Chances are, this is probably the first time you've evaluated an MDM solution, and by now, you know there is A LOT to consider when evaluating vendors. But before you go signing any contracts, be sure you know exactly what you're signing up for.
Selling MDM to Leadership: Defining the WhyProfisee
This document discusses defining the business justification or "why" for a master data management (MDM) program. It covers:
1. Defining the business perspective on why undertake an MDM program by focusing on problems to solve rather than technical details. This includes categorizing and prioritizing business benefits.
2. Prioritizing where to start the program by focusing efforts on solving business problems.
3. The next part will cover calculating the total cost of ownership and "rightsizing" the initial scope of the MDM program, including which data domains, functions, or organizations to include.
Selling MDM to Leadership: Beyond the 1st Use-CaseProfisee
Getting through the first business case is challenging and can seem to go on forever. It may seem impossible to believe, but MDM will become a way of life for your organization. We’ll walk through countless examples to demonstrate the far-reaching impact and value that an MDM program can have.
It is easy to get caught up in the possibilities of what MDM can do for your enterprise. It can be daunting trying to decide where to start, what to measure, and what objectives to set. After all, not all data has the same value and not all data problems have the same impact. Learn how to determine the scope of your MDM program with this presentation.
Join Bill O'Kane, former Gartner VP and MDM Analyst to examine current trends occurring in the MDM marketplace today at the "street-level" and how they can impact your enterprise or MDM initiatives.
It's not one or the other, or, one vs the other... MDM and DG are better together. And for good reasons.
Join Nicola Askham, The Data Governance Coach, as she discusses the relationship between Data Governance (DG) and MDM, how they benefit each other, and how to get maximum value from both.
CRM data quality has become so pervasive that only 49% of organizations consider the current state of their CRM data to be clean, not allowing them to fully leverage it.
The document discusses healthcare's need for master data management (MDM) to create a single trusted source of reference data across disparate systems. It notes that MDM hubs can standardize data to common governance rules, define common reference data, and avoid redundant data entry. The document also provides examples of common healthcare domains that can benefit from MDM like providers, facilities, patients, reference codes. Finally, it summarizes one healthcare organization's experience deploying MDM starting with provider and location domains to consolidate inconsistent data across various systems and enable more accurate reporting.
Selling MDM to Leadership: Defining the WhyProfisee
This document discusses defining the business justification or "why" for a master data management (MDM) program. It covers:
1. Defining the business perspective on why undertake an MDM program by focusing on problems to solve rather than technical details. This includes categorizing and prioritizing business benefits.
2. Prioritizing where to start the program by focusing efforts on solving business problems.
3. The next part will cover calculating the total cost of ownership and "rightsizing" the initial scope of the MDM program, including which data domains, functions, or organizations to include.
Selling MDM to Leadership: Beyond the 1st Use-CaseProfisee
Getting through the first business case is challenging and can seem to go on forever. It may seem impossible to believe, but MDM will become a way of life for your organization. We’ll walk through countless examples to demonstrate the far-reaching impact and value that an MDM program can have.
It is easy to get caught up in the possibilities of what MDM can do for your enterprise. It can be daunting trying to decide where to start, what to measure, and what objectives to set. After all, not all data has the same value and not all data problems have the same impact. Learn how to determine the scope of your MDM program with this presentation.
Join Bill O'Kane, former Gartner VP and MDM Analyst to examine current trends occurring in the MDM marketplace today at the "street-level" and how they can impact your enterprise or MDM initiatives.
It's not one or the other, or, one vs the other... MDM and DG are better together. And for good reasons.
Join Nicola Askham, The Data Governance Coach, as she discusses the relationship between Data Governance (DG) and MDM, how they benefit each other, and how to get maximum value from both.
CRM data quality has become so pervasive that only 49% of organizations consider the current state of their CRM data to be clean, not allowing them to fully leverage it.
The document discusses healthcare's need for master data management (MDM) to create a single trusted source of reference data across disparate systems. It notes that MDM hubs can standardize data to common governance rules, define common reference data, and avoid redundant data entry. The document also provides examples of common healthcare domains that can benefit from MDM like providers, facilities, patients, reference codes. Finally, it summarizes one healthcare organization's experience deploying MDM starting with provider and location domains to consolidate inconsistent data across various systems and enable more accurate reporting.
Making an Effective Business Case for Master Data ManagementProfisee
85% of MDM (master data management) initiatives will fail to go beyond piloting and experimentation, making a persuasive and informative business case for MDM critical to the program's success.
The document discusses the myth that an organization needs to be "ready" to implement Master Data Management (MDM) by cleaning up data quality issues first. It argues that data quality is actually one of the benefits achieved by an effective MDM implementation, not a prerequisite. MDM solutions can capture and enforce data quality rules across different data models and business processes in real-time, while standalone data quality projects are limited in scope and have a finite lifespan. Rather than waiting to fix all data issues, the document advocates that organizations should transform digitally by implementing MDM to improve data quality on an ongoing basis.
The, What, Why, & How of MDM in Digital Business Transformation SlideshareProfisee
MDM not only makes digital transformation possible, it optimizes the results of these efforts while reducing the risk of tactical and strategic failures. This webinar dives into the critical role that MDM plays in digital business transformation initiatives
Harvard-Profisee | Path to Trustworthy Data Webinar SlidesProfisee
Find out how your data investments and strategies compare to the 343 executives surveyed by Harvard Business Review Analytic Services and learn how you can leverage your enterprise data as a strategic asset from those who have walked the path before you.
These slides guided a presentation from Alex Clemente, Managing Director at Harvard Business Review Analytic Services and include several key findings from the 2021 HBR-AS Pulse Survey, "The Path to Trustworthy Data."
Be sure to watch the entire presentation and interactive Q&A on-demand here: https://profisee.com/event/walking-the-path-to-trustworthy-data/
The path to a better bottom line is paved by large numbers of operational decisions made by people, by processes and by software applications. Systematically improving each operational decision – at scale – is at the core of Decision Management. Business Architects and Analysts identify, describe and model operational decisions in Decision Discovery.
In this webinar, James Taylor, CEO of Decision Management Solutions, and Dr. Juergen Pitschke, Founder and Managing Director at BCS, will show you how to get started with Decision Management on your next application development or business process improvement project with Decision Discovery. Learn how to:
Identify decisions, sub-decisions and information and knowledge resources (including rules and analytics)
Describe decisions in detail (Decision Tables and other Metaphors)
Model decisions in a DMN-conformant decision modeling tool for communication and documentation
Link to execution environments
Master Data Management (MDM) is a systematic approach to cleaning up customer data so businesses can manage it efficiently and grow effectively. MDM helps businesses achieve a single version of truth about customers. It deals with strategies, architectures, and technologies for managing customer data, known as Customer Data Integration (CDI). Implementing MDM requires gaining commitment from senior management, understanding business drivers and resource requirements, and providing estimates of benefits like reduced costs and increased sales. A pilot project should be proposed before a full implementation to demonstrate value and gather feedback.
5 Steps To Measure ROI On Your Data Science Initiatives - WebinarGramener
1. Measuring ROI from data science initiatives is challenging for many organizations as the outcomes are often not clearly defined, quantified, or attributed to the initiatives. Breaking the chain from data to insights to actions to outcomes is common.
2. A framework is presented for quantifying the value of data science initiatives using 5 steps - define success metrics, measure the metrics, attribute outcomes to causal factors, calculate net costs and benefits to determine breakeven, and benchmark results.
3. The framework is applied to a case study of a beverage manufacturer that used analytics to optimize plant costs. Key metrics like cost savings, employee productivity, and process efficiency were defined and attribution methods like A/B testing were used
The document discusses best practices for data governance leadership and master data management, including establishing a data governance council and committees to define data strategies and policies, monitor data quality, and ensure accountability and compliance. It also covers implementing a customer data hub using Oracle solutions to consolidate, cleanse, and share customer information across systems.
The most successful Enterprise SaaS companies know that growing revenue only through new customer acquisition is the less efficient way to scale. Rather, they understand that growing revenue within your existing customer base - through up-sells, cross-sells, and expanded use - is the most profitable way to scale.
In fact, Enterprise SaaS companies that grow revenue - and company valuation - by expanding revenue within their existing customer base also know the key to making this work is to focus on - and operationalize - Customer Success.
This presentation - Customer Success for Security Software - is from Pulse 2014, the biggest Customer Success industry event ever and included panelists from ProofPoint, Rapid7, WhiteHat
This document provides information on data governance and discusses several challenges and approaches to data governance. It discusses that 80% of enterprise data is unstructured and spread across many sources like web data, enterprise applications, emails, and social media. Governing such diverse data assets is a complex long-term journey. It also discusses why data governance is needed, challenges of data governance, and different routes and frameworks to conduct data governance assessments and develop solutions. These include using cases studies, lean six sigma methodology, enterprise data architecture approaches, and linking data governance with machine learning. The document concludes by emphasizing structure of data, experimenting with different assessment and solutioning methods, and leveraging machine learning as a new capability.
Analysts predict $3.5 trillion will be spent on IT projects worldwide in 2017, however for every $1 billion invested in the US, $122 million is wasted due to poor project performance. Three in ten major IT projects fail, and 75% of business executives expect their software projects to fail. Fewer than one third of projects are completed on time and on budget. Failed projects can damage brands, partnerships and morale while losing investments and opportunities. Proper project planning and management is needed to avoid these issues and failures.
This document provides an introduction and overview of master data management (MDM). It begins with defining MDM as managing an organization's critical data. The agenda then outlines an overview of MDM, how it helps businesses succeed, and risks and challenges. It provides examples of master data and how MDM systems work. Key benefits of MDM include a single source of truth, reduced costs, and increased customer satisfaction by avoiding duplicate or inconsistent data across systems. Risks include data inconsistencies from mergers and acquisitions. Challenges involve determining what data to manage, ensuring consistency, and establishing appropriate data governance and information systems.
The document discusses enterprises' increasing investments in big data over the next three years. It notes that 70% of IT decision makers see exploiting big data as critical to future success, and 65% say they risk becoming irrelevant without embracing big data. Additionally, 64% see big data changing business boundaries as non-traditional providers enter industries. The reasons for this new interest in data are to make strategic decisions faster using insights from captured and combined data in new forms.
The document announces a conference called "Best Practices for Consumer Products" to be held October 5-7, 2015 in Atlanta, Georgia. The conference will bring together hundreds of business and IT professionals from consumer products companies to share best practices and innovative strategies around topics like integrated business planning, supply chain management, e-commerce, analytics, and more. Attendees will learn how to maximize their existing technology investments and stay on the leading edge of the industry.
This presentation covers the definition of Master Data Management, outlines 5 essential elements of MDM, and describe 10 real-world best practices for MDM and data governance and 4 advanced topic areas, based on years of experience in the field.
Key Steps to Kick Start Your Master Data Management Strategy in 2020Rahul Singh
Data is king. And, it has become the new support function for organizations ever since digitization has leapfrogged. Data management is becoming more necessary than ever to ensure its quality, accuracy, and integrity remain intact, all-around. That said, merely consolidating and managing data does not cut the mark anymore.
Gartner: Seven Building Blocks of Master Data ManagementGartner
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm.
Rahul Chande, Specialist Leader at Deloitte Consulting LLP, shares keys to master data management and effectiveness in the federal government sector at the 2015 Informatica Government Summit.
Proven Strategies to Leverage Your Customer Community to Grow Your BusinessSocious
Find out how businesses are leveraging stronger relationship with customers to identify revenue opportunities within their customer base and create more products that their markets love. During this presentation, you’ll learn:
Why peer-to-peer communities keep more customers engaged than other channels
How to ensure your customer community serves both your customers and your business
Actionable strategies for turning the social data in your community platform into profit
The document provides a template for creating a business case to justify investing in a marketing automation solution. It outlines sections to include such as an executive summary, opportunity overview, assumptions, business impact analysis, risks, and a recommendation. The template helps evaluate costs, benefits, and key factors for a marketing automation project to obtain management approval.
Making an Effective Business Case for Master Data ManagementProfisee
85% of MDM (master data management) initiatives will fail to go beyond piloting and experimentation, making a persuasive and informative business case for MDM critical to the program's success.
The document discusses the myth that an organization needs to be "ready" to implement Master Data Management (MDM) by cleaning up data quality issues first. It argues that data quality is actually one of the benefits achieved by an effective MDM implementation, not a prerequisite. MDM solutions can capture and enforce data quality rules across different data models and business processes in real-time, while standalone data quality projects are limited in scope and have a finite lifespan. Rather than waiting to fix all data issues, the document advocates that organizations should transform digitally by implementing MDM to improve data quality on an ongoing basis.
The, What, Why, & How of MDM in Digital Business Transformation SlideshareProfisee
MDM not only makes digital transformation possible, it optimizes the results of these efforts while reducing the risk of tactical and strategic failures. This webinar dives into the critical role that MDM plays in digital business transformation initiatives
Harvard-Profisee | Path to Trustworthy Data Webinar SlidesProfisee
Find out how your data investments and strategies compare to the 343 executives surveyed by Harvard Business Review Analytic Services and learn how you can leverage your enterprise data as a strategic asset from those who have walked the path before you.
These slides guided a presentation from Alex Clemente, Managing Director at Harvard Business Review Analytic Services and include several key findings from the 2021 HBR-AS Pulse Survey, "The Path to Trustworthy Data."
Be sure to watch the entire presentation and interactive Q&A on-demand here: https://profisee.com/event/walking-the-path-to-trustworthy-data/
The path to a better bottom line is paved by large numbers of operational decisions made by people, by processes and by software applications. Systematically improving each operational decision – at scale – is at the core of Decision Management. Business Architects and Analysts identify, describe and model operational decisions in Decision Discovery.
In this webinar, James Taylor, CEO of Decision Management Solutions, and Dr. Juergen Pitschke, Founder and Managing Director at BCS, will show you how to get started with Decision Management on your next application development or business process improvement project with Decision Discovery. Learn how to:
Identify decisions, sub-decisions and information and knowledge resources (including rules and analytics)
Describe decisions in detail (Decision Tables and other Metaphors)
Model decisions in a DMN-conformant decision modeling tool for communication and documentation
Link to execution environments
Master Data Management (MDM) is a systematic approach to cleaning up customer data so businesses can manage it efficiently and grow effectively. MDM helps businesses achieve a single version of truth about customers. It deals with strategies, architectures, and technologies for managing customer data, known as Customer Data Integration (CDI). Implementing MDM requires gaining commitment from senior management, understanding business drivers and resource requirements, and providing estimates of benefits like reduced costs and increased sales. A pilot project should be proposed before a full implementation to demonstrate value and gather feedback.
5 Steps To Measure ROI On Your Data Science Initiatives - WebinarGramener
1. Measuring ROI from data science initiatives is challenging for many organizations as the outcomes are often not clearly defined, quantified, or attributed to the initiatives. Breaking the chain from data to insights to actions to outcomes is common.
2. A framework is presented for quantifying the value of data science initiatives using 5 steps - define success metrics, measure the metrics, attribute outcomes to causal factors, calculate net costs and benefits to determine breakeven, and benchmark results.
3. The framework is applied to a case study of a beverage manufacturer that used analytics to optimize plant costs. Key metrics like cost savings, employee productivity, and process efficiency were defined and attribution methods like A/B testing were used
The document discusses best practices for data governance leadership and master data management, including establishing a data governance council and committees to define data strategies and policies, monitor data quality, and ensure accountability and compliance. It also covers implementing a customer data hub using Oracle solutions to consolidate, cleanse, and share customer information across systems.
The most successful Enterprise SaaS companies know that growing revenue only through new customer acquisition is the less efficient way to scale. Rather, they understand that growing revenue within your existing customer base - through up-sells, cross-sells, and expanded use - is the most profitable way to scale.
In fact, Enterprise SaaS companies that grow revenue - and company valuation - by expanding revenue within their existing customer base also know the key to making this work is to focus on - and operationalize - Customer Success.
This presentation - Customer Success for Security Software - is from Pulse 2014, the biggest Customer Success industry event ever and included panelists from ProofPoint, Rapid7, WhiteHat
This document provides information on data governance and discusses several challenges and approaches to data governance. It discusses that 80% of enterprise data is unstructured and spread across many sources like web data, enterprise applications, emails, and social media. Governing such diverse data assets is a complex long-term journey. It also discusses why data governance is needed, challenges of data governance, and different routes and frameworks to conduct data governance assessments and develop solutions. These include using cases studies, lean six sigma methodology, enterprise data architecture approaches, and linking data governance with machine learning. The document concludes by emphasizing structure of data, experimenting with different assessment and solutioning methods, and leveraging machine learning as a new capability.
Analysts predict $3.5 trillion will be spent on IT projects worldwide in 2017, however for every $1 billion invested in the US, $122 million is wasted due to poor project performance. Three in ten major IT projects fail, and 75% of business executives expect their software projects to fail. Fewer than one third of projects are completed on time and on budget. Failed projects can damage brands, partnerships and morale while losing investments and opportunities. Proper project planning and management is needed to avoid these issues and failures.
This document provides an introduction and overview of master data management (MDM). It begins with defining MDM as managing an organization's critical data. The agenda then outlines an overview of MDM, how it helps businesses succeed, and risks and challenges. It provides examples of master data and how MDM systems work. Key benefits of MDM include a single source of truth, reduced costs, and increased customer satisfaction by avoiding duplicate or inconsistent data across systems. Risks include data inconsistencies from mergers and acquisitions. Challenges involve determining what data to manage, ensuring consistency, and establishing appropriate data governance and information systems.
The document discusses enterprises' increasing investments in big data over the next three years. It notes that 70% of IT decision makers see exploiting big data as critical to future success, and 65% say they risk becoming irrelevant without embracing big data. Additionally, 64% see big data changing business boundaries as non-traditional providers enter industries. The reasons for this new interest in data are to make strategic decisions faster using insights from captured and combined data in new forms.
The document announces a conference called "Best Practices for Consumer Products" to be held October 5-7, 2015 in Atlanta, Georgia. The conference will bring together hundreds of business and IT professionals from consumer products companies to share best practices and innovative strategies around topics like integrated business planning, supply chain management, e-commerce, analytics, and more. Attendees will learn how to maximize their existing technology investments and stay on the leading edge of the industry.
This presentation covers the definition of Master Data Management, outlines 5 essential elements of MDM, and describe 10 real-world best practices for MDM and data governance and 4 advanced topic areas, based on years of experience in the field.
Key Steps to Kick Start Your Master Data Management Strategy in 2020Rahul Singh
Data is king. And, it has become the new support function for organizations ever since digitization has leapfrogged. Data management is becoming more necessary than ever to ensure its quality, accuracy, and integrity remain intact, all-around. That said, merely consolidating and managing data does not cut the mark anymore.
Gartner: Seven Building Blocks of Master Data ManagementGartner
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm.
Rahul Chande, Specialist Leader at Deloitte Consulting LLP, shares keys to master data management and effectiveness in the federal government sector at the 2015 Informatica Government Summit.
Proven Strategies to Leverage Your Customer Community to Grow Your BusinessSocious
Find out how businesses are leveraging stronger relationship with customers to identify revenue opportunities within their customer base and create more products that their markets love. During this presentation, you’ll learn:
Why peer-to-peer communities keep more customers engaged than other channels
How to ensure your customer community serves both your customers and your business
Actionable strategies for turning the social data in your community platform into profit
The document provides a template for creating a business case to justify investing in a marketing automation solution. It outlines sections to include such as an executive summary, opportunity overview, assumptions, business impact analysis, risks, and a recommendation. The template helps evaluate costs, benefits, and key factors for a marketing automation project to obtain management approval.
Critical 5 to succeed as agile product manager using scrumBimlesh Gundurao
This document discusses agile product management using SCRUM. It identifies 5 critical factors for success: 1) Understanding how agile product management differs from traditional approaches, 2) Distinguishing the roles of product owner and product manager, 3) Implementing agile practices at an enterprise scale, 4) Avoiding common pitfalls, and 5) Focusing on critical success factors like prioritization, communication, and progress measurement. The document provides details on each of these factors, with examples of how to structure product management organizations, prioritize backlogs, scale agile across teams, and common challenges to avoid.
This document provides a template for creating a business case to justify investing in a mobile marketing program. It outlines sections to include such as an executive summary, opportunity overview, assumptions, business impact analysis, risks, and a recommendation. The template helps the user build the business case by providing examples of what to include in each section.
This document provides an overview of a webinar on project portfolio management. It introduces the presenter and lists objectives of exploring how project portfolio management can help organizations align projects to strategic goals and achieve business benefits. It also discusses various aspects of project portfolio management such as defining the project portfolio scope, establishing selection criteria for projects, and managing a project portfolio through its lifecycle.
This document outlines a webinar on project portfolio management presented by Claude Maley. It includes information on the presentation objectives, the presenter's background, definitions of key terms, and the importance of aligning projects to organizational strategy and goals. Various aspects of project portfolio management such as project selection, governance, reporting, and organizational structure are also discussed.
Strategic marketing implementation and controlCIM Academy
This document provides information about the CIM Diploma in Professional Marketing. It outlines the learning outcomes and requirements for the Strategic Marketing and Implementation and Control modules. These modules teach skills such as situation analysis, strategic planning, resource management, and monitoring marketing plans. The document also discusses frameworks for implementing marketing strategies, prioritizing tactics, measuring success, and earning distinction marks in the program.
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.
Takeaways:
- Organizational thinking must change: Value-added data management practices must be considered and included as a vital part of your business strategy.
- Walk before you run with data focused initiatives: Understand and implement necessary data management prerequisites as a foundation, then build upon that foundation.
- There are no silver bullets: Tools alone are not the answer. Specifying business requirements, business practices and data governance are almost always more important.
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.
Check out more of our webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/
eSavvy webinar: Top 5+1 Tips of How to Maximize the ROI of a CRM InvestmenteSavvy
Do you want to know how to maximize the return of investment in a CRM system? Are you interested to find out how to truly use a CRM system to its full potential and how you can benefit from doing so? Then watch our next webinar, during which our Managing Director David Goad will share with you top tips on how to maximize the ROI of a CRM investment. David has been involved in more than 200 Business Application Implementations and was one of the contributing authors of the proven project management methodology recommended by Microsoft – Dynamics Sure Step. He will use his vast experience and project management knowledge to provide you with valuable insights about how to select your new CRM, how to prepare for CRM deployment projects and what to do during and after the project to maximize the results from your investment.
Automate and Differentiate: How to Create and Launch Experience and Proposal ...Hubbard One
How are leading law firms creating, launching, and managing databases to collect, store, and report on the experience and skills of their lawyers? This program addressed the question by discussing best practices on how to plan, implement, and maximize value with an experience management and proposal automation systems. Through real world examples attendees learned how to gain internal buy-in, define requirements and avoiding project delivery mistakes.
Paul Odette, Product Manager, and Amy Fielek, Director of Services for the Business Development Practice, lead a discussion with law firm panelists to provide project overviews, lessons learned, and tips for how to ensure success with your experience management and proposal automation programs.
This document provides a template and methodology for conducting a business intelligence (BI) assessment. The assessment examines organizational data management across several pillars including strategy, processes, applications, key performance indicators and people/ownership. It involves defining the current ("as-is") state, desired future ("to-be") state, and gap closing program to transition between the two states in phases. The gap closing program consists of strategic phases and tactical projects. The overall methodology includes planning, reviewing the as-is state, defining the to-be state, developing the gap closing program, and delivering the final assessment package.
Read on to:
1. Understand how strategic dashboards are different from other types of dashboards and how it tells the story of KPIs, actions, risks, objectives by linking strategy to operations.
2. Know the role of analytics in strategic business dashboards are a mainstay in today's business and How to build agility into your strategic dashboards.
3. Get to know the two fundamental ways of building dashboards and their differences.
4. Understand the difference between Technology stack and a business solution.
The PPT also contains a demonstration of a strategic dashboard solution.
An overview on how to ensure your CRM yroject will become an epic success. This presentation does not aim to cover all aspects, but focus on topics that have been important either in failure or success from my point of view, backed by research and business literature on relevant topics.
DOWNLOAD and read the speakers notes to get the full Picture, they are quite comprehensive on all slides
How to start the journey of Data science in your organizations. Find how to understand the business objectives, AI Frameworks, Methodologies and canvas models to help you depict business potential scenarios for justification.
MOCCA board member Linlin Li, VP of Digital, Demand Gen, Ops, and SDRs at Centrify presented at the recent Silicon Valley Marketo User Group how revenue alignment, innovation and data science are becoming the three pillars in a best in class Marketing Operations team.
Many organizations struggle with implementing process improvement. A key enabler is the skill of the change agent. This presentation examines the core skills and concepts needed to be an effective change agent.
UX STRAT Europe, Stefan Dieffenbacher: The User Experience Strategy Behind On...UX STRAT
This document outlines the strategy and approach for a large digital transformation project at a major European bank. It discusses:
1) Analyzing customer usage data which shows a shift towards digital channels over branches
2) Developing a framework to integrate all disciplines (e.g. strategy, UX, technology) into a comprehensive digital strategy landscape
3) The proposed multi-phase approach, including developing key concepts over 25 weeks followed by ongoing releases, with over 3,000 person days of effort from the consulting firm.
Similar to Selling MDM to Leadership: Evaluation Pitfalls (20)
The Comprehensive Guide to Validating Audio-Visual Performances.pdfkalichargn70th171
Ensuring the optimal performance of your audio-visual (AV) equipment is crucial for delivering exceptional experiences. AV performance validation is a critical process that verifies the quality and functionality of your AV setup. Whether you're a content creator, a business conducting webinars, or a homeowner creating a home theater, validating your AV performance is essential.
What to do when you have a perfect model for your software but you are constrained by an imperfect business model?
This talk explores the challenges of bringing modelling rigour to the business and strategy levels, and talking to your non-technical counterparts in the process.
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14 th Edition of International conference on computer visionShulagnaSarkar2
About the event
14th Edition of International conference on computer vision
Computer conferences organized by ScienceFather group. ScienceFather takes the privilege to invite speakers participants students delegates and exhibitors from across the globe to its International Conference on computer conferences to be held in the Various Beautiful cites of the world. computer conferences are a discussion of common Inventions-related issues and additionally trade information share proof thoughts and insight into advanced developments in the science inventions service system. New technology may create many materials and devices with a vast range of applications such as in Science medicine electronics biomaterials energy production and consumer products.
Nomination are Open!! Don't Miss it
Visit: computer.scifat.com
Award Nomination: https://x-i.me/ishnom
Conference Submission: https://x-i.me/anicon
For Enquiry: Computer@scifat.com
WMF 2024 - Unlocking the Future of Data Powering Next-Gen AI with Vector Data...Luigi Fugaro
Vector databases are transforming how we handle data, allowing us to search through text, images, and audio by converting them into vectors. Today, we'll dive into the basics of this exciting technology and discuss its potential to revolutionize our next-generation AI applications. We'll examine typical uses for these databases and the essential tools
developers need. Plus, we'll zoom in on the advanced capabilities of vector search and semantic caching in Java, showcasing these through a live demo with Redis libraries. Get ready to see how these powerful tools can change the game!
Photoshop Tutorial for Beginners (2024 Edition)alowpalsadig
Photoshop Tutorial for Beginners (2024 Edition)
Explore the evolution of programming and software development and design in 2024. Discover emerging trends shaping the future of coding in our insightful analysis."
Here's an overview:Introduction: The Evolution of Programming and Software DevelopmentThe Rise of Artificial Intelligence and Machine Learning in CodingAdopting Low-Code and No-Code PlatformsQuantum Computing: Entering the Software Development MainstreamIntegration of DevOps with Machine Learning: MLOpsAdvancements in Cybersecurity PracticesThe Growth of Edge ComputingEmerging Programming Languages and FrameworksSoftware Development Ethics and AI RegulationSustainability in Software EngineeringThe Future Workforce: Remote and Distributed TeamsConclusion: Adapting to the Changing Software Development LandscapeIntroduction: The Evolution of Programming and Software Development
Photoshop Tutorial for Beginners (2024 Edition)Explore the evolution of programming and software development and design in 2024. Discover emerging trends shaping the future of coding in our insightful analysis."Here's an overview:Introduction: The Evolution of Programming and Software DevelopmentThe Rise of Artificial Intelligence and Machine Learning in CodingAdopting Low-Code and No-Code PlatformsQuantum Computing: Entering the Software Development MainstreamIntegration of DevOps with Machine Learning: MLOpsAdvancements in Cybersecurity PracticesThe Growth of Edge ComputingEmerging Programming Languages and FrameworksSoftware Development Ethics and AI RegulationSustainability in Software EngineeringThe Future Workforce: Remote and Distributed TeamsConclusion: Adapting to the Changing Software Development LandscapeIntroduction: The Evolution of Programming and Software Development
The importance of developing and designing programming in 2024
Programming design and development represents a vital step in keeping pace with technological advancements and meeting ever-changing market needs. This course is intended for anyone who wants to understand the fundamental importance of software development and design, whether you are a beginner or a professional seeking to update your knowledge.
Course objectives:
1. **Learn about the basics of software development:
- Understanding software development processes and tools.
- Identify the role of programmers and designers in software projects.
2. Understanding the software design process:
- Learn about the principles of good software design.
- Discussing common design patterns such as Object-Oriented Design.
3. The importance of user experience (UX) in modern software:
- Explore how user experience can improve software acceptance and usability.
- Tools and techniques to analyze and improve user experience.
4. Increase efficiency and productivity through modern development tools:
- Access to the latest programming tools and languages used in the industry.
- Study live examples of applications
Alluxio Webinar | 10x Faster Trino Queries on Your Data PlatformAlluxio, Inc.
Alluxio Webinar
June. 18, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Jianjian Xie (Staff Software Engineer, Alluxio)
As Trino users increasingly rely on cloud object storage for retrieving data, speed and cloud cost have become major challenges. The separation of compute and storage creates latency challenges when querying datasets; scanning data between storage and compute tiers becomes I/O bound. On the other hand, cloud API costs related to GET/LIST operations and cross-region data transfer add up quickly.
The newly introduced Trino file system cache by Alluxio aims to overcome the above challenges. In this session, Jianjian will dive into Trino data caching strategies, the latest test results, and discuss the multi-level caching architecture. This architecture makes Trino 10x faster for data lakes of any scale, from GB to EB.
What you will learn:
- Challenges relating to the speed and costs of running Trino in the cloud
- The new Trino file system cache feature overview, including the latest development status and test results
- A multi-level cache framework for maximized speed, including Trino file system cache and Alluxio distributed cache
- Real-world cases, including a large online payment firm and a top ridesharing company
- The future roadmap of Trino file system cache and Trino-Alluxio integration
Unlock the Secrets to Effortless Video Creation with Invideo: Your Ultimate G...The Third Creative Media
"Navigating Invideo: A Comprehensive Guide" is an essential resource for anyone looking to master Invideo, an AI-powered video creation tool. This guide provides step-by-step instructions, helpful tips, and comparisons with other AI video creators. Whether you're a beginner or an experienced video editor, you'll find valuable insights to enhance your video projects and bring your creative ideas to life.
Nashik's top web development company, Upturn India Technologies, crafts innovative digital solutions for your success. Partner with us and achieve your goals
Transforming Product Development using OnePlan To Boost Efficiency and Innova...OnePlan Solutions
Ready to overcome challenges and drive innovation in your organization? Join us in our upcoming webinar where we discuss how to combat resource limitations, scope creep, and the difficulties of aligning your projects with strategic goals. Discover how OnePlan can revolutionize your product development processes, helping your team to innovate faster, manage resources more effectively, and deliver exceptional results.
Stork Product Overview: An AI-Powered Autonomous Delivery FleetVince Scalabrino
Imagine a world where instead of blue and brown trucks dropping parcels on our porches, a buzzing drove of drones delivered our goods. Now imagine those drones are controlled by 3 purpose-built AI designed to ensure all packages were delivered as quickly and as economically as possible That's what Stork is all about.
Flutter vs. React Native: A Detailed Comparison for App Development in 2024dhavalvaghelanectarb
Choosing the right framework for your cross-platform mobile app can be a tough decision. Both Flutter and React Native offer compelling features and have earned their place in the development world. Here is a detailed comparison to help you weigh their strengths and weaknesses. Here are the pros and cons of developing mobile apps in React Native vs Flutter.
Mobile App Development Company In Noida | Drona InfotechDrona Infotech
React.js, a JavaScript library developed by Facebook, has gained immense popularity for building user interfaces, especially for single-page applications. Over the years, React has evolved and expanded its capabilities, becoming a preferred choice for mobile app development. This article will explore why React.js is an excellent choice for the Best Mobile App development company in Noida.
Visit Us For Information: https://www.linkedin.com/pulse/what-makes-reactjs-stand-out-mobile-app-development-rajesh-rai-pihvf/
Streamlining End-to-End Testing Automation with Azure DevOps Build & Release Pipelines
Automating end-to-end (e2e) test for Android and iOS native apps, and web apps, within Azure build and release pipelines, poses several challenges. This session dives into the key challenges and the repeatable solutions implemented across multiple teams at a leading Indian telecom disruptor, renowned for its affordable 4G/5G services, digital platforms, and broadband connectivity.
Challenge #1. Ensuring Test Environment Consistency: Establishing a standardized test execution environment across hundreds of Azure DevOps agents is crucial for achieving dependable testing results. This uniformity must seamlessly span from Build pipelines to various stages of the Release pipeline.
Challenge #2. Coordinated Test Execution Across Environments: Executing distinct subsets of tests using the same automation framework across diverse environments, such as the build pipeline and specific stages of the Release Pipeline, demands flexible and cohesive approaches.
Challenge #3. Testing on Linux-based Azure DevOps Agents: Conducting tests, particularly for web and native apps, on Azure DevOps Linux agents lacking browser or device connectivity presents specific challenges in attaining thorough testing coverage.
This session delves into how these challenges were addressed through:
1. Automate the setup of essential dependencies to ensure a consistent testing environment.
2. Create standardized templates for executing API tests, API workflow tests, and end-to-end tests in the Build pipeline, streamlining the testing process.
3. Implement task groups in Release pipeline stages to facilitate the execution of tests, ensuring consistency and efficiency across deployment phases.
4. Deploy browsers within Docker containers for web application testing, enhancing portability and scalability of testing environments.
5. Leverage diverse device farms dedicated to Android, iOS, and browser testing to cover a wide range of platforms and devices.
6. Integrate AI technology, such as Applitools Visual AI and Ultrafast Grid, to automate test execution and validation, improving accuracy and efficiency.
7. Utilize AI/ML-powered central test automation reporting server through platforms like reportportal.io, providing consolidated and real-time insights into test performance and issues.
These solutions not only facilitate comprehensive testing across platforms but also promote the principles of shift-left testing, enabling early feedback, implementing quality gates, and ensuring repeatability. By adopting these techniques, teams can effectively automate and execute tests, accelerating software delivery while upholding high-quality standards across Android, iOS, and web applications.
Orca: Nocode Graphical Editor for Container OrchestrationPedro J. Molina
Tool demo on CEDI/SISTEDES/JISBD2024 at A Coruña, Spain. 2024.06.18
"Orca: Nocode Graphical Editor for Container Orchestration"
by Pedro J. Molina PhD. from Metadev
Why Apache Kafka Clusters Are Like Galaxies (And Other Cosmic Kafka Quandarie...Paul Brebner
Closing talk for the Performance Engineering track at Community Over Code EU (Bratislava, Slovakia, June 5 2024) https://eu.communityovercode.org/sessions/2024/why-apache-kafka-clusters-are-like-galaxies-and-other-cosmic-kafka-quandaries-explored/ Instaclustr (now part of NetApp) manages 100s of Apache Kafka clusters of many different sizes, for a variety of use cases and customers. For the last 7 years I’ve been focused outwardly on exploring Kafka application development challenges, but recently I decided to look inward and see what I could discover about the performance, scalability and resource characteristics of the Kafka clusters themselves. Using a suite of Performance Engineering techniques, I will reveal some surprising discoveries about cosmic Kafka mysteries in our data centres, related to: cluster sizes and distribution (using Zipf’s Law), horizontal vs. vertical scalability, and predicting Kafka performance using metrics, modelling and regression techniques. These insights are relevant to Kafka developers and operators.
2. 2
Part 1: Organizational Readiness
• What Does “Ready” Look Like?
Part 2: Defining the Why
• Justification – Prioritization - Rightsizing
Part 3: TCO Calculation
• Solution Complexity Drives TCO
Part 4: Program Scope
• Quick Wins – Where to Focus – Implementation Styles
Part 5: Evaluation Pitfalls
• Business Outcomes – Selection Criteria – What to Look for
Part 6: Beyond the 1st Use-Case
• MDM as a Way of Life – Operational vs. Analytical MDM
PANEL TOPICS
3. 3
Bill O’Kane
Former Gartner Analyst and Profisee VP & MDM Strategist; Bill served for eight years as Vice President of Data and
Analytics and Magic Quadrant lead author at Gartner.
FEATURED SPEAKERS
Christopher Dwight
VP of Customer Success at Profisee; Christopher has been in the enterprise information management and master
data management (MDM) space for more than 20 years.
Harbert Bernard
Value Management Consultant at Profisee; Harbert utilizes his expertise around building business cases for
investments in technology to develop BIRs (Business Impact Roadmaps) for a range of enterprises.
Martin Boyd
VP Product Marketing at Profisee; Martin has over ten years’ experience in MDM, governance and data quality.
4. 4
“
IF YOU DON’T KNOW WHERE YOU’RE
GOING ANY ROAD WILL GET YOU
THERE.
- LEWIS CARROLL, ALICE IN WONDERLAND
Business outcomes, not capabilities
Remember you are evaluating a platform, not an app!
Capability driven evaluations - misleading
"Customer 360" is not a business case!
What are your selection criteria?
How to structure an evaluation process
Your data, not theirs (& use realistic volumes)
Evaluate against BUSINESS use cases – do not focus on features (then ask HOW did you do that?)
Avoid inflexible eval processes (often long list of features) – level playing field is ‘fair’ but unlikely to result in good decision
Properly staff eval – Have available manpower to examine the vendor response – need to allocate time
Product features that sound great and demo well, but are never implemented
ML for matching (test your vendor! Need real world examples)
Automated metadata discovery
Features that rely on high quality data (that you don’t have!) – trust scoring
Differences between IaaS, SaaS, PaaS
Technology fit – match to existing skills
What to look for?
Realistic TCO for out-years
Look beyond first use case
Effort & licensing implications – need DETAILED estimation of services
Configuration vs customization – need detailed quote
Identify core functionality vs. work arounds – “HOW did you do that?” (workarounds, vs core functionality)
Is vendor willing to lift the hood? Why won’t they be transparent?
Ask for line item quote – can be surprising!
Ask for installation guides – how many, how complex?