This document summarizes Perficient's capabilities in providing master data management (MDM) solutions for financial services clients. Perficient has expertise in implementing MDM to create a unified customer view across systems and business units. Key benefits of MDM include improved customer experience, increased revenue opportunities, and reduced costs. The document also discusses current industry trends like social media, mobility, and big data that are driving greater need for MDM.
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Gartner: Master Data Management FunctionalityGartner
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
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Presentation of use cases of Master Data Management for product Data. It presents the five facets of MDM for product Data (MDM for Material, MDM for Lean Managed Services, MDM for Regulated Products, Product Information Management, MDM for “Anything”) and how Talend platform for MDM can adress them
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
Digital Transformation is a top priority for many organizations, and a successful digital journey requires a strong data foundation. Creating this digital transformation requires a number of core data management capabilities such as MDM, With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Data Governance — Aligning Technical and Business ApproachesDATAVERSITY
Data Governance can have a varied definition, depending on the audience. To many, data governance consists of committee meetings and stewardship roles. To others, it focuses on technical data management and controls. Holistic data governance combines both of these aspects, and a robust data architecture and associated diagrams can be the “glue” that binds business and IT governance together. Join this webinar for practical tips and hands-on exercises for aligning data architecture & data governance for business and IT success.
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Gartner: Master Data Management FunctionalityGartner
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
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Presentation of use cases of Master Data Management for product Data. It presents the five facets of MDM for product Data (MDM for Material, MDM for Lean Managed Services, MDM for Regulated Products, Product Information Management, MDM for “Anything”) and how Talend platform for MDM can adress them
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
Digital Transformation is a top priority for many organizations, and a successful digital journey requires a strong data foundation. Creating this digital transformation requires a number of core data management capabilities such as MDM, With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Data Governance — Aligning Technical and Business ApproachesDATAVERSITY
Data Governance can have a varied definition, depending on the audience. To many, data governance consists of committee meetings and stewardship roles. To others, it focuses on technical data management and controls. Holistic data governance combines both of these aspects, and a robust data architecture and associated diagrams can be the “glue” that binds business and IT governance together. Join this webinar for practical tips and hands-on exercises for aligning data architecture & data governance for business and IT success.
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
Essential Reference and Master Data ManagementDATAVERSITY
Data tends to pile up and can be rendered unusable or obsolete without careful maintenance processes. Reference and Master Data Management (MDM) has been a popular Data Management approach to effectively gain mastery over not just the data but the supporting architecture for processing it. This webinar presents MDM as a strategic approach to improving and formalizing practices around those data items that provide context for many organizational transactions: its master data. Too often, MDM has been implemented technology-first and achieved the same very poor track record (one-third succeeding on-time, within budget, and achieving planned functionality). MDM success depends on a coordinated approach typically involving Data Governance and Data Quality activities.
Learning objectives:
- Understand foundational reference and MDM concepts based on the Data Management Body of Knowledge (DMBOK)
- Understand why these are an important component of your Data Architecture
- Gain awareness of Reference and MDM Frameworks and building blocks
- Know what MDM guiding principles consist of and best practices
- Know how to utilize reference and MDM in support of business strategy
To take a “ready, aim, fire” tactic to implement Data Governance, many organizations assess themselves against industry best practices. The process is not difficult or time-consuming and can directly assure that your activities target your specific needs. Best practices are always a strong place to start.
Join Bob Seiner for this popular RWDG topic, where he will provide the information you need to set your program in the best possible direction. Bob will walk you through the steps of conducting an assessment and share with you a set of typical results from taking this action. You may be surprised at how easy it is to organize the assessment and may hear results that stimulate the actions that you need to take.
In this webinar, Bob will share:
- The value of performing a Data Governance best practice assessment
- A practical list of industry Data Governance best practices
- Criteria to determine if a practice is best practice
- Steps to follow to complete an assessment
- Typical recommendations and actions that result from an assessment
Strategic Business Requirements for Master Data Management SystemsBoris Otto
This presentation describes strategic business requirements of master data management (MDM) systems. The requirements were developed in a consortium research approach by the Institute of Information Management at the University of St. Gallen, Switzerland, and 20 multinational enterprises.
The presentation was given at the 17th Amercias Conference on Information Systems (AMCIS 2011) in Detroit, MI.
The research paper on which this presentation is based on can be found here: http://www.alexandria.unisg.ch/Publikationen/Zitation/Boris_Otto/177697
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall Enterprise Architecture for enhanced business value and success.
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.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Data Modeling, Data Governance, & Data QualityDATAVERSITY
Data Governance is often referred to as the people, processes, and policies around data and information, and these aspects are critical to the success of any data governance implementation. But just as critical is the technical infrastructure that supports the diverse data environments that run the business. Data models can be the critical link between business definitions and rules and the technical data systems that support them. Without the valuable metadata these models provide, data governance often lacks the “teeth” to be applied in operational and reporting systems.
Join Donna Burbank and her guest, Nigel Turner, as they discuss how data models & metadata-driven data governance can be applied in your organization in order to achieve improved data quality.
Tackling Data Quality problems requires more than a series of tactical, one-off improvement projects. By their nature, many Data Quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process, and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.
Most Common Data Governance Challenges in the Digital EconomyRobyn Bollhorst
Todays’ increasing emphasis on differentiation in the digital economy further complicates the data governance challenge. Learn about today’s common challenges and about the new adaptations that are required to support the digital era. Avoid the pitfalls and follow along on Johnson & Johnson’s journey to:
- Establish and scale a best in class enterprise data governance program
- Identify and focus on the most critical data and information to bolster incremental wins and garner executive support
- Ensure readiness for automation with SAP MDG on HANA
Where Data Architecture and Data Governance CollideDATAVERSITY
While collide is perhaps a strong term to use to describe the key area where Data Architecture and Data Governance interact, it does provide motivation to perhaps calm the traffic and avoid further collisions. In order to harmoniously interact, architecture and governance must literally be working from the same diagram (singing from the same sheet of music). The worst time to try to accomplish this is on a short-term decision. Better still to educate each group to the function of the other and major issues upcoming. A shared Data Literacy exercise can provide a good starting point.
Learning objectives:
- Gaining a good understanding of both important topics, each’s relationship to the other, and what is required for each to be successful
- Not to have the first conversation be the important one
- Coordination is key requiring necessary interdependencies and sequencing
- Integration challenges can be valued, assisting shared priority development
New Analytic Uses of Master Data Management in the EnterpriseDATAVERSITY
Companies all over the world are going through digital transformation now, which in many cases is all about maturing the data environment and the use of data. Master data is key to this effort. All transformative projects require master data and usually many subject areas.
What could you accomplish if cultivating master data didn’t have to be part of every project and could be accessed as a service?
We’ll look at creative enterprise use cases of Master Data Management in the enterprise. We’ll see what some MDM vendors are doing with AI and how the future of MDM will be shaped by looking at some specific MDM actions influenced by AI.
Data Catalogs Are the Answer – What is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
Metadata is hotter than ever, according to a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information.
While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to today’s organization, and provide insights into building successful business strategies for metadata adoption & use.
How to identify the correct Master Data subject areas & tooling for your MDM...Christopher Bradley
1. What are the different Master Data Management (MDM) architectures?
2. How can you identify the correct Master Data subject areas & tooling for your MDM initiative?
3. A reference architecture for MDM.
4. Selection criteria for MDM tooling.
chris.bradley@dmadvisors.co.uk
Making data based decisions makes instinctive sense, and evidence is mounting that it makes strong commercial sense too.
Whilst being aware of this kind of potential is undoubtedly valuable, knowing it and doing something about it are two very different things.
So how do you go about becoming a data driven organization?
And how does the Data Management Maturity Assessment help in achieving your data strategy goals?
The what, why, and how of master data managementMohammad Yousri
This presentation explains what MDM is, why it is important, and how to manage it, while identifying some of the key MDM patterns and best practices that are emerging. This presentation is a high-level treatment of the problem space.
The presentation is summarizing the article of Microsoft in a simple way.
https://msdn.microsoft.com/en-us/library/bb190163.aspx
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
Essential Reference and Master Data ManagementDATAVERSITY
Data tends to pile up and can be rendered unusable or obsolete without careful maintenance processes. Reference and Master Data Management (MDM) has been a popular Data Management approach to effectively gain mastery over not just the data but the supporting architecture for processing it. This webinar presents MDM as a strategic approach to improving and formalizing practices around those data items that provide context for many organizational transactions: its master data. Too often, MDM has been implemented technology-first and achieved the same very poor track record (one-third succeeding on-time, within budget, and achieving planned functionality). MDM success depends on a coordinated approach typically involving Data Governance and Data Quality activities.
Learning objectives:
- Understand foundational reference and MDM concepts based on the Data Management Body of Knowledge (DMBOK)
- Understand why these are an important component of your Data Architecture
- Gain awareness of Reference and MDM Frameworks and building blocks
- Know what MDM guiding principles consist of and best practices
- Know how to utilize reference and MDM in support of business strategy
To take a “ready, aim, fire” tactic to implement Data Governance, many organizations assess themselves against industry best practices. The process is not difficult or time-consuming and can directly assure that your activities target your specific needs. Best practices are always a strong place to start.
Join Bob Seiner for this popular RWDG topic, where he will provide the information you need to set your program in the best possible direction. Bob will walk you through the steps of conducting an assessment and share with you a set of typical results from taking this action. You may be surprised at how easy it is to organize the assessment and may hear results that stimulate the actions that you need to take.
In this webinar, Bob will share:
- The value of performing a Data Governance best practice assessment
- A practical list of industry Data Governance best practices
- Criteria to determine if a practice is best practice
- Steps to follow to complete an assessment
- Typical recommendations and actions that result from an assessment
Strategic Business Requirements for Master Data Management SystemsBoris Otto
This presentation describes strategic business requirements of master data management (MDM) systems. The requirements were developed in a consortium research approach by the Institute of Information Management at the University of St. Gallen, Switzerland, and 20 multinational enterprises.
The presentation was given at the 17th Amercias Conference on Information Systems (AMCIS 2011) in Detroit, MI.
The research paper on which this presentation is based on can be found here: http://www.alexandria.unisg.ch/Publikationen/Zitation/Boris_Otto/177697
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall Enterprise Architecture for enhanced business value and success.
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.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Data Modeling, Data Governance, & Data QualityDATAVERSITY
Data Governance is often referred to as the people, processes, and policies around data and information, and these aspects are critical to the success of any data governance implementation. But just as critical is the technical infrastructure that supports the diverse data environments that run the business. Data models can be the critical link between business definitions and rules and the technical data systems that support them. Without the valuable metadata these models provide, data governance often lacks the “teeth” to be applied in operational and reporting systems.
Join Donna Burbank and her guest, Nigel Turner, as they discuss how data models & metadata-driven data governance can be applied in your organization in order to achieve improved data quality.
Tackling Data Quality problems requires more than a series of tactical, one-off improvement projects. By their nature, many Data Quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process, and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.
Most Common Data Governance Challenges in the Digital EconomyRobyn Bollhorst
Todays’ increasing emphasis on differentiation in the digital economy further complicates the data governance challenge. Learn about today’s common challenges and about the new adaptations that are required to support the digital era. Avoid the pitfalls and follow along on Johnson & Johnson’s journey to:
- Establish and scale a best in class enterprise data governance program
- Identify and focus on the most critical data and information to bolster incremental wins and garner executive support
- Ensure readiness for automation with SAP MDG on HANA
Where Data Architecture and Data Governance CollideDATAVERSITY
While collide is perhaps a strong term to use to describe the key area where Data Architecture and Data Governance interact, it does provide motivation to perhaps calm the traffic and avoid further collisions. In order to harmoniously interact, architecture and governance must literally be working from the same diagram (singing from the same sheet of music). The worst time to try to accomplish this is on a short-term decision. Better still to educate each group to the function of the other and major issues upcoming. A shared Data Literacy exercise can provide a good starting point.
Learning objectives:
- Gaining a good understanding of both important topics, each’s relationship to the other, and what is required for each to be successful
- Not to have the first conversation be the important one
- Coordination is key requiring necessary interdependencies and sequencing
- Integration challenges can be valued, assisting shared priority development
New Analytic Uses of Master Data Management in the EnterpriseDATAVERSITY
Companies all over the world are going through digital transformation now, which in many cases is all about maturing the data environment and the use of data. Master data is key to this effort. All transformative projects require master data and usually many subject areas.
What could you accomplish if cultivating master data didn’t have to be part of every project and could be accessed as a service?
We’ll look at creative enterprise use cases of Master Data Management in the enterprise. We’ll see what some MDM vendors are doing with AI and how the future of MDM will be shaped by looking at some specific MDM actions influenced by AI.
Data Catalogs Are the Answer – What is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
Metadata is hotter than ever, according to a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information.
While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to today’s organization, and provide insights into building successful business strategies for metadata adoption & use.
How to identify the correct Master Data subject areas & tooling for your MDM...Christopher Bradley
1. What are the different Master Data Management (MDM) architectures?
2. How can you identify the correct Master Data subject areas & tooling for your MDM initiative?
3. A reference architecture for MDM.
4. Selection criteria for MDM tooling.
chris.bradley@dmadvisors.co.uk
Making data based decisions makes instinctive sense, and evidence is mounting that it makes strong commercial sense too.
Whilst being aware of this kind of potential is undoubtedly valuable, knowing it and doing something about it are two very different things.
So how do you go about becoming a data driven organization?
And how does the Data Management Maturity Assessment help in achieving your data strategy goals?
The what, why, and how of master data managementMohammad Yousri
This presentation explains what MDM is, why it is important, and how to manage it, while identifying some of the key MDM patterns and best practices that are emerging. This presentation is a high-level treatment of the problem space.
The presentation is summarizing the article of Microsoft in a simple way.
https://msdn.microsoft.com/en-us/library/bb190163.aspx
resentation of use cases of Master Data Management for Customer Data. It presents the business drivers and how Talend platform for MDM can adress them.
Unlocking Success in the 3 Stages of Master Data ManagementPerficient, Inc.
Master data management (MDM) comprises the processes, governance, policies, standards and tools that define and manage critical data. MDM is used to conduct strategic initiatives such as customer 360, product excellence and operational efficiency.
The quality of enterprise Information depends on the master data, so getting it right should be a high priority. This webinar will highlight key factors needed for success in each of the three stages of the MDM journey:
Planning
Implementation
Steady state
We review each stage in detail and provide insight into planning and collaborative activities. In this slideshare you will learn:
Best practices, tips and techniques for a successful MDM program
Top considerations for business case building, architecture and going live
How to support the overall program after launching your MDM program
Organizations across diverse industries are in pursuit of Customer 360, by integrating customer information across multiple channels, systems, devices and products. Having a 360-degree view of the customer enables enterprises to improve the interaction experience, drive customer loyalty and improve retention. However delivering a true Customer 360 can be very challenging.
Mike Ferguson, managing director of Intelligent Business Strategies, highlights his top ten worst practices in Master Data Management (MDM) in this Information Builders webinar slideshow.
How Credit Card Processing Impacts Conversion RateAffiliate Summit
Your merchant processing might be holding back the true potential of your affiliate program. Learn how to increase conversions with better banking, fraud control, and small checkout tips.
Experience level: Beginner, Intermediate, Advanced
Target audience: Affiliates/Publishers, Merchants/Advertisers
Niche/vertical: Credit cards
John Monarch, President, Monarch Holdings LLC (Twitter @papajohn56)
Business Intelligence (BI) and Data Management Basics amorshed
A one-day training course on the Concepts of Data Management and Business Intelligence (BI) in the DX age
A Basic Review of BI and DM
How to Implement BI
A review of BI Tools and 2022 Gartner Quadrant Magic
Basics of Data warehouse (DWH)
An introductions to Power BI
Components of Power BI
Steps for BI Implementation
Data Culture
Intro to ETL and ELT
OLAP files and Architecture
Digital transformation or DX review
A glance at DMBOK2.0 framework
BI Challenges
Data Governance
Data Integration
Data Security and Privacy in DMBOK2.0
Data-Driven Organization
Data and BI Maturity Model
Traditional BI
Self-service BI
who is DMP
who is BI developer
what is Metadata
what is Master data
Data Quality
Data Literacy
Benefits of BI
BI features
How does BI Works?
Modern BI
Data Analytics
BI Architecture
Data Types
Data Lake
Data Mart
Data Silo
Data Visualization
Power BI Architecture and components
Accelerating Personalization to Cut Through Digital NoisePrecisely
Your customers’ inboxes are overflowing with unread email. Even social media and text messages are ignored. There is simply too much digital content and too little time to consume it.
So how do you stand out and get your customers’ attention? You need to go beyond traditional Customer 360 efforts. To get your customers’ attention, you need to maximize personalization based on context.
Basics of BI and Data Management (Summary).pdfamorshed
Basics of Business Intelligence and Data Management
BI Architecture
How BI works?
DMBOK framework
what is Data literacy
Data quality
Data Governance
what is self-service or modern BI
Power BI Architecture
How Power BI Works
BI Implementation steps
The Evolving Role of the Data Architect – What Does It Mean for Your Career?DATAVERSITY
If you’re a data architect, you’ve heard it all—from ‘data management is the sexiest job of the 21st century’ to ‘data management is dead’. The truth almost certainly lies somewhere in the middle of the extremes, but how can you make sense of the true future of the data architect’s role in the rapidly-changing data landscape? The Data Architect holds a unique position as the translator between business value and technical implementation.
Join this webinar to learn how you can take advantage of the uniqueness of this role to catapult your career to the next level.
Modernizing Integration with Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3CMqS0E
Today, businesses have more data and data types combined with more complex ecosystems than they have ever had before. Examples include on-premise data marts, data warehouses, data lakes, applications, spreadsheets, IoT data, sensor data, unstructured, etc. combined with cloud data ecosystems like Snowflake, Big Query, Azure Synapse, Amazon S3, Redshift, Databricks, SaaS apps, such as Salesforce, Oracle, Service Now, Workday, and on and on.
Data, Analytics, Data Science and Architecture teams are struggling to provide the business users with the right data as quickly and efficiently as possible to quickly enable Analytics, Dashboards, BI, Reports, etc. Unfortunately, many enterprises seek to meet this pressing need by utilizing antiquated and legacy 40+ year-old approaches. There is a better way. Proven by thousands of other companies.
As Forrester so astutely reported in their recent Total Economic Impact Study, companies who employed Data Virtualization reported a “65% decrease in data delivery times over ETL” and an “83% reduction in time to new revenue.”
Join us for this very educational webinar to learn firsthand from Denodo Technologies and Fusion Alliance how:
- Data Virtualization helps your company save time and money by eliminating superfluous ETL pipelines and data replication.
- Data Virtualization can become the cornerstone of your modern data approach to deliver data faster and more efficiently than old legacy approaches at enterprise scale.
- How quickly and easily, Data Virtualization can scale, even in the most complex environments, to create a universal abstraction semantic model(s) for all of your cloud, on premise, structured, unstructured and hybrid data
- Data Mesh and Data Fabric architecture patterns for maximum reuse
- Other customers have used, and are using, Data Virtualization to tackle their toughest data integration and data delivery challenges
- Fusion Alliance can help you define a data strategy tailored to your organization’s needs and requirements, and how they can help you achieve success and enable your business with self-service capabilities
Data Governance Best Practices, Assessments, and RoadmapsDATAVERSITY
When starting or evaluating the present state of your Data Governance program, it is important to focus on best practices such that you don’t take a ready, fire, aim approach. Best practices need to be practical and doable to be selected for your organization, and the program must be at risk if the best practice is not achieved.
Join Bob Seiner for an important webinar focused on industry best practice around standing up formal Data Governance. Learn how to assess your organization against the practices and deliver an effective roadmap based on the results of conducting the assessment.
In this webinar, Bob will focus on:
- Criteria to select the appropriate best practices for your organization
- How to define the best practices for ultimate impact
- Assessing against selected best practices
- Focusing the recommendations on program success
- Delivering a roadmap for your Data Governance program
What's the relationship between digital disruption and digital transformation? How can organisations manage their digital transformations better and achieve their business transformations faster? What role does digital culture play and how do you develop a digital culture?
New Zealand businesses and government agencies are all facing the effects of digital technology and responding to the changing nature of market expectations.
In this presentation, delivered at Solnet's CXO Digital Transformation seminars, Phil Coop, (Digital Transformation Director, Solnet) discusses the roles of focus, innovation, team structure, culture, data, and UX as ingredients to a successful digital transformation.
The Business Value of Metadata for Data GovernanceRoland Bullivant
In today’s digital economy, data drives the core processes that deliver profitability and growth - from marketing, to finance, to sales, supply chain, and more. It is also likely that for many large organizations much of their key data is retained in application packages from SAP, Oracle, Microsoft, Salesforce and others. In order to ensure that their foundational data infrastructure runs smoothly, most organizations have adopted a data governance initiative. These typically focus on the people and processes around managing data and information. Without an actionable link to the physical systems that run key business processes, however, governance programs can often lack the ‘teeth’ to effectively implement business change.
Metadata management is a process that can link business processes and drivers with the technical applications that support them. This makes data governance actionable and relevant in today’s fast-paced and results-driven business environment. One of the challenges facing data governance teams however, is the variety in format, accessibility and complexity of metadata across the organization’s systems.
DAS Slides: Data Quality Best PracticesDATAVERSITY
Tackling data quality problems requires more than a series of tactical, one off improvement projects. By their nature, many data quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control data quality issues in your organization.
Big Data in Financial Services: How to Improve Performance with Data-Driven D...Perficient, Inc.
Most banking and financial services organizations have only scratched the surface of leveraging customer data to transform their business, realize new revenue opportunities, manage risk and address customer loyalty. Yet a business’s digital footprint continues to evolve as automated payments, location-based purchases, and unstructured customer communications continue to influence the technology landscape for financial services.
Data Modeling Best Practices - Business & Technical ApproachesDATAVERSITY
Data Modeling is hotter than ever, according to a number of recent surveys. Part of the appeal of data models lies in their ability to translate complex data concepts in an intuitive, visual way to both business and technical stakeholders. This webinar provides real-world best practices in using Data Modeling for both business and technical teams.
Improving Data Literacy Around Data ArchitectureDATAVERSITY
Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.
Align Business Data & Analytics for Digital TransformationPerficient, Inc.
Your success in the digital world relies primarily on how well you manage and analyze the data coming from disparate internal systems and external channels. You need to understand how to innovate and leverage digital data to drive sales and productivity.
Existing principles driving traditional data architecture are inadequate to support the volume, variety, and velocity of this new data ecosystem. In these scenarios, information governance (master data management, metadata, data quality and data governance) becomes highly critical in terms of providing the context for operational, competitive and advanced analytics.
Companies require a data architecture and strategy that can support efficient digital transformation by unlocking the value in all data sources to provide mission-critical insights and informed decision-making.
Our experts covered:
-Five information management pillars necessary for digital transformation
-Stages of digital information maturity, reflecting the typical path of an organization implementing this new data ecosystem
-Issues, challenges, and approaches to governing this new architecture
Data Architecture Strategies: Building an Enterprise Data Strategy – Where to...DATAVERSITY
The majority of successful organizations in today’s economy are data-driven, and innovative companies are looking at new ways to leverage data and information for strategic advantage. While the opportunities are vast, and the value has clearly been shown across a number of industries in using data to strategic advantage, the choices in technology can be overwhelming. From Big Data to Artificial Intelligence to Data Lakes and Warehouses, the industry is continually evolving to provide new and exciting technological solutions.
This webinar will help make sense of the various data architectures & technologies available, and how to leverage them for business value and success. A practical framework will be provided to generate “quick wins” for your organization, while at the same time building towards a longer-term sustainable architecture. Case studies will also be provided to show how successful organizations have successfully built a data strategies to support their business goals.
Similar to Create a 'Customer 360' with Master Data Management for Financial Services (20)
The world is quite a different place than it was six months ago, and with the 2020 holiday season fast approaching, the pressure is on to meet revenue goals in what’s been an uncertain year.
In August, we surveyed 154 marketing executives to find out what they think is likely to happen this holiday season and how they are preparing for it. The results are fascinating, and we’ve distilled them into clear actions you can take right now to adapt and prepare for a very different 2020 holiday season.
In this webinar, Eric Enge (Principal, Digital Marketing at Perficient) and Jim Hertzfeld (Chief Strategist, Digital at Perficient) discussed:
How marketers have already adapted and where they see the most opportunity moving forward
What will be different this holiday season and how to adjust your strategy accordingly
Ways to identify and meet changing customer expectations, wants, and needs
How to determine if your priorities or investments should change
What actions you can take right now to be successful
Transforming Pharmacovigilance Workflows with AI & Automation Perficient, Inc.
Medical information call centers have an opportunity to transform the way they capture, code, and analyze adverse events (AEs) and product quality complaints (PQCs) with artificial intelligence (AI) and automation.
The use of such innovative technology improves data quality and consistency, compliance, and operational efficiency. It helps reduce the frequency of your pharmacovigilance (PV) operations resources going home, saying, “I have more to do at the end of the day than I did when I started."
Our one-hour, on-demand webinar shows you how you can use AI and automation to turbo-charge your end-to-end PV system. Use cases and demonstrations will include:
Analyzing safety data
Auto-coding verbatim terms to official medical dictionary terms
Auto-creating an AE case in your database
Converting speech to text
The Secret to Acquiring and Retaining Customers in Financial ServicesPerficient, Inc.
Data, when leveraged effectively, can help you segment and target customers, analyze spending habits, and can create a personalized experience that builds value and customer loyalty.
Without a 360-degree view of your customers, you can’t properly target them with real-time personalized offers, advice, and other services. In addition, lack of customer intelligence creates lost opportunities for banks and insurers to cross-sell and upsell new products and services.
Our one-hour webinar covered how customer intelligence platforms can help you engage, acquire, and retain customers.
Oracle Strategic Modeling Live: Defined. Discussed. Demonstrated.Perficient, Inc.
The only thing certain about forecasting in a volatile economy is that the future is unpredictable. Historically, organizations have effectively utilized statistical techniques for short-term business planning, but leveraging actuals no longer allows us to predict the future. The ability to be prepared, responsive, and agile under these conditions is becoming a crucial success factor. Oracle Strategic Modeling can help you better navigate change to cope with uncertainty.
If your CFO’s questions regarding earnings, liquidity, and cash flow are unceasing and far-reaching, watch our on-demand webinar for a deep dive into strategic modeling. We modeled real-world scenarios to show how you can:
Quickly and easily develop a hierarchical model of your business
Leverage multiple pre-built functions to forecast key performance drivers
Provide transparency on forecasted financials via audit trail
Utilize goal seek to set financial targets and estimate the financials drivers necessary to achieve it
Perform sophisticated “what-if” analysis via simulations to improve the accuracy of your forecast
Use built-in dashboard functionality to deliver powerful reporting capabilities
While many stay-at-home orders have been lifted, consumers’ new digital buying behaviors and habits are here to stay. Watch our panel discussion on the accelerated need for commerce and learn how commerce and content can transform our digital economy.
Topics include:
-What is the “experience economy” and how do you leverage it? -If you move beyond product and price, what’s next?
-How business models have shifted and what you can do to break down silos and leverage new processes to capture the digital dollar.
-How organizations have built agile teams to address the ever-changing needs of customers, including responsive approaches that address the omnichannel consumer.
-Technologies that are best suited to enable your business and customers – and how headless commerce has changed the game.
-How the future of commerce is changing, and what you should do now to prepare.
Our panel features Jordan Jewell, IDC Research analyst known for his insight into the commerce industry. Joining him from Perficient is general manager Brian Beckham, who brings deep expertise in content management and empowering organizations in their digital transformations. Rounding out the panel is Episerver’s Joey Moore, who has spent the last decade helping organizations across the globe advance their digital maturity.
Centene's Financial Transformation Journey: A OneStream Success StoryPerficient, Inc.
Centene, a large multi-line managed care organization, was looking to modernize and streamline its corporate performance management (CPM) applications.
Centene had to move data between platforms multiple times during the close process so that close data could be fully consolidated and made available for reporting. This process had numerous challenges and inefficiencies that Centene wished to improve upon so that they could provide a more streamlined and more transparent process to the functional teams that leverage consolidated financials in their systems for reporting and analysis.
Centene chose OneStream XF for global and US consolidations, currency conversion, eliminations, and ownership percentage.
Michael Vannoni, director, financial systems solutions discussed the migration to OneStream XF including:
-Factors leading to the selection of OneStream XF
-Details of the solution design
-Benefits realized with global consolidation implementation
-Future planned enhancements
WHODrug Koda, developed by Uppsala Monitoring Centre (UMC), is an automated coding service, which uses artificial intelligence (AI) to automate the coding of drug names and ATC selections, improving consistency and operational efficiency. It can also be used to accelerate dictionary upgrades, including the transition from WHODrug B2 format to B3.
Through API (Application Programming Interface) web services, the coding engine can be integrated with custom or off-the-shelf drug safety, medical coding, or data management systems.
In this webinar, Perficient and UMC discussed WHODrug Koda and how you can integrate it into your medical coding activities.
Preparing for Your Oracle, Medidata, and Veeva CTMS Migration ProjectPerficient, Inc.
There are multiple reasons why companies migrate to a new clinical trial management system (CTMS). Still, the two most common are mergers and acquisitions (i.e., CTMS consolidation) and the desire to switch CTMS vendors. Regardless of the reason, many of the best practices, processes, and tools are the same.
In this webinar, we looked at the migration approaches taken across several case studies. You’ll come away with an understanding of:
Pros and cons of each CTMS migration method
Types of migration tools, including APIs, ETL tools, and adapters
Approximate timelines and costs associated with each migration method
The topics discussed in this webinar can be applied to any CTMS migration project, whether you’re moving to or from Oracle’s Siebel CTMS, Medidata’s Rave CTMS, and Veeva’s Vault CTMS.
Accelerating Partner Management: How Manufacturers Can Navigate Covid-19Perficient, Inc.
The pandemic has ushered in a new normal for manufacturers, and the impact of digital communication is more important than ever.
View our on-demand webinar with Tony Kratovil, Regional Vice President of Manufacturing at Salesforce, and Eric Dukart, National Sales Executive at Perficient. They covered why the right digital strategies are critical for manufacturers in the wake of COVID-19.
Our webinar covered:
Current challenges with forecasting, collaboration, and disruptions to distribution networks.
Insights for stabilizing operations, accelerating partner management, and developing a digital strategy that differentiates your business.
Candid Q&A with real-world examples.
New Work.com resources to help manufacturers restart safely and rebuild.
Tools and resources to move forward – fast.
The Critical Role of Audience Intelligence with Eric Enge and Rand FishkinPerficient, Inc.
Things move quickly in marketing. How do you identify what your customers need and how you can help? Now more than ever, audience intelligence is the key.
Audience intelligence is about understanding your target customers, their needs, what resonates with them, and how you can reach them. Eric Enge (Digital Marketing Principal, Perficient) and Rand Fishkin (Co-Founder & CEO, SparkToro) discussed this topic live on May 7, 2020. Watch to hear tactics for gaining a better understanding of your customers, how to use audience intelligence to optimize your marketing now, and more.
Cardtronics, the global leader in ATM deployment and management, decided to retire its on-premises Hyperion solution to gain the operational efficiencies, features, and functionality provided by a best-in-class cloud solution.
Cardtronics chose Oracle EPM Cloud including Financial Consolidation and Close, Planning, Management Reporting, Account Reconciliation, Enterprise Data Management, as well as Oracle Analytics Cloud.
In this video, project owner Richard Ng, director, financial systems, Cardtronics, discusses the migration to Oracle EPM Cloud including:
Multi-release 18-month deployment schedule across multiple countries
Benefits of a global Chart of Accounts for ERP and EPM
Seamless integration across ERP Cloud, HCM Cloud, and EPM Cloud
Preparing for Project Cortex and the Future of Knowledge ManagementPerficient, Inc.
Microsoft has turned traditional enterprise content management on its head with its recent announcement of Project Cortex.
Project Cortex uses advanced artificial intelligence to harness collective knowledge from across the enterprise and automatically organize it into shared topics like projects, products, processes, and customers. Using AI, Cortex creates a knowledge network based on relationships among topics, content, and people and delivers it in the apps you use every day – Office, Outlook, and Teams.
This webinar examined Project Cortex in more detail, including:
• What is Project Cortex?
• Why is Project Cortex different than other knowledge network projects previously introduced?
• How does incorporating AI and automation change the game?
• What is possible with Project Cortex?
• What can you do to prepare?
Utilizing Microsoft 365 Security for Remote Work Perficient, Inc.
With an increasingly mobile workforce, and the spread of shadow IT, the rapid rise of cybercrime - companies must find unique ways to effectively manage their sprawling SaaS portfolio.
2. About Perficient
Perficient is a leading information technology consulting firm serving clients
throughout North America.
We help clients implement business-driven technology solutions that integrate
business processes, improve worker productivity, increase customer loyalty and create
a more agile enterprise to better respond to new business opportunities.
3. What We Bring to Our Clients
Industry-leading solution & Collaborative Approach
technology expertise • Work with our clients, adapting to
• ~2000 experienced colleagues their cultures
• Dedicated solution practices • Education and mentoring services
• Partnerships and certifications in
premier technologies Superior Service and Value
• Local client service teams
Disciplined project execution • Flexible resource and fee
• Highly experienced project managers arrangements
• Perficient’s Enable™ methodology • Delivery track record
based on best practices
Commitment and Quality
Innovative approaches and IP Assurance
• Perficient’s user-centered design • Track record of 2000 engagements
approach with 800+ clients
• Application migration methodology • ~85% of clients bring us back
• Quick Start Rulebook™ for Enterprise • Strong client references
Integration
4. Our Solutions Expertise
Business Solutions Technology Solutions
• Business Intelligence • Business Integration/SOA
• Business Process Management • Cloud Services
• Customer Experience and CRM • Commerce
• Enterprise Performance Management • Content Management
• Enterprise Resource Planning • Custom Application Development
• Experience Design (XD) • Education
• Management Consulting • Information Management
• Mobile Platforms
• Platform Integration
• Portal & Social
6. Our Speakers
Mike Panzarella, Director, Financial Services Practice
With 20 years of experience with Big Four consulting and
commercial banking, Mike has expertise in BI/DW platform
architectures for Fortune 100 financial service firms with a focus on
social media and mobile convergence. Mike also has extensive
experience in designing and implementing Big Data solutions for
Fortune 100 companies.
Ben Leeson, Data Governance Architect
Ben has over 10 years of Governance and IT leadership experience
with Fortune 50 Financial Services companies. Ben’s areas of focus
are in Data Governance, Data Stewardship, Data Quality, Data
Sourcing and Data Strategy. He has experience driving enterprise
level data management programs that span each line of business
and corporate banking functions.
7. What We Will Cover
2013
About Us Defining MDM Tr e n d s
Challenges Data Governance
Leverage IT
U n l o c k i n g B u s i n en v e Vamu e t s
I ss st l en Q & A
9. What is Master Data Management?
Master Data Management (MDM)
comprises of a set of
processes, governance, policies, standar
ds and tools that consistently defines
and manages the master data of an
organization.
10. What is Master Data Management?
• Disciplines, technologies, and processes that accommodate, control
and manage master data across the organization
• A means to manage and deliver a unified view of an organization’s data
SOURCE SYSTEMS MASTER DATA ENTERPRISE
MANAGEMENT APPLICATIONS
CRM
Name: B. Jones INFORMATION
Address: 35 West 15th Street Sales
Address: Toledo, OH 12345 First: Bill
Last: Jones
ERP
Name: William Jones Address: 35 West 15th Street
Address: 35 West 15th St. Customer
City: Toledo
Address: Toledo, OH 12345 Support
State/Zip: OH / 12345
Legacy
Gender: M
Name: Billie Jones
Address: 36 West 15th St. Age: 30 Claims
Address: Toledo, OH 12345
DOB: 1/1/81
Master Data Management Needs Governance to Succeed
10
11. MDM Business Drivers
Strategic Initiative
•Consolidate data from silos/integrate new systems quickly
•Meet demands of new business channels
•Grow with the business
•Identify key relationships and hierarchies
Revenue
•Identify cross-sell, up-sell opportunities
•Customize product offerings and bundles
•Introduce new products quickly
•Identify high-value customers
•Improve customer retention
Cost
•Automate manual business processes
•Reduce data errors
•Eliminate excess mailings
•Identify credit risk
•Support system consolidation initiatives
Compliance
•Automate manual business processes
•Reduce data errors
•Eliminate excess mailings
•Identify risk (credit)
•Support system consolidation initiatives
11
13. Trend: Gartner‟s Nexus of Forces
The Nexus of Forces (mobility, social networks, information and cloud services) is accelerating
the pace and granularity of interconnected markets at a faster rate than ever.
Banks
Employees
and Customers
Social Corporate
Networks Data
Email, IM Retail and
Banking
End Transactions
Customers
Applications
Retail Stores
Source: Gartner (Jan. 2013) 13
14. Trend: Embracing Social
What is “Social MDM”?
• Increased social awareness in banking
• Need for social collaboration
• Evolution of CRM system and use of sensor data
• New systems of engagement = more data silos
• Data quality is increasingly important
• Pending regulatory standards (FFIEC)
• Golden Record vs. Golden Profile
15. Trend: Digital Disruption
• Investment in mobile innovations
• Create a seamless customer
cross-channel experience
• Validating data Geolocation data
• Data quality known issue
• Manage privacy issues
• Compliance
“GoBank” mobile account
from Green Dot
15
16. Trend: The Big Data Ecosystem
• Better processing and management of
Big Data
• Enhanced metadata and social
analytic preprocessing
16
17. Trend: MDM in the Cloud
• Proliferation of cloud based
solutions
• New entrants into marketplace
• Value-added services and solutions
for “social listening”
• Commoditization of data
• Data is data is data
• Cost of pulling data in
• Regulatory compliance standards
17
19. MDM Challenges
• Sponsorship at the enterprise level
• Data hoarding & mistrust of data centralization
• Addition of business process alignment
• Continued customer data integration
• Introduction of external/new data sources
• SOA and SLO compliance
• Scalability of architecture
21. MDM Questions to Ask
• What is the Data Strategy?
Strategy • How does it support the business strategy?
• How is data utilized in the fulfillment of business processes?
• Does poor data quality impact the company functions?
Quality • Is data cleansing simply assumed as part of doing business?
• How can data better serve the business? (i.e. Analytics, Operations)
Value
• Does the company have the skills to fulfill the data strategy?
Resources
• Who is pushing funding for the data solution(s)?
Funding
• What is the current and future architecture of the company?
Arch.
21
22. What is Enterprise Data?
Types of Enterprise Data
Entity Data
Master Data is a subset
(Something exists)
Transactional Data Analytical Data
(Something happened) (data for enabling future action)
22
23. What is Enterprise Data?
Another View
Govern the Data
Contribute
Data Data Master Enable Deliver Data
Providers Quality Data Sharing Consumers
Update
Enrich
23
24. Audiences for MDM
MDM, especially the customer domain, requires business input.
It’s important to know your audience when implementing a MDM solution.
The terms may change but the concepts are similar.
Business Perspective: Technology Perspective:
data flow, data supply data lineage, metadata, system
chain, data producer, data of record, source system, and
supplier, and business process integration
Data Environment Master Data Data Consumers
Management
Support
Ops
Sales
24
25. Impacts of Changes to Data
Data Data profiling & data
Originator cleansing – now a hop
Q
(Upstream) or more removed from
the source: telephone
game
Data
Provider
B
Transformations to fit the
schema of the new
system: e.g. changing the Data
format of date Consumer
H (Downstream)
Data lineage management enables systems to account for the downstream
impacts of a change to the data.
The change can appear to be relatively benign like cleaning up data, to the more
intentional like changing the context of a business element.
If Data Provider B changes the format of a data element the downstream systems
need to be aware of the change and adjust their code to account for it. Data Provider B
is responsible for communicating to their Data Consumers the changes.
25
26. Data Governance Focus Areas
Identify Associated Business Processes
Develop the Analyst Community: Who are they? What are their Requirements?
People & Process
Share ideas, best practices, common resources, communication channels
Standardize the Common Business Language: Project Delivery Process:
Business glossary, information domains, conceptual data Gather data requirements early in the
models process
Stand up a Governance Structure:
Executive Support and SME Participation
Create & maintain routines, policies, standards, review processes (exceptions), and communications
Define Data Governance Roles and Responsibilities:
Data management executive, data stewards, data custodians, information architects, analysts, SAs, and more
Establish Master Data and Data Provisioning Management:
Determine authoritative data sources are and the process for attaining data from them
Technology
Data Metadata Data Quality
Integration/Movement Management Management
Technical & Data Quality
Operational Standards &
Metadata Measures
Data management tools are unified and the platform is maximized 26
27. Data Governance Primary Roles
To weave sustainable data governance into the fabric of the
company, executive level participation must occur in the administrative
component
Data Governance Administrator Data Steward Data Custodian
(Formal Oversight) (Business Requirements) (Technical Requirements)
Direction Business Strategy Data Integration
Scope Business Terms Objective Data Quality
Prioritization Data Standards Data Modeling
Governance Structure Business Rules Metadata Management
Organizational Alignment Business Process Data Lineage
Policy Definition Subjective Data Quality Work Flow Management
Issue Resolution Data Analytics Data Security
Roles and Responsibilities Identify Opportunities
Authority and Accountability Identify Risk
Funding
Education
Communication
Enable Data Management Manage the Data
27
33. Come See Us at Bank Innovation!
Perficient.com/BankInnovation
33
34. Connect with Perficient
SUBSCRIBE TO PERFICIENT BLOGS ONLINE
Blogs.Perficient.com/ FinancialServices
FOLLOW PERFICIENT ON TWITTER
Perficient_FS
BECOME A FAN OF PERFICIENT ON FACEBOOK
w w w. F aceb o o k. co m/ Perfi ci en t
D O W N L O AD P E R F I C I E N T W H I T E PAP E R S
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Editor's Notes
As a technology and management consulting company, Perficient is uniquely positioned to provide an enhanced project and implementation experience for our financial services clients through our solid partner relationships with IBM, Microsoft, Oracle and Tibco. We provide both functional and technical expertise, in addition to the skillset to assist with onboarding new IM solutions, review data stewardship processes, guide clients with data cleanup and implement custom integration solutions across the business.
By 2014, 66 percent of Fortune 1000 organizations will have deployed two or more MDM solutions to support their enterprise MDM strategies.
In a recent study conducted by Ovum, they reveal retail banking IT spend to hit $118.6bn in 2013. As part of this business trends report, they are reporting that the online, mobile and digital marketing for banks will continue to be a top priority. Forecasts show mobile banking will increase 6.7% in North America. In 2013, retail banks will attempt to capitalize on new mobile capabilities in payments and location-based services. To manage all of these priorities, MDM will be critical and central to all of these IT projects.
As an example, capitalizing on consumer needs and use of the Nexus of Forces provides clustered revenue generation and differentiated client engagement for banks and retailers.
Social networks have emerged as a vast repository of conversation and information that can be used in conjunction with an organization’sinternal master data to greatly improve business analytics, customer service and operational efficiencies.MDM can help match data acquired from social media and identify it with a customer profile that already exists within the enterprise.
Example reference data
Machine generated and sensor data – related to person (Ben info)Algorithms and framework – Big Data in the sense of “decision profile” w/devices you interact withComplex events processing – what does that mean from
Data-centric marketing for customer intelligence projectsMulti-channel customer engagementGolden Record vs. Golden Profile – advent of social media and unstructured dataBI DemocracyTrying to understand their customer – pre-transaction through post-transactionWealth management example – universal risk profile for investors