Synopsis:
[Video link: http://www.youtube.com/watch?v=ZNrTxSU5IQ0 ]
Jim Stagnitto and John DiPietro of consulting firm a2c) will discuss Agile Data Warehouse Design - a step-by-step method for data warehousing / business intelligence (DW/BI) professionals to better collect and translate business intelligence requirements into successful dimensional data warehouse designs.
The method utilizes BEAM✲ (Business Event Analysis and Modeling) - an agile approach to dimensional data modeling that can be used throughout analysis and design to improve productivity and communication between DW designers and BI stakeholders. BEAM✲ builds upon the body of mature "best practice" dimensional DW design techniques, and collects "just enough" non-technical business process information from BI stakeholders to allow the modeler to slot their business needs directly and simply into proven DW design patterns.
BEAM✲ encourages DW/BI designers to move away from the keyboard and their entity relationship modeling tools and begin "white board" modeling interactively with BI stakeholders. With the right guidance, BI stakeholders can and should model their own BI data requirements, so that they can fully understand and govern what they will be able to report on and analyze.
The BEAM✲ method is fully described in
Agile Data Warehouse Design - a text co-written by Lawrence Corr and Jim Stagnitto.
About the speaker:
Jim Stagnitto Director of a2c Data Services Practice
Data Warehouse Architect: specializing in powerful designs that extract the maximum business benefit from Intelligence and Insight investments.
Master Data Management (MDM) and Customer Data Integration (CDI) strategist and architect.
Data Warehousing, Data Quality, and Data Integration thought-leader: co-author with Lawrence Corr of "Agile Data Warehouse Design", guest author of Ralph Kimball’s “Data Warehouse Designer” column, and contributing author to Ralph and Joe Caserta's latest book: “The DW ETL Toolkit”.
John DiPietro Chief Technology Officer at A2C IT Consulting
John DiPietro is the Chief Technology Officer for a2c. Mr. DiPietro is responsible
for setting the vision, strategy, delivery, and methodologies for a2c’s Solution
Practice Offerings for all national accounts. The a2c CTO brings with him an
expansive depth and breadth of specialized skills in his field.
Sponsor Note:
Thanks to:
Microsoft NERD for providing awesome venue for the event.
http://A2C.com IT Consulting for providing the food/drinks.
http://Cognizeus.com for providing book to give away as raffle.
According to Gartner, “By 2018, organizations with data virtualization capabilities will spend 40% less on building and managing data integration processes for connecting distributed data assets.” This solidifies Data Virtualization as a critical piece of technology for any flexible and agile modern data architecture.
This session will:
• Introduce data virtualization and explain how it differs from traditional data integration approaches
• Discuss key patterns and use cases of Data Virtualization
• Set the scene for subsequent sessions in the Packed Lunch Webinar Series, which will take a deeper dive into various challenges solved by data virtualization.
Agenda:
• Introduction & benefits of DV
• Summary & Next Steps
• Q&A
Watch full webinar here: https://goo.gl/EFQNFs
This webinar is part of the Data Virtualization Packed Lunch Webinar Series: https://goo.gl/W1BeCb
Business Intelligence & Data Analytics– An Architected ApproachDATAVERSITY
Business intelligence (BI) and data analytics are increasing in popularity as more organizations are looking to become more data-driven. Many tools have powerful visualization techniques that can create dynamic displays of critical information. To ensure that the data displayed on these visualizations is accurate and timely, a strong Data Architecture is needed. Join this webinar to understand how to create a robust Data Architecture for BI and data analytics that takes both business and technology needs into consideration.
Modern Data Warehousing with the Microsoft Analytics Platform SystemJames Serra
The traditional data warehouse has served us well for many years, but new trends are causing it to break in four different ways: data growth, fast query expectations from users, non-relational/unstructured data, and cloud-born data. How can you prevent this from happening? Enter the modern data warehouse, which is able to handle and excel with these new trends. It handles all types of data (Hadoop), provides a way to easily interface with all these types of data (PolyBase), and can handle “big data” and provide fast queries. Is there one appliance that can support this modern data warehouse? Yes! It is the Analytics Platform System (APS) from Microsoft (formally called Parallel Data Warehouse or PDW) , which is a Massively Parallel Processing (MPP) appliance that has been recently updated (v2 AU1). In this session I will dig into the details of the modern data warehouse and APS. I will give an overview of the APS hardware and software architecture, identify what makes APS different, and demonstrate the increased performance. In addition I will discuss how Hadoop, HDInsight, and PolyBase fit into this new modern data warehouse.
Data Catalog for Better Data Discovery and GovernanceDenodo
Watch full webinar here: https://buff.ly/2Vq9FR0
Data catalogs are en vogue answering critical data governance questions like “Where all does my data reside?” “What other entities are associated with my data?” “What are the definitions of the data fields?” and “Who accesses the data?” Data catalogs maintain the necessary business metadata to answer these questions and many more. But that’s not enough. For it to be useful, data catalogs need to deliver these answers to the business users right within the applications they use.
In this session, you will learn:
*How data catalogs enable enterprise-wide data governance regimes
*What key capability requirements should you expect in data catalogs
*How data virtualization combines dynamic data catalogs with delivery
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.
Data Architecture is foundational to an information-based operational environment. Without proper structure and efficiency in organization, data assets cannot be utilized to their full potential, which in turn harms bottom-line business value. When designed well and used effectively, however, a strong Data Architecture can be referenced to inform, clarify, understand, and resolve aspects of a variety of business problems commonly encountered in organizations.
The goal of this webinar is not to instruct you in being an outright Data Architect, but rather to enable you to envision a number of uses for Data Architectures that will maximize your organization’s competitive advantage. With that being said, we will:
Discuss Data Architecture’s guiding principles and best practices
Demonstrate how to utilize Data Architecture to address a broad variety of organizational challenges and support your overall business strategy
Illustrate how best to understand foundational Data Architecture concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
According to Gartner, “By 2018, organizations with data virtualization capabilities will spend 40% less on building and managing data integration processes for connecting distributed data assets.” This solidifies Data Virtualization as a critical piece of technology for any flexible and agile modern data architecture.
This session will:
• Introduce data virtualization and explain how it differs from traditional data integration approaches
• Discuss key patterns and use cases of Data Virtualization
• Set the scene for subsequent sessions in the Packed Lunch Webinar Series, which will take a deeper dive into various challenges solved by data virtualization.
Agenda:
• Introduction & benefits of DV
• Summary & Next Steps
• Q&A
Watch full webinar here: https://goo.gl/EFQNFs
This webinar is part of the Data Virtualization Packed Lunch Webinar Series: https://goo.gl/W1BeCb
Business Intelligence & Data Analytics– An Architected ApproachDATAVERSITY
Business intelligence (BI) and data analytics are increasing in popularity as more organizations are looking to become more data-driven. Many tools have powerful visualization techniques that can create dynamic displays of critical information. To ensure that the data displayed on these visualizations is accurate and timely, a strong Data Architecture is needed. Join this webinar to understand how to create a robust Data Architecture for BI and data analytics that takes both business and technology needs into consideration.
Modern Data Warehousing with the Microsoft Analytics Platform SystemJames Serra
The traditional data warehouse has served us well for many years, but new trends are causing it to break in four different ways: data growth, fast query expectations from users, non-relational/unstructured data, and cloud-born data. How can you prevent this from happening? Enter the modern data warehouse, which is able to handle and excel with these new trends. It handles all types of data (Hadoop), provides a way to easily interface with all these types of data (PolyBase), and can handle “big data” and provide fast queries. Is there one appliance that can support this modern data warehouse? Yes! It is the Analytics Platform System (APS) from Microsoft (formally called Parallel Data Warehouse or PDW) , which is a Massively Parallel Processing (MPP) appliance that has been recently updated (v2 AU1). In this session I will dig into the details of the modern data warehouse and APS. I will give an overview of the APS hardware and software architecture, identify what makes APS different, and demonstrate the increased performance. In addition I will discuss how Hadoop, HDInsight, and PolyBase fit into this new modern data warehouse.
Data Catalog for Better Data Discovery and GovernanceDenodo
Watch full webinar here: https://buff.ly/2Vq9FR0
Data catalogs are en vogue answering critical data governance questions like “Where all does my data reside?” “What other entities are associated with my data?” “What are the definitions of the data fields?” and “Who accesses the data?” Data catalogs maintain the necessary business metadata to answer these questions and many more. But that’s not enough. For it to be useful, data catalogs need to deliver these answers to the business users right within the applications they use.
In this session, you will learn:
*How data catalogs enable enterprise-wide data governance regimes
*What key capability requirements should you expect in data catalogs
*How data virtualization combines dynamic data catalogs with delivery
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.
Data Architecture is foundational to an information-based operational environment. Without proper structure and efficiency in organization, data assets cannot be utilized to their full potential, which in turn harms bottom-line business value. When designed well and used effectively, however, a strong Data Architecture can be referenced to inform, clarify, understand, and resolve aspects of a variety of business problems commonly encountered in organizations.
The goal of this webinar is not to instruct you in being an outright Data Architect, but rather to enable you to envision a number of uses for Data Architectures that will maximize your organization’s competitive advantage. With that being said, we will:
Discuss Data Architecture’s guiding principles and best practices
Demonstrate how to utilize Data Architecture to address a broad variety of organizational challenges and support your overall business strategy
Illustrate how best to understand foundational Data Architecture concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
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.
Linking Data Governance to Business GoalsPrecisely
The importance of data to businesses has increased exponentially over recent years as companies seek benefits such as gains in efficiency, the ability to respond to growing privacy regulations scale quickly and increased and increase customer loyalty.
Despite being a vital part of any Data Transformation, Data Governance has sometimes been misrepresented as a restrictive and controlling process leaving governance leaders having to continually make the case for business buy-in.
In this on-demand webinar we will explore the concept of business-first Data Governance, an approach that promotes adoption by the organisation, lays the foundation for data integrity and consistently delivers business value in the long term.
Microsoft Data Warehouse Business Intelligence Lifecycle - The Kimball ApproachMark Ginnebaugh
Data Warehouse - Business Intelligence Lifecycle Overview by Warren Thronthwaite
This slide deck describes the Kimball approach from the best-selling Data Warehouse Toolkit, 2nd Edition. It was presented to the Bay Area Microsoft Business Intelligence User Group in October 2012.
Starting with business requirements and project definition, the lifecycle branches out into three tracks: Technical, Data and Applications. You will learn:
* The major steps in the Lifecycle and what needs to happen in each one.
* Why business requirements are so important and how they influence all major decisions across the entire DW/BI system.
* Key tools for prioritizing business requirements and creating an enterprise information framework.
* How to break up a DW/BI system into doable increments that add real business value and can be completed in a reasonable time frame.
How to Take Advantage of an Enterprise Data Warehouse in the CloudDenodo
Watch full webinar here: [https://buff.ly/2CIOtys]
As organizations collect increasing amounts of diverse data, integrating that data for analytics becomes more difficult. Technology that scales poorly and fails to support semi-structured data fails to meet the ever-increasing demands of today’s enterprise. In short, companies everywhere can’t consolidate their data into a single location for analytics.
In this Denodo DataFest 2018 session we’ll cover:
Bypassing the mandate of a single enterprise data warehouse
Modern data sharing to easily connect different data types located in multiple repositories for deeper analytics
How cloud data warehouses can scale both storage and compute, independently and elastically, to meet variable workloads
Presentation by Harsha Kapre, Snowflake
Embarking on building a modern data warehouse in the cloud can be an overwhelming experience due to the sheer number of products that can be used, especially when the use cases for many products overlap others. In this talk I will cover the use cases of many of the Microsoft products that you can use when building a modern data warehouse, broken down into four areas: ingest, store, prep, and model & serve. It’s a complicated story that I will try to simplify, giving blunt opinions of when to use what products and the pros/cons of each.
Describes what Enterprise Data Architecture in a Software Development Organization should cover and does that by listing over 200 data architecture related deliverables an Enterprise Data Architect should remember to evangelize.
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
You Need a Data Catalog. Do You Know Why?Precisely
The data catalog has become a popular discussion topic within data management and data governance circles. A data catalog is a central repository that contains metadata for describing data sets, how they are defined, and where to find them. TDWI research indicates that implementing a data catalog is a top priority among organizations we survey. The data catalog can also play an important part in the governance process. It provides features that help ensure data quality, compliance, and that trusted data is used for analysis. Without an in-depth knowledge of data and associated metadata, organizations cannot truly safeguard and govern their data.
Join this on-demand webinar to learn more about the data catalog and its role in data governance efforts.
Topics include:
· Data management challenges and priorities
· The modern data catalog – what it is and why it is important
· The role of the modern data catalog in your data quality and governance programs
· The kinds of information that should be in your data catalog and why
Business Intelligence PowerPoint Presentation Slides SlideTeam
Presenting this set of slides with name - Business Intelligence Powerpoint Presentation Slides. All slides are completely editable and professionally designed by our team of expert PowerPoint designers. The presentation content covers all areas of Business Intelligence Powerpoint Presentation Slides and is extensively researched. This ready-to-use deck comprises visually stunning PowerPoint templates, icons, visual designs, data-driven charts and graphs and business diagrams. The deck consists of a total of thirtynine slides. You can customize this presentation as per your branding needs. You can change the font size, font type, colors as per your requirement. Download the presentation, enter your content in the placeholders and present with confidence.
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
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.
Download at http://DavidHubbard.net/powerpoint - This Introduction to Business Intelligence gives an overview of how Business Intelligence fits into business strategy in general. It does not go into the specific technologies of Business Intelligence. It is meant to be used to explain Business Intelligence to those not already familiar with Business Intelligence.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
Using a Semantic and Graph-based Data Catalog in a Modern Data FabricCambridge Semantics
Watch this webinar to learn about the benefits of using semantic and graph database technology to create a Data Catalog of all of an enterprise's data, regardless of source or format, as part of a modern IT or data management stack and an important step toward building an Enterprise Data Fabric.
DAS Slides: Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key inter-relationships 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.
Aeromexico and Adyen - Transformation of E-Commerce PaymentsBrian Gross
Aeromexico implemented the Adyen payments gateway, leading to revolutionary improvements in both acceptance rates and the customer experience. Presented at Airline & Travel Payments Summit (ATPS), Berlin, May 2017
Product Brochure: Adyen Company Profile 2015: Online Payment ServicesyStats.com
Product Brochure with summarized information of our publication "Adyen Company Profile 2015: Online Payment Services".
Find more here: https://www.ystats.com/product/adyen-company-profile-2015-online-payment-services/
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.
Linking Data Governance to Business GoalsPrecisely
The importance of data to businesses has increased exponentially over recent years as companies seek benefits such as gains in efficiency, the ability to respond to growing privacy regulations scale quickly and increased and increase customer loyalty.
Despite being a vital part of any Data Transformation, Data Governance has sometimes been misrepresented as a restrictive and controlling process leaving governance leaders having to continually make the case for business buy-in.
In this on-demand webinar we will explore the concept of business-first Data Governance, an approach that promotes adoption by the organisation, lays the foundation for data integrity and consistently delivers business value in the long term.
Microsoft Data Warehouse Business Intelligence Lifecycle - The Kimball ApproachMark Ginnebaugh
Data Warehouse - Business Intelligence Lifecycle Overview by Warren Thronthwaite
This slide deck describes the Kimball approach from the best-selling Data Warehouse Toolkit, 2nd Edition. It was presented to the Bay Area Microsoft Business Intelligence User Group in October 2012.
Starting with business requirements and project definition, the lifecycle branches out into three tracks: Technical, Data and Applications. You will learn:
* The major steps in the Lifecycle and what needs to happen in each one.
* Why business requirements are so important and how they influence all major decisions across the entire DW/BI system.
* Key tools for prioritizing business requirements and creating an enterprise information framework.
* How to break up a DW/BI system into doable increments that add real business value and can be completed in a reasonable time frame.
How to Take Advantage of an Enterprise Data Warehouse in the CloudDenodo
Watch full webinar here: [https://buff.ly/2CIOtys]
As organizations collect increasing amounts of diverse data, integrating that data for analytics becomes more difficult. Technology that scales poorly and fails to support semi-structured data fails to meet the ever-increasing demands of today’s enterprise. In short, companies everywhere can’t consolidate their data into a single location for analytics.
In this Denodo DataFest 2018 session we’ll cover:
Bypassing the mandate of a single enterprise data warehouse
Modern data sharing to easily connect different data types located in multiple repositories for deeper analytics
How cloud data warehouses can scale both storage and compute, independently and elastically, to meet variable workloads
Presentation by Harsha Kapre, Snowflake
Embarking on building a modern data warehouse in the cloud can be an overwhelming experience due to the sheer number of products that can be used, especially when the use cases for many products overlap others. In this talk I will cover the use cases of many of the Microsoft products that you can use when building a modern data warehouse, broken down into four areas: ingest, store, prep, and model & serve. It’s a complicated story that I will try to simplify, giving blunt opinions of when to use what products and the pros/cons of each.
Describes what Enterprise Data Architecture in a Software Development Organization should cover and does that by listing over 200 data architecture related deliverables an Enterprise Data Architect should remember to evangelize.
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
You Need a Data Catalog. Do You Know Why?Precisely
The data catalog has become a popular discussion topic within data management and data governance circles. A data catalog is a central repository that contains metadata for describing data sets, how they are defined, and where to find them. TDWI research indicates that implementing a data catalog is a top priority among organizations we survey. The data catalog can also play an important part in the governance process. It provides features that help ensure data quality, compliance, and that trusted data is used for analysis. Without an in-depth knowledge of data and associated metadata, organizations cannot truly safeguard and govern their data.
Join this on-demand webinar to learn more about the data catalog and its role in data governance efforts.
Topics include:
· Data management challenges and priorities
· The modern data catalog – what it is and why it is important
· The role of the modern data catalog in your data quality and governance programs
· The kinds of information that should be in your data catalog and why
Business Intelligence PowerPoint Presentation Slides SlideTeam
Presenting this set of slides with name - Business Intelligence Powerpoint Presentation Slides. All slides are completely editable and professionally designed by our team of expert PowerPoint designers. The presentation content covers all areas of Business Intelligence Powerpoint Presentation Slides and is extensively researched. This ready-to-use deck comprises visually stunning PowerPoint templates, icons, visual designs, data-driven charts and graphs and business diagrams. The deck consists of a total of thirtynine slides. You can customize this presentation as per your branding needs. You can change the font size, font type, colors as per your requirement. Download the presentation, enter your content in the placeholders and present with confidence.
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
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.
Download at http://DavidHubbard.net/powerpoint - This Introduction to Business Intelligence gives an overview of how Business Intelligence fits into business strategy in general. It does not go into the specific technologies of Business Intelligence. It is meant to be used to explain Business Intelligence to those not already familiar with Business Intelligence.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
Using a Semantic and Graph-based Data Catalog in a Modern Data FabricCambridge Semantics
Watch this webinar to learn about the benefits of using semantic and graph database technology to create a Data Catalog of all of an enterprise's data, regardless of source or format, as part of a modern IT or data management stack and an important step toward building an Enterprise Data Fabric.
DAS Slides: Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key inter-relationships 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.
Aeromexico and Adyen - Transformation of E-Commerce PaymentsBrian Gross
Aeromexico implemented the Adyen payments gateway, leading to revolutionary improvements in both acceptance rates and the customer experience. Presented at Airline & Travel Payments Summit (ATPS), Berlin, May 2017
Product Brochure: Adyen Company Profile 2015: Online Payment ServicesyStats.com
Product Brochure with summarized information of our publication "Adyen Company Profile 2015: Online Payment Services".
Find more here: https://www.ystats.com/product/adyen-company-profile-2015-online-payment-services/
A Partnership with Adyen is Equal to Exponential Growth: 17 Payments Experts ...Marcos Ortiz Valmaseda
Do you want the little secret that allows to global organizations like Uber, Spotify, Facebook, Netflix, Yelp, Dropbox, Hillarys, Evernote, SurveyMonkey and many more hack its growth globally? The "secret" has a name: Adyen. 17 Payments Experts shared what they thought about Adyen and how it has been critical to these organizations to scale globally in the fastest possible way.
Improving the customer experience using big data customer-centric measurement...Vishal Kumar
This presentation provides an overview of some of the content of my new book, TCE: Total Customer Experience. In the presentation, I discuss customer experience management, customer loyalty, the optimal customer survey, the value of analytics and using a Big Data customer-centric approach to improve the value of all your business data.
For More, please visit http://www.tcelab.com
Big Data has Big Implications for Customer Experience ManagementVishal Kumar
This presentation covers the application of Big Data principles in Customer Experience Management. I present data models to help companies integrate, organize and analyze their disparate data sources (e.g., operational, financial, constituency and customer feedback) to improve the customer experience and customer loyalty.
For More, please visit http://www.tcelab.com
How an omni-channel approach to payments brings huge benefits to retailers and how it fits in with the overall omni-channel trend - Workshop by Christoph von Bülow, Country Manager Adyen Germany at the NOAH 2015 Conference in Berlin, Tempodrom on the 9th of June 2015.
Sample Report: Adyen Company Profile 2015: Online Payment ServicesyStats.com
Free Report Samples for our publication "Adyen Company Profile 2015: Online Payment Services".
Find the full report available for purchase at: https://www.ystats.com/product/adyen-company-profile-2015-online-payment-services/
Customer Experience Management for StartupsVishal Kumar
Dr. Bob E Hayes: I was invited to give a talk at Eastside Incubator on how startups can incorporate customer experience management into their companies. These are the slides. You can read my blog post on this topic (http://businessoverbroadway.com/three-customer-experience-management-tips-for-startups) that are a good complement to these slides.
For More, please visit http://www.tcelab.com
Synopsis:
D3.js is a Javascript library primarily used to create interactive data visualizations in the browser. Despite its growing popularity and warm community, getting started with D3 can be tricky. This talk covers the basics of D3 and sheds light on some of its main conceptual hurdles. It concludes by discussing some applications of D3 to big data.
About the speaker:
Sam Selikoff [ http://www.samselikoff.com/ | @samselikoff ] is a self-taught full-stack web developer. Formerly a graduate student of economics and finance, he unexpectedly discovered a passion for programming while doing data work for a consulting firm. He is currently focusing on client-side MVC and data visualization.
Thanks to our Sponsors
Microsoft [ http://microsoftnewengland.com ] for providing awesome venue for the event.
Rovi [ http://rovi.com ] for providing the food/drinks.
cognizeus [ http://cognizeus.com ] for hosting the event and providing books to give away as raffle.
Dropbox: Building Business Through Lean Startup PrinciplesVishal Kumar
A Deck by Drew Houston from Dropbox explaining how Dropbox incorporated Lean Startup Principles in building their company. A great primer on how dropbox executed their startup.
The Best Startup Investor Pitch Deck & How to Present to Angels & Venture Cap...J. Skyler Fernandes
Take the online video course on Udemy:
https://www.udemy.com/course/the-best-startup-investor-pitch-deck/?referralCode=A5ED0FBD65120A93A16E
3.5+hrs of video content, walking step by step each part of the pitch, with personal VC stories, examples, and advice.
The "Best" Startup Investor Pitch Deck is an aggregation of some of the best pitch decks and wisdom from some of the top angels, VCs, and entrepreneurs including my own person insight/experience. The slide deck includes a template for entrepreneurs to use to present to investors, with details on what should be addressed on each slide. There are also additional slides on how best to pitch to investors effectively, how to design and format slides, and what to do before the pitch.
Here is what Square uses for their Pitch Deck, it has several good pointers on what should go in a startup pitch deck: Sourced from http://www.noise.re/duction/squares-pitch-deck/
When and How Data Lakes Fit into a Modern Data ArchitectureDATAVERSITY
Whether to take data ingestion cycles off the ETL tool and the data warehouse or to facilitate competitive Data Science and building algorithms in the organization, the data lake – a place for unmodeled and vast data – will be provisioned widely in 2020.
Though it doesn’t have to be complicated, the data lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the data swamp, but not the data lake! The tool ecosystem is building up around the data lake and soon many will have a robust lake and data warehouse. We will discuss policy to keep them straight, send data to its best platform, and keep users’ confidence up in their data platforms.
Data lakes will be built in cloud object storage. We’ll discuss the options there as well.
Get this data point for your data lake journey.
Building a 360 Degree View of Your Customers on BICSPerficient, Inc.
Why there is a need for Customer 360 and what the proposed cloud based solution is. We cover the stages of strategic marketing and how Oracle BI can help.
The Value of Customer Insights & Analytics in a Modern Retail EnvironmentDenodo
Watch full webinar here: https://bit.ly/3uj8g3m
As retail reacts to the current economic climate, the use of data and analytics becomes more and more important.
“Data is everywhere, but what does it mean?” This is a common question asked by C-level executives all the way down to retail staff in stores.
In this webinar, we will explore the role of a logical data fabric in unlocking the value of data and providing insights into the business.
Join this webinar to:
- Hear about how a logical data fabric helps retail organizations better know their end customer from a customer 360 degree point of view.
- How easy it is to integrate 3rd party data, for example, from the supply chain to make better informed business decisions.
- Where advanced AI/ML capabilities can be used by data scientists to help predict sales performance.
Slides from a recent Big Data Warehousing Meetup titled, Big Data Analytics with Microsoft.
See Power Pivot/ Power Query/ Power View/ Power Maps and Azure Machine Learning be used to analyze Big Data.
One challenge of dealing with Big Data project is to acquire both structured and instructed information in order to find the right correlation. During the event, we explained all the steps to build your model and enhance your existing data through Microsoft's Power BI.
We had an in-depth discussion about the innovations built into the latest stack of Microsoft Business Intelligence, and practical tips from Technology Specialist’s from Microsoft.
The session also featured demos to help you see the technology as an end-to-end solution.
For more information, visit www.casertaconcepts.com
Foundational Strategies for Trust in Big Data Part 1: Getting Data to the Pla...Precisely
Teams working on new business initiatives, whether for enhancing customer engagement, creating new value, or addressing compliance considerations, know that a successful strategy starts with the synchronization of operational and reporting data from across the organization into a centralized repository for use in advanced analytics and other projects. However, the range and complexity of data sources as well as the lack of specialized skills needed to extract data from critical legacy systems often causes inefficiencies and gaps in the data being used by the business.
The first part of our webcast series on Foundation Strategies for Trust in Big Data provides insight into how Syncsort Connect with its design once, deploy anywhere approach supports a repeatable pattern for data integration by enabling enterprise architects and developers to ensure data from ALL enterprise data sources– from mainframe to cloud – is available in the downstream data lakes for use in these key business initiatives.
Accelerate Self-Service Analytics with Data Virtualization and VisualizationDenodo
Watch full webinar here: https://bit.ly/3fpitC3
Enterprise organizations are shifting to self-service analytics as business users need real-time access to holistic and consistent views of data regardless of its location, source or type for arriving at critical decisions.
Data Virtualization and Data Visualization work together through a universal semantic layer. Learn how they enable self-service data discovery and improve performance of your reports and dashboards.
In this session, you will learn:
- Challenges faced by business users
- How data virtualization enables self-service analytics
- Use case and lessons from customer success
- Overview of the highlight features in Tableau
CRM-UG Summit Phoenix 2018 - What is Common Data Model and how to use it?Nicolas Georgeault
My Slidedeck about Common Data Service and Model from CRMUG SUmmit in Phoenix Oct 2018. This technology is under development so content is subject to change and based on current service on 10/18/2018
[AIIM] Getting Stuff Done with Content - Tony Peleska and Jordan JonesAIIM International
It’s no longer enough to manage all of the enterprise content you’re storing, you need to put it to work for you. Learn how Cisco Systems and the Minnesota Housing Finance Agency are “Getting Stuff Done” with their content.
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.
WebXpress Business Intelligence CapabilityWebXpress.IN
Business intelligence (BI) refers to skills, knowledge, technologies, applications and practices used to help a business to acquire a better understanding of the market behavior and business context. The purpose of business intelligence is to support better business decision making.
Turning Big Data into Better Business OutcomesCisco Canada
The big data era is upon us as organizations are awash in social, mobile and machine-generated data. Opportunity abounds. But competition threatens. Further this high volume, data-at-the-edge environment challenges centralized data warehouse approaches typical with BI and Analytics today. Data virtualization provides a more agile, leave-the-data-where-it-lies way to fulfill BI and Analytic needs and achieve key business outcomes.
Integrating Advanced Analytics with Autodesk SolutionsRich Hanapole
Learn how to integrate analytics software with Autodesk products to improve project visibility and communicate progress, issues and accomplishments to project stakeholders.
This class highlights proven approaches to design and integrate analytics into a project and demonstrates how stakeholders have the ability to view charts and trends including the ability to drill down into project data to identify challenge areas and apply corrective actions to improve the likelihood of a successful project outcome.
TRANSFORM DATA WITH INSIGHTFUL ANALYTICS - BUSINESS INTELLIGENCE SOLUTIONSTaction Software LLC
in today’s progressive business environment, it has become an absolute necessity to have insights into the data and accordingly analyze it in-depth to deliver sustainable performance. To hold a distinct competitive advantage, organizations must be willing to go-beyond the traditional way of capturing and using the data. Empowered business decisions require real-time data analytics and Trends for balancing business projections and actual deliveries. Taction’s Business Intelligence practice helps businesses to unlock the data value for faster decision-making, maximum accuracy and efficiency to accelerate innovation to get a competitive advantage.
Assessing New Databases– Translytical Use CasesDATAVERSITY
Organizations run their day-in-and-day-out businesses with transactional applications and databases. On the other hand, organizations glean insights and make critical decisions using analytical databases and business intelligence tools.
The transactional workloads are relegated to database engines designed and tuned for transactional high throughput. Meanwhile, the big data generated by all the transactions require analytics platforms to load, store, and analyze volumes of data at high speed, providing timely insights to businesses.
Thus, in conventional information architectures, this requires two different database architectures and platforms: online transactional processing (OLTP) platforms to handle transactional workloads and online analytical processing (OLAP) engines to perform analytics and reporting.
Today, a particular focus and interest of operational analytics includes streaming data ingest and analysis in real time. Some refer to operational analytics as hybrid transaction/analytical processing (HTAP), translytical, or hybrid operational analytic processing (HOAP). We’ll address if this model is a way to create efficiencies in our environments.
Seeing Redshift: How Amazon Changed Data Warehousing ForeverInside Analysis
The Briefing Room with Claudia Imhoff and Birst
Live Webcast April 9, 2013
What a difference a day can make! When Amazon announced their new RedShift offering – a data warehouse in the cloud – the entire industry of information management changed. The most notable disruption? Price. At a whopping $1,000 per year for a terabyte, RedShift achieved a price-point improvement that amounts to at least two orders of magnitude, if not three when compared to its top-tier competitors. But pricing is just one change; there's also the entire process by which data warehousing is done.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Claudia Imhoff explain why a new cloud-based reality for data warehousing significantly changes the game for business intelligence and analytics. She'll be briefed by Brad Peters of Birst who will tout his company's BI solution, which has been specifically architected for cloud-based hosting. Peters will discuss several key intricacies of doing BI in the cloud, including the unique provisioning, loading and modeling requirements. Founded in 2004, Birst has nearly a decade of doing cloud-based BI and Analytics.
Visit: http://www.insideanalysis.com
Here is a gift that keeps on giving in 2018 & beyond!Vishal Kumar
As 2017 comes to a close and we spend time with our loved ones during the holidays, I would like to use the opportunity to wish you a year filled with predictable collage of statistically significant achievements. Looking forward to a great 2018 with lots of moments to celebrate.
As a family we thought a lot about what would be a worthwhile 2017 goodbye and 2018 welcome gift. And, I remembered what we have experienced in 2017 including some magnificent books. We decided to create a calendar with the insights from our best of the best 2017 reads. Please accept the calendar that keeps on giving through 2018. Do share your thoughts and favorite reads to make our 2018 special. Page me @ vishal@tao.ai
Download it at: https://www.dropbox.com/s/yh9i60wdiaj3h3y/2018_calendar.pdf?dl=0
Share with anyone who could benefit.
Make money with big data by organizing your company around your customers. I presented this deck at the Cybera Big Data #cybersummit 2012 in Banff, Canada. In it, I talk about customer loyalty, how to use driver and linkage analysis to sort out both what's important to your customers and what will drive sustainable revenue for your business. Case studies include a SaaS software company, and U.S. Hospital patient experience data based on HCAHPS patient surveys from 4,610 health care facilities nationwide.
For More, please visit http://www.tcelab.com
Total Customer Experience Management Overview #TCE #CEM -- The Why, What and HowVishal Kumar
This is a CEM tutorial & TCELab introduction presentation we put together for our TCELab Sales Affiliates and Partners -- explains an overview of Total Customer Experience Management, Why your customer's CEO's will love it, your opportunity, and how TCELab's products and services fit into the CEM / Big Data / Customer Loyalty Space.
A must watch for CEM enthusiast or any business professionals interesting in reducing churn.
Find video at: http://www.youtube.com/watch?v=BFPDmM4Ct1E
Or read it in our corporate blog: http://tce.io/tutecast
Video itinerary:
0:00:07 What is Customer Experience Management (CEM)?
0:02:04 Why do CEO’s care?
0:04:15 Why CEM vendor should be excited?
0:07:15 What does CEM Program looks like?
0:07:45 Design of a CEM Program: CEM Program Components
0:11:20 Design of a CEM Program: Disparate Sources of Business Data
0:14:23 Design of a CEM Program: Data Linkage (connecting data to answer different question)
0:17:17 Design of a CEM Program: Integrating your business data (mapping organization silos with survey type)
0:20:58 Design of a CEM Program: Three ways to grow business… why just NPS is not enough?
0:25:40 TCELab product plug but some cross winds of CEM gold information
0:33:10 TCELab CLAAP Platform but some cross winds of CEM gold information
0:39:00 TCELab product execution process, time-lengths & other relevant information around it (information relevant to affiliate networks)
0:43:30 TCELab product lists (information relevant to affiliate networks)
0:52:40 TCELab case study: Kashoo + lot of good information for SAAS companies CEM program
For More, please visit http://www.tcelab.com
Global wireless network operator and mobile satisfaction / customer loyalty s...Vishal Kumar
This is the complete 26 page research paper from a global Network Operator Customer Loyalty study. The survey was fielded in Spring 2010, asking a sample of 5,000 people from 111 countries about their user experience with respect to their current network operator, mobile phones and mobile applications. Mob4Hire as well as Business Over Broadway (ne: TCELab) co-sponsored the survey results.
Table of Contents
==============
Methodology 2
Panel Description 2
Key Metrics Used in the Study 2
Executive Summary 3
Top Wireless Insights 3
Top Mobile Insights 3
Table of Contents 4
Figures 5
Operator Performance & Loyalty Grids 6
Network Operator Performance Grid 7
Network Operator Customer Loyalty Grid 8
Network Operator RAPID Loyalty Measurement Rankings 9
Network Operator Loyalty Insights 10
Network Operator Business Attributes 13
Drivers of Customer Loyalty 15
Operator Mobile App Performance Grid 16
Mobile App User Experience Insights 17
Impact of Mobile Applications on Ecosystem 20
Mobile Handsets 21
Smartphone vs. Feature Phones 22
RAPID Loyalty Measurement Primer 23
Customer Loyalty 23
Customer Lifetime Value 24
References 25
Who we are 26
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
2. Agenda
•
Introduction / a2c Overview
•
Modeling for End Users
•
Role of Dimensional Models in Big Data
•
Example: eCommerce
•
Structured Data: Sales
•
Semi-structured Data: Clickstream
•
Agile Dimensional Modeling Overview
•
Case Study Review
•
Q&A
!2
3. Introduction
•
a2c
•
•
Data Warehousing
•
Master Data Management
•
Closed Look Analytics and Visualization
•
•
Boutique EDM (Enterprise Data Management)
consultancy firm:
Data & Application Architecture
John DiPietro
•
•
Principal, Chief Technology Officer
Jim Stagnitto
•
Data Warehouse & MDM Architect
!3
5. Company Overview
•
Technology Solution Consultancy headquartered in Philadelphia with
regional offices in New York and Boston
•
Servicing Healthcare, Life Science, Tel-Com and Financial Services
industries with recent obtainment of our GSA schedule to pursue Federal
Government opportunities
•
Consultant base of over 2500 proven IT professionals throughout the North
East Region with a recruiting network which provides national coverage
•
Flexible approach to helping our clients with their initiatives
•
Project-based Solutions
•
Staff Augmentation
•
Managed Service Offerings – “On-Shore QA , Development & Application Support”
•
Executive & Professional Search
!5
6. Competitive Advantage
•
Founders of a2c were part of the fastest growing privately held IT consulting and staff
augmentation firm in the US from 1994-2002. Our Executive Management Team has over a
100 years collective experience and been responsible for delivering over a half-billion dollars
of IT Consulting and staff augmentation revenue from 1994 through to the present day.
•
a2c’s Recruiting Engine and Methodology is one of the best in the industry, capable of
producing quality results, on-demand for our clients
•
Resource Managers continually “Silo” disciplines with available candidates whom have
proven their abilities with us over the last 10 years
•
Our solutions organization is instrumentally involved during the screening and selection
process to ensure that candidates submitted to our clients are an ideal match
•
a2c’s Culture provides an ability to attract and retain the best talent in the industry and fosters
creativity, integrity, growth and teamwork
•
a2c provides our clients with an alternative solution to a “Big 4” consultancy at substantial
savings for projects that are between $500K and $5M due to our flexibility, agility and focus
!6
9. a2c Solutions Capabilities
•
Enterprise Data Management Practice helps clients manage their complete Information
Lifecycle from their On-line Transactional systems to their Data Warehousing, Enterprise
Reporting, Data Migration, Back-Up and Recovery Strategies (See Slide 7)
•
Business Architecture & Optimization Practice utilizes “Six Sigma Lean” methodologies to
analyze, re-engineer and automate our client’s business processes to leverage human
workflow and business rules engine technologies to create efficiencies and provide
business unit owners with the necessary metrics to continually improve performance
•
Program Management Office oversees all aspects of solutions planning and delivery
across client engagement teams and provides the methodology and frameworks which
are based on PMI® industry standards
•
Application Development & Managed Services Practice helps clients architect, implement
and deploy the latest Microsoft and Enterprise Java based applications which are built on
proven frameworks and architectures for the enterprise
•
a2c's SDLC Delivery Model is comprised of over 20 years collective best practices and
industry proven methodologies that allow our delivery teams to rapidly design, develop
and implement solutions. Our SDLC model has been designed to complement our project
management methodology, utilizing iterative development cycles that enable project
teams to provide consistently high quality, on-time deliverables, regardless of technology
platform
!9
11. Modeling for End Users
•
How to Design to Answer
Business Questions?
•
Think about how questions are articulated
•
And how the answers should be
deliveredIdentify a common question
framework
•
Design an architecture that
embraces and leverages this
common question framework
•
Utilize the best designs and
technologies to:
•
(a) derive the answers
•
(b) present them in compelling ways that
lead to the next interesting question!
!11
12. How Do We Ask Questions?
Who
What
When
“How do this quarter’s sales by sales rep of
electronic products that we promoted to retail
customers in the east compare with last year’s?
What
Who
Where
Why
!12
When
13. How Do We Ask Questions?
•
Events / Transactions
•
•
•
e.g. Sale
a immutable "fact" that occurs in a time and (typically a)
place
Interrogatives:
•
Who, What, When, Where, Why
•
Descriptive context that fully describes the event
•
a set of “dimensions" that describe events
!13
14. Dimensional Value Proposition
•
It makes sense to present answers to people using the same
taxonomy of events and interrogatives (aka: facts and dimensions
- dimensional structure) that they use when forming questions
•
Events are instances of processes :
•
It’s best to present information to people who will ask the system
questions in dimensional form
•
This is true regardless of the type of information being
interrogated, it’s source, or IT stuff (like database technologies
utilized)
•
It’s best to model this presentation layer based on the events (aka:
business processes) that underlie the questions
!14
16. Scenarios
•
A brief discussion of how and where
dimensional modeling and/or
databases fit within common and
emerging “big data” data
warehousing architectures
!16
17. Kimball Dimensional DW
Dimensional BI Semantic Layer
Dimensional Data Warehouse
Data Movement / Integration
Source Data
(Structured)
!17
18. Kimball with Big Data
Dimensional BI Semantic Layer
Dimensional Data Warehouse
Big Data
Capture
Big Data
Discovery
(e.g. HDFS)
(e.g. MR)
Data Movement / Integration Tier
Data Movement / Integration Tier
Source Data Tier
Source Data Tier
(Un/Semi-Structured)
(Structured)
!18
19. Corporate Information Factory (CIF)
Dimensional BI Semantic Layer
Dimensional Tier
(Virtual or Physical)
Corporate Information Factory 3NF DW
Data Movement / Integration
Source Data
(Structured)
!19
20. CIF with Big Data
Dimensional BI Semantic Layer
Dimensional Tier
(Virtual or Physical)
Big Data
Capture
Big Data
Discovery
(e.g. HDFS)
(e.g. MR)
Corporate Information
Factory 3NF DW
Data Movement / Integration Tier
Data Movement / Integration Tier
Source Data Tier
Source Data Tier
(Un/Semi-Structured)
(Structured)
!20
21. Data Vault
Dimensional BI Semantic Layer
Dimensional Tier
(Virtual or Physical)
Data Vault
Data Movement / Integration
Source Data
(Structured)
!21
22. Data Vault with Big Data
Dimensional BI Semantic Layer
Dimensional Tier
(Virtual or Physical)
Big Data
Capture
Big Data
Discovery
(e.g. HDFS)
(e.g. MR)
Data Vault
Data Movement / Integration Tier
Data Movement / Integration Tier
Source Data Tier
Source Data Tier
(Un/Semi-Structured)
(Structured)
!22
24. Common Framework
Dimensional BI Semantic Layer
Dimensional Tier
[Physical (Kimball) or Virtual (CIF or Data Vault)
Persistant Un/
Semi-Structured
Staging Area
Unstructured ->
Structured
Data Discovery
Processing
Persistent Structured Data
Repository
(not needed for Kimball)
Un/Semi-Structured Data
Movement
Structured Data Movement
Un/Semi-Structured Source Data
Structured Source Data
(Structured)
!24
Insight
Generation /
Data Mining
25. Common Framework
Dining Room
Readily Accessible to End Users
(and BI Developers)
Safe, Hospital Environment
Data Assets “Ready for Primetime”
Dimensionally Structured
Dimensional BI Semantic Layer
Dimensional Tier
[Physical (Kimball) or Virtual (CIF or Data Vault)
Persistant Un/
Semi-Structured
Staging Area
Unstructured ->
Structured Data
Discovery
Processing
Persistent Structured Data
Repository
Kitchen
(not needed for Kimball)
Un/Semi-Structured Data Movement
Structured Data Movement
Un/Semi-Structured Source Data
Structured Source Data
(Structured)
Clickstream Data
Off Limits to End Users
Data Professionals Only Please
Dangerous / Inhospitable Environment
Data Assets “Not Ready for Primetime”
Structured Variably For Data Processing
eCommerce Sale
eCommerce Example
!25
32. I keep six honest serving-men
(They taught me all I knew);
Their names are What and Why and When
And How and Where and Who…
–Rudyard Kipling
!32
!32
43. DW Architectures: A Brief History
Corporate Information
Factory
!
Data-Driven Analysis
Undisciplined Dimensional
!
Report-Driven Analysis
Dimensional Bus
Architecture
!
Process-Driven Analysis
44. 7Ws Dimensional Model
When
Who
Time
Customer
Day
How – Facts:
Employee
Month
Much
Third Party
Fiscal Period
Many
Organization
Often
£$€
Where
What
Location
Product
??
Why
Service
Store
Causal
Transactions
Ship To
Promotion
Hospital
Reason
Geographic
Weather
Competition
47. Tech Design Artifacts?
CALENDAR
PRODUCT
Date Key
Product Key
Date
Day
Day in Week
Day in Month
Day in Qtr
Day in Year
Month
Qtr
Year
Weekday Flag
Holiday Flag
Product Code
Product Description
Product Type
Brand
Subcategory
Category
SALES FACT
Date Key
Product Key
Store Key
Promotion Key
Quantity Sold
Revenue
Cost
Basket Count
STORE
PROMOTION
Store Key
Promotion Key
Store Code
Store Name
URL
Store Manager
Region
Country
Promotion Code
Promotion Name
Promotion Type
Discount Type
Ad Type
50. Waterfall BI/DW
Limited Stakeholder interaction
Analysis
Design
Development
This Year
BDUF
Stakeholder
Requirements
Input
Data
Model
Next Year
Test
Release
ETL
BI
DATA
VALUE?
51. Agile DW/BI Development
Stakeholder interaction
?
JEDUF
BI
Prototyping
ETL
Review
Release
This Year
Next Year
Iteration 1
VALUE?
Iteration 2
ETL
BI
Iteration 3Rev
ADM
VALUE
Iteration …
VALUE!
DATA
Iteration n
VALUE!
VALUE!
52. State of The
DW Field
Solid:
Dimensional Data Warehouse Design is Mature
Proven Design Patterns Exist for Common
Requirements
Hit or Miss:
Collecting Unambiguous and Thorough
Requirements
Slotting Requirements into Proven Design
Patterns
End-User Ownership and Validation
Too Often: Snatching Defeat from the Jaws of
Victory
!52
54. BEAM✲ Methodology
Structured, non-technical, collaborative working
conversation directly with BI Users
BEAM✲
BI User’s Business
Process, Organizational,
Hierarchical, and Data
Knowledge
• Focused Data Profiling
•
Data
Modeler
BI Stakeholders
• Logical and Physical
(Kimball-esque)
Dimensional Data Models
• Example data
• Detailed and Testable ETL
Specification
• Instantiated DW
Prototype
57. Agile Data Modeling Requirements
•
Techniques for encouraging interaction
•
Must use simple, inclusive notation and tools
•
Must be quick: hours rather than days – modelstorming
•
Balance ‘just in time’ (JIT) and ‘just enough design up
front’ (JEDUF) to reduce design rework
•
DW designers must embrace data model change, allow models
to evolve, avoid generic data models; need design patterns they
can trust to represent tomorrow’s BI requirements tomorrow
•
ETL and BI developers must embrace database change; need
tool support
!57
60. CALENDAR
PRODUCT
Date Key
Product Key
Date
Day
Day in Week
Day in Month
Day in Qtr
Day in Year
Month
Qtr
Year
Weekday Flag
Holiday Flag
Product Code
Product Description
Product Type
Brand
Subcategory
Category
SALES FACT
Date Key
Product Key
Store Key
Promotion Key
Quantity Sold
Revenue
Cost
Basket Count
STORE
PROMOTION
Store Key
Promotion Key
Store Code
Store Name
URL
Store Manager
Region
Country
Promotion Code
Promotion Name
Promotion Type
Discount Type
Ad Type
65. Collaborative / Conversational Design
Who does what?
“Customers buy products”
BEAM✲
Modeler
Subjects Verb Objects
BI Users
66. Design Using Natural Language
•
Verbs – Events – Relationships – Fact Tables
•
Nouns – Details – Entities – Dimensions
•
Main Clause – Subject-Verb-Object
•
Prepositions – connect additional details to the
main clause
•
Interrogatives – The 7Ws – Dimension Types
•
Business Vocabulary - no IT-Speak
!66
67. “Spreadsheet”-like Models
Event Table Name (filled in later)
Subject Column Name
Verb
Object Column Name
Interrogative
Details
Example Data (4-6
rows)
69. Capture Example Data
verb
on/at/every
SUBJECT
OBJECT
EVENT
DATE
[who]
[what]
[when]
[where]
[how many]
[why]
[how]
Typical
Typical/Popular
Typical
Typical
Typical/Average
Typical/Normal
Typical/Normal
Different
Different
Different
Different
Different
Different
Different
Repeat
Repeat
Repeat
Repeat
Repeat
Repeat
Repeat
Missing
Missing
Missing
Missing
Missing
Missing
Missing
Group
Multiple/Bundle
Old, Low
Old, Low Value
Oldest needed
Near
Min, Negative, 0
New, High
New, High
Most Recent, Future
Far
Max, Precision
Multi-Level
Engage business users
Clarify definitions / Conform Dimensions
Illustrate exceptions
Drive out uniqueness
“Show and tell”
Multiple Values
Exceptional
Exceptional
77. Model How Many Measures
•
Additive – can be summed up over any combination
of dimensions. No special rules
•
Non-additive – can not be summed over any
dimension e.g. unit price or temperature
•
•
•
Must be aggregated in other ways e.g. average, min, max
Degenerate Dimensions – transaction #, timestamps, flags
Semi-additive – can not be summed across at least
one dimension e.g. balances can not be summed
over time
!77
87. Recap
•
Collaborative and Agile
•
•
Data Sourcing
•
•
Data Modeling
Data Conformance
Requirements = Design
•
•
Slots directly into proven and mature dimensional data warehousing
design patterns
Validation through Prototyping
•
Semi-automated build of dimensional data warehouse
•
Perfect compliment to Agile BI Tools and Methods (e.g. Pentaho)
!87
88. If you have been affected by
any of the issues raised
in this presentation
89. !
Agile Data Warehouse Design
Lawrence Corr, Jim Stagnitto, Decision Press, November 2011
!