “BI for Everyone”. Their new Tabular cube technology aligns with this strategic decision.

This content offers insight for Microsoft BI Developers and Architects as well as BI Directors and Leads and will benefit companies who have invested in this technology or are considering adding it to their technology portfolio. In this webinar, you will learn BI best practices and see a deeper dive into the Microsoft SSAS Tabular cube modeling offering for Self-Service and Gold Standard reporting. Greg Meehan, a Business Intelligence Consultant with top-end SSAS Tabular expertise, shares key advice, tips and experiences utilizing the tool as it has matured over the last few years with newer-in memory technology.

A foundational sub-set of master data and a critical link between master data domains, reference data is shared by multiple constituencies, domains, and systems across an enterprise. Without a sound approach to managing your organization’s reference data, an MDM implementation cannot be successful. It is often the most overlooked component to an MDM solution.

In this webinar, Datasource’s Solomon Williams and Orchestra Networks’ Conrad Chuang will expand on the criticality of reference data and provide educational content on:

- The importance of Reference Data Management
- Best practices in a Reference Data Domain that the entire organization can leverage
- Use cases and lessons from the trenches
- Q&A with the experts- ask your questions about approaches and implementation strategies

On May 25, 2018, the General Data Protection Regulation (GDPR) will replace and expand the Data Protection Directive to be globally applicable, regulating personal data of EU citizens as well as the exportation of personal data outside the EU. Any company with employees or customers in the EU will have to comply, regardless of location.

A strategic Data Governance program can be leveraged to address many aspects of GDPR. In this webinar, Nancy Couture, Senior Director of Delivery Enablement, will expand on GDPR requirements and discuss:

- How the key points of GDPR strategically align to the goals of Data Governance
- How organizations can leverage Data Governance to identify their data footprint and hold people accountable for the quality, transparency, and knowledge around their data
- Using a solid Data Governance capability for a smoother compliance roadmap and more!

Organizations today face the question of how to optimize their data warehouses, save money, increase business value, and grow end-user utilization.

Cloud technologies have evolved to the point where these environments are affordable, secure, and scalable to meet the business needs. The question is: "What is the best mix?" Is it on-premise, hybrid, or cloud? And. how should a cloud migration be approached?

In this webinar:

- common concerns
- roadblocks
- considerations on cloud providers
- a methodology for migrating your organization's data warehouse to the cloud

Hertz is one of the largest car rental companies in the world, with three global brands and 11,000 locations in 150 countries. Hertz has a mission to be the lowest cost, highest quality, and most customer-focused rental company in every market. However, high growth through the years, the current state of internal programs, processes, and new complexities from acquisitions have presented challenges. To address these challenges, enable growth and efficiencies, and meet the objectives of their mission, Hertz has initiated a complete digital transformation.

Attendees will learn:

The guiding principles of the program.
An overview of the reference data architecture.
The multi-domain approach.
The criticality of Data Governance in an MDM solution.
Lessons learned to date.

In this session, the presenters will step through the main business drivers associated with the Data Quality and Data Governance initiatives, the tools needed and leveraged and, most importantly, how to attract and engage key business owners of the data to support a long-term Data Governance organization.

Solomon Williams and Conrad Chuang discuss the changing demands on master data management programs, its ramifications, the change in perspective, and the impact on today’s enterprises. Master data management programs used to be domain-specific - you were either working on a customer or product MDM. But today, MDM has shed its domain-centricity and is now process-oriented. Modern multi-domain MDM programs support key business processes, such as Idea to Opportunity, Opportunity to Market, Market to Order, and Order to Cash.

Metadata Management is one of the most overlooked data management disciplines. Its complexity and often-underestimated benefits are typically the culprits. However, Metadata Management is a foundational discipline that can further mature other data management initiatives, especially Data Quality Management, Data Governance, and Data Stewardship. This presentation details the many aspects of Metadata Management as well as its positive impact when applied in coordination with other data management disciplines.

Learn how Data Governance can deliver significant value quickly, build better relationships with BI teams, and defend your company against the coming Analytical Zombie Apocalypse. Based on real-life experience in organizations like yours, this session shows you how to enliven your reporting, analytics, and metrics efforts through your Data Governance capabilities.

In this presentation, we'll address the plague of Executive Attention Span Disorder (EASD) and proven strategies to make sure your long-running enterprise data program (BI, Data Governance, Metadata, Data Warehouse, etc.) won't be abandoned after the first three months.

You know you need Data Governance, but how do you convince the people in your organization to invest in a long-term program?

Many prefer to focus on things that can be completed in 90 days or less and deliver value immediately. The best-designed DG program can fail or never launch in the first place when not sold properly. Get some great ideas from our hard-won experience selling, designing, and running successful enterprise data governance programs.

A common goal of MDM implementations is to create an accurate, uniform, 360 degree view of the customer. Accurate, consistent views provide for an enhanced customer experience for multi-channel interactions as well as cross-sell, up-sell opportunities. The next logical step for advancing the usefulness of the master data record is to include the social media touch points of the customer. By leveraging social media data to enrich the existing MDM customer record, a direct line of marketing has just been opened to the customer. However, this is not without its challenges.

This presentation defines the “value proposition” of social media data enrichment by discussing:

• Integrating social media data acquisition into the Master Data Strategy
• Tapping into the social media information pool
• Determining which data elements should be mastered

In this webinar, we define reference data and Reference Data Management and identify the sources of reference data. We discuss how a lack of managed reference data impacts an organization and several key aspects of a reference data management capability.

In this webinar, Datasource Master Data Management Practice Lead, Solomon Williams, provides a high level introduction to both master data and MDM, while discussing the many sources of master data. He also looks at at how master data impacts an organization and provide several use cases for MDM.

"Is Data Quality in Your DNA" is the case study of Illumina, a leading manufacturer of tools for genetic research. The case study follows Illumina as they migrate over 100 legacy ERP systems into a single ERP environment.

InfaTools Stage Mapping Accelerator is a tool Datasource leverages to enable faster project delivery. It is a streamlined application that provides seamless interaction with Informatica PowerCenter to generate stage mappings, sessions and workflows, eliminating the need for additional applications.

Developing processes and methods to define the handling of data within an organization can be challenging. This can be even more difficult when faced with external regulations or compliance considerations (HIPAA, PCI, SOX). These best practices are critical to ensure data quality, reduce risk and allow organizations to leverage the full value of their enterprise data.

At Datasource Consulting, we have worked through these challenges first hand and have helped our clients stand-up efficient and well-orchestrated Data Governance Programs. Let us share our insight by joining us for an informative webinar, Data Governance: Tips & Advice for Building and Strengthening a Data Governance Program.

This webinar covers:

• Best practices for building an effective data governance program
• How to start a data governance program from the ground up
• Lessons learned from healthcare & HIPAA
• Overcoming common implementation challenges

In today’s age of agile development, increasing pressures to deliver, and the importance of developing high quality models, how can we afford not to look at proven models that can save time, reduce cost and increase quality?

Universal Data Models and Datasource Consulting have now teamed up in a partnership to provide even more outstanding solutions.

• The what, why, and how to re-use Universal Data Models
• Case studies of organizations that have benefited from the use of Universal Data Models
• Pitfalls regarding re-using models
• How to do ‘agile data modeling’ using Universal Data Models
• Examples of Universal Data Models
• Support evolving demands for business information, quickly and accurately
• How to ensure continuously high quality data models with much lower risk of errors
• Communicate and collaborate best practice data modeling throughout an organization

This webinar will discuss tips and tricks for implementation and provide insight into why data quality is a crucial component of any Enterprise Information Management (or EIM) solution. The webinar is quick, concise and to the point so you will quickly know if you should focus on the importance of Data Quality for your enterprise.

The importance of Data Quality is rising in today’s enterprise business world. According to TDWI, the cost of bad data is more than $600 billion annually in the United States. Low data quality can cause a variety of challenges for your business including:

• Low customer satisfaction and loss of customers
• Misguided business decisions
• Missed opportunities
• Financial inaccuracies and mistakes
• Legal and monetary penalties and
• Negative company image

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. Cloud-based data warehouse solutions have been gaining a lot of attention. Amazon Redshift is a leader in this space, with its cloud based, MPP analytic columnar database offering.

1. Custom Redshift Demo
2. An Introduction to Amazon
3. How to get started
4. Common tips and best practices

Business Intelligence/Data Warehouse (BI/DW) solutions often require a multi-million dollar investment for even modest size companies. Senior management certainly concedes that timely, reliable information is essential to business operations, but they are challenged to demonstrate real cost savings or revenue creation directly attributable to the Business Intelligence and Data Warehouse investment. In these challenging economic times, BI/DW programs are coming under increasing scrutiny to justify their budgets relative to competing investments.

The presentation will use two Business Intelligence & Data Warehouse case studies to show a measurable financial return that far exceeds the initial investment. These two examples will be used to illustrate a general protocol for scoping and managing BI/DW projects to ensure that the value proposition is quantitative and demonstrable.

There is much interest in leveraging agile methods for delivering DW/BI applications cheaper, faster and better than traditional approaches. The agility arises from narrowly focused project scope, iterative sprint development efforts, and active participation of business users to prioritize scope and functionality of successive iterations until the desired functionality is achieved.

However, many agile projects minimize the data modeling discipline and architecture principals in order to preserve their short and focused sprints. This often results in a portfolio of disparate, point solutions with considerable data redundancy and data inconsistencies across BI applications. Although each application may serve its purpose and provided business value, the portfolio becomes unmanageable from a maintenance and integration perspective.

Agile development and enterprise integration need not be mutually exclusive. This webinar will outline an architecture and methodology to achieve both by leveraging data modeling techniques, tools, and metadata management.

Data Masking is a growing concern for major corporations.

Data security, regulatory and audit compliance require organizations to protect sensitive data such as personally identifiable information (Pii). Having been involved in numerous projects using data masking, Datasource Consulting understands the complexity, challenges and nuances for successfully completing such projects.

Join Business Intelligence Consultant, Yelena McElwain, for an informative session that will discuss many of the practical approaches and potential pitfalls associated with Data Masking. She will take you on an in depth tour of the rules and techniques commonly associated with data masking projects.

Much attention has been paid, appropriately, to building the data warehouse. Architecture, ETL, BI tools, appliances, and agile methodology are certainly relevant to building a data environment optimized for analysis and reporting. However, this discussion will focus on using the data warehouse.

Predictive Analytics leverages advanced statistical modeling to produce powerful forecasting tools. With such tools, one can produce reliable sales forecasts, define staffing needs, set inventory levels and refine manufacturing schedules. Predictive models project the optimal replacement frequency of aircraft parts avoiding expensive or dangerous in-service failures. Actuaries use statistical models to set competitive insurance premiums that cover health care costs with reasonable profit margin.

The presentation will start with a reminder look at simple linear regression and correlation and expand into more advanced analytics such as multivariate regression and principal component analysis. It will offer suggestions for initiating advance analytical techniques in your organization and avoiding many of the common pitfalls.

There has been a common and consistent complaint across nearly every organization – “It takes too long to get the information I need to make decisions!” Businesses are frustrated with the complexity of their data.

This then turns us back to why we began investing in a BI solution to begin with, eliminating multiple versions of the truth. Have we even made any progress? Does this sound familiar?

This webinar will go over innovative changes that can be made to help put the business back into Business Intelligence.

You may have heard a lot about Agile development methodologies and how they can help increase the velocity of your BI program. This session will first focus on the tools, methods, and best practices that can help your BI program become more agile. Then we’ll discuss how Data Virtualization can be used to dramatically shorten the lifecycle of information delivery while maintaining data governance and helping your BI program become more agile.