This is the presentation I gave at OUGF14 in Helsinki, Finland in June 2014.
Oracle SQL Developer Data Modeler (SDDM) has been around for a few years now and is up to version 4.x. It really is an industrial strength data modeling tool that can be used for any data modeling task you need to tackle. Over the years I have found quite a few features and utilities in the tool that I rely on to make me more efficient (and agile) in developing my models. This presentation will demonstrate at least five of these features, tips, and tricks for you. I will walk through things like modifying the delivered reporting templates, how to create and applying object naming templates, how to use a table template and transformation script to add audit columns to every table, and using the new meta data export tool and several other cool things you might not know are there. Since there will likely be patches and new releases before the conference, there is a good chance there will be some new things for me to show you as well. This might be a bit of a whirlwind demo, so get SDDM installed on your device and bring it to the session so you can follow along.
OER UNIT 1- SCHEMA DESIGN - DATA WAREHOUSINGGirija Muscut
This presentation discuss star schema, snowflake schema design. Explain completely create dimension, alter dimension, validation of dimension and dimension status, compile state
Not to be confused with Oracle Database Vault (a commercial db security product), Data Vault Modeling is a specific data modeling technique for designing highly flexible, scalable, and adaptable data structures for enterprise data warehouse repositories. It is not a replacement for star schema data marts (and should not be used as such). This approach has been used in projects around the world (Europe, Australia, USA) for the last 10 years but is still not widely known or understood. The purpose of this presentation is to provide attendees with a detailed introduction to the technical components of the Data Vault Data Model, what they are for and how to build them. The examples will give attendees the basics for how to build, and design structures when using the Data Vault modeling technique. The target audience is anyone wishing to explore implementing a Data Vault style data model for an Enterprise Data Warehouse, Operational Data Warehouse, or Dynamic Data Integration Store. See more content like this by following my blog http://kentgraziano.com or follow me on twitter @kentgraziano.
OER UNIT 1- SCHEMA DESIGN - DATA WAREHOUSINGGirija Muscut
This presentation discuss star schema, snowflake schema design. Explain completely create dimension, alter dimension, validation of dimension and dimension status, compile state
Not to be confused with Oracle Database Vault (a commercial db security product), Data Vault Modeling is a specific data modeling technique for designing highly flexible, scalable, and adaptable data structures for enterprise data warehouse repositories. It is not a replacement for star schema data marts (and should not be used as such). This approach has been used in projects around the world (Europe, Australia, USA) for the last 10 years but is still not widely known or understood. The purpose of this presentation is to provide attendees with a detailed introduction to the technical components of the Data Vault Data Model, what they are for and how to build them. The examples will give attendees the basics for how to build, and design structures when using the Data Vault modeling technique. The target audience is anyone wishing to explore implementing a Data Vault style data model for an Enterprise Data Warehouse, Operational Data Warehouse, or Dynamic Data Integration Store. See more content like this by following my blog http://kentgraziano.com or follow me on twitter @kentgraziano.
Data modeling continues to be a tried-and-true method of managing critical data aspects from both the business and technical perspective. Like any tool or methodology, there is a “right tool for the right job”, and specific model types exist for both business and technical users across operational, reporting, analytic, and other use cases. This webinar will provide an overview of the various data modeling techniques available, and how to use each for maximum value to the organization.
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
Data can provide tremendous value to an organization in today’s information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
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
Data Vault Modeling and Methodology introduction that I provided to a Montreal event in September 2011. It covers an introduction and overview of the Data Vault components for Business Intelligence and Data Warehousing. I am Dan Linstedt, the author and inventor of Data Vault Modeling and methodology.
If you use the images anywhere in your presentations, please credit http://LearnDataVault.com as the source (me).
Thank-you kindly,
Daniel Linstedt
Power BI data modeling is the process of creating a relationship between common columns of multiple tables. If the column headings are the same across tables, then Power BI auto-detects the relationship between tables. Using these columns, we can merge the tables as well.
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
Activate Data Governance Using the Data CatalogDATAVERSITY
Data Governance programs depend on the activation of data stewards that are held formally accountable for how they manage data. The data catalog is a critical tool to enable your stewards to contribute and interact with an inventory of metadata about the data definition, production, and usage. This interaction is active Data Governance in the truest sense of the word.
In this RWDG webinar, Bob Seiner will share tips and techniques focused on activating your data stewards through a data catalog. Data Governance programs that involve stewards in daily activities are more likely to demonstrate value from their data-intensive investments.
Bob will address the following in this webinar:
- A comparison of active and passive Data Governance
- What it means to have an active Data Governance program
- How a data catalog tool can be used to activate data stewards
- The role a data catalog plays in Data Governance
- The metadata in the data catalog will not govern itself
Power BI has become a product with a ton of exciting features. This presentation will give an overview of some of them, including Power BI Desktop, Power BI service, what’s new, integration with other services, Power BI premium, and administration.
Data Catalog in Denodo Platform 7.0: Creating a Data Marketplace with Data Vi...Denodo
Watch Alberto's session from Fast Data Strategy on-demand here: https://buff.ly/2wByS41
Gartner’s recently published report “Data Catalogs Are the New Black in Data Management Analytics” emphasizes the importance of data catalogs.
Watch this session to learn more about:
• The vision behind the Denodo Data Catalog
• How to maximize information value with the Denodo Data Catalog
• Why it is essential to combine data delivery with a data catalog
Agile Data Engineering: Introduction to Data Vault 2.0 (2018)Kent Graziano
(updated slides used for North Texas DAMA meetup Oct 2018) As we move more and more towards the need for everyone to do Agile Data Warehousing, we need a data modeling method that can be agile with us. Data Vault Data Modeling is an agile data modeling technique for designing highly flexible, scalable, and adaptable data structures for enterprise data warehouse repositories. It is a hybrid approach using the best of 3NF and dimensional modeling. It is not a replacement for star schema data marts (and should not be used as such). This approach has been used in projects around the world (Europe, Australia, USA) for over 15 years and is now growing in popularity. The purpose of this presentation is to provide attendees with an introduction to the components of the Data Vault Data Model, what they are for and how to build them. The examples will give attendees the basics:
• What the basic components of a DV model are
• How to build, and design structures incrementally, without constant refactoring
Microsoft SQL Server Analysis Services (SSAS) - A Practical Introduction Mark Ginnebaugh
Patrick Sheehan of Microsoft covers platform architecture, data warehousing methodology, and multi-dimensional cube development.
You will learn:
* How to develop and deploy data cubes using SQL Server Analysis Services (SSAS)
* Optimal data warehouse methodology for use with SSAS
* Tips/tricks for designing & building cubes over no warehouse/suboptimal source system (it happens)
* Cube processing types - How/why to use each
* Cube design practices + How to build and deploy cubes!
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
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.
Worst Practices in Data Warehouse DesignKent Graziano
This presentation was given at OakTable World 2014 (#OTW14) in San Francisco. After many years of designing data warehouses and consulting on data warehouse architectures, I have seen a lot of bad design choices by supposedly experienced professional. A sense of professionalism, confidentiality agreements, and some sense of common decency have prevented me from calling people out on some of this. No more! In this session I will walk you through a typical bad design like many I have seen. I will show you what I see when I reverse engineer a supposedly complete design and walk through what is wrong with it and discuss options to correct it. This will be a test of your knowledge of data warehouse best practices by seeing if you can recognize these worst practices.
Agile Data Warehousing: Using SDDM to Build a Virtualized ODSKent Graziano
(This is the talk I gave at Houston DAMA and Agile Denver BI meetups)
At a past client, in order to meet timelines to fulfill urgent, unmet reporting needs, I found it necessary to build a virtualized Operational Data Store as the first phase of a new Data Vault 2.0 project. This allowed me to deliver new objects, quickly and incrementally to the report developer so we could quickly show the business users their data. In order to limit the need for refactoring in later stages of the data warehouse development, I chose to build this virtualization layer on top of a Type 2 persistent staging layer. All of this was done using Oracle SQL Developer Data Modeler (SDDM) against (gasp!) a MS SQL Server Database. In this talk I will show you the architecture for this approach, the rationale, and then the tricks I used in SDDM to build all the stage tables and views very quickly. In the end you will see actual SQL code for a virtual ODS that can easily be translated to an Oracle database.
Data modeling continues to be a tried-and-true method of managing critical data aspects from both the business and technical perspective. Like any tool or methodology, there is a “right tool for the right job”, and specific model types exist for both business and technical users across operational, reporting, analytic, and other use cases. This webinar will provide an overview of the various data modeling techniques available, and how to use each for maximum value to the organization.
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
Data can provide tremendous value to an organization in today’s information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
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
Data Vault Modeling and Methodology introduction that I provided to a Montreal event in September 2011. It covers an introduction and overview of the Data Vault components for Business Intelligence and Data Warehousing. I am Dan Linstedt, the author and inventor of Data Vault Modeling and methodology.
If you use the images anywhere in your presentations, please credit http://LearnDataVault.com as the source (me).
Thank-you kindly,
Daniel Linstedt
Power BI data modeling is the process of creating a relationship between common columns of multiple tables. If the column headings are the same across tables, then Power BI auto-detects the relationship between tables. Using these columns, we can merge the tables as well.
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
Activate Data Governance Using the Data CatalogDATAVERSITY
Data Governance programs depend on the activation of data stewards that are held formally accountable for how they manage data. The data catalog is a critical tool to enable your stewards to contribute and interact with an inventory of metadata about the data definition, production, and usage. This interaction is active Data Governance in the truest sense of the word.
In this RWDG webinar, Bob Seiner will share tips and techniques focused on activating your data stewards through a data catalog. Data Governance programs that involve stewards in daily activities are more likely to demonstrate value from their data-intensive investments.
Bob will address the following in this webinar:
- A comparison of active and passive Data Governance
- What it means to have an active Data Governance program
- How a data catalog tool can be used to activate data stewards
- The role a data catalog plays in Data Governance
- The metadata in the data catalog will not govern itself
Power BI has become a product with a ton of exciting features. This presentation will give an overview of some of them, including Power BI Desktop, Power BI service, what’s new, integration with other services, Power BI premium, and administration.
Data Catalog in Denodo Platform 7.0: Creating a Data Marketplace with Data Vi...Denodo
Watch Alberto's session from Fast Data Strategy on-demand here: https://buff.ly/2wByS41
Gartner’s recently published report “Data Catalogs Are the New Black in Data Management Analytics” emphasizes the importance of data catalogs.
Watch this session to learn more about:
• The vision behind the Denodo Data Catalog
• How to maximize information value with the Denodo Data Catalog
• Why it is essential to combine data delivery with a data catalog
Agile Data Engineering: Introduction to Data Vault 2.0 (2018)Kent Graziano
(updated slides used for North Texas DAMA meetup Oct 2018) As we move more and more towards the need for everyone to do Agile Data Warehousing, we need a data modeling method that can be agile with us. Data Vault Data Modeling is an agile data modeling technique for designing highly flexible, scalable, and adaptable data structures for enterprise data warehouse repositories. It is a hybrid approach using the best of 3NF and dimensional modeling. It is not a replacement for star schema data marts (and should not be used as such). This approach has been used in projects around the world (Europe, Australia, USA) for over 15 years and is now growing in popularity. The purpose of this presentation is to provide attendees with an introduction to the components of the Data Vault Data Model, what they are for and how to build them. The examples will give attendees the basics:
• What the basic components of a DV model are
• How to build, and design structures incrementally, without constant refactoring
Microsoft SQL Server Analysis Services (SSAS) - A Practical Introduction Mark Ginnebaugh
Patrick Sheehan of Microsoft covers platform architecture, data warehousing methodology, and multi-dimensional cube development.
You will learn:
* How to develop and deploy data cubes using SQL Server Analysis Services (SSAS)
* Optimal data warehouse methodology for use with SSAS
* Tips/tricks for designing & building cubes over no warehouse/suboptimal source system (it happens)
* Cube processing types - How/why to use each
* Cube design practices + How to build and deploy cubes!
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
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.
Worst Practices in Data Warehouse DesignKent Graziano
This presentation was given at OakTable World 2014 (#OTW14) in San Francisco. After many years of designing data warehouses and consulting on data warehouse architectures, I have seen a lot of bad design choices by supposedly experienced professional. A sense of professionalism, confidentiality agreements, and some sense of common decency have prevented me from calling people out on some of this. No more! In this session I will walk you through a typical bad design like many I have seen. I will show you what I see when I reverse engineer a supposedly complete design and walk through what is wrong with it and discuss options to correct it. This will be a test of your knowledge of data warehouse best practices by seeing if you can recognize these worst practices.
Agile Data Warehousing: Using SDDM to Build a Virtualized ODSKent Graziano
(This is the talk I gave at Houston DAMA and Agile Denver BI meetups)
At a past client, in order to meet timelines to fulfill urgent, unmet reporting needs, I found it necessary to build a virtualized Operational Data Store as the first phase of a new Data Vault 2.0 project. This allowed me to deliver new objects, quickly and incrementally to the report developer so we could quickly show the business users their data. In order to limit the need for refactoring in later stages of the data warehouse development, I chose to build this virtualization layer on top of a Type 2 persistent staging layer. All of this was done using Oracle SQL Developer Data Modeler (SDDM) against (gasp!) a MS SQL Server Database. In this talk I will show you the architecture for this approach, the rationale, and then the tricks I used in SDDM to build all the stage tables and views very quickly. In the end you will see actual SQL code for a virtual ODS that can easily be translated to an Oracle database.
Agile Data Engineering - Intro to Data Vault Modeling (2016)Kent Graziano
(Updated deck) As we move more and more towards the need for everyone to do Agile Data Warehousing, we need a data modeling method that can be agile with us. Data Vault Data Modeling is an agile data modeling technique for designing highly flexible, scalable, and adaptable data structures for enterprise data warehouse repositories. It is a hybrid approach using the best of 3NF and dimensional modeling. It is not a replacement for star schema data marts (and should not be used as such). This approach has been used in projects around the world (Europe, Australia, USA) for over 10 years but is still not widely known or understood. The purpose of this presentation is to provide attendees with an introduction to the components of the Data Vault Data Model, what they are for and how to build them. The examples will give attendees the basics:
• What the basic components of a DV model are
• How to build, and design structures incrementally, without constant refactoring
Data Vault 2.0: Using MD5 Hashes for Change Data CaptureKent Graziano
This presentation was given at OakTable World 2014 (#OTW14) in San Francisco as a short Ted-style 10 minute talk. In it I introduce Data Vault 2.0 and its innovative approach to doing change data capture in a data warehouse by using MD5 Hash columns.
I gave this presentation at OUGF14 in Helsinki, Finland and again for TDWI Nashville. This presentation takes a look at the Agile Manifesto and the 12 Principles of Agile Development and discusses how these apply to Data Warehousing and Business Intelligence projects. Several examples and details from my past experience are included.
Extreme BI: Creating Virtualized Hybrid Type 1+2 DimensionsKent Graziano
From a talk I gave at WWDVC and ECO in 2015 about how we built virtual dimensions (views) on a data vault-style data warehouse (see Data Warehousing in the Real World for full details on that architecture)
(OTW13) Agile Data Warehousing: Introduction to Data Vault ModelingKent Graziano
This is the presentation I gave at OakTable World 2013 in San Francisco. #OTW13 was held at the Children's Creativity Museum next to the Moscone Convention Center and was in parallel with Oracle OpenWorld 2013.
The session discussed our attempts to be more agile in designing enterprise data warehouses and how the Data Vault Data Modeling technique helps in that approach.
Agile Methods and Data Warehousing (2016 update)Kent Graziano
This presentation takes a look at the Agile Manifesto and the 12 Principles of Agile Development and discusses how these apply to Data Warehousing and Business Intelligence projects. Several examples and details from my past experience are included. Includes more details on using Data Vault as well. (I gave this presentation at OUGF14 in Helsinki, Finland and again in 2016 for TDWI Nashville.)
Agile Data Warehouse Modeling: Introduction to Data Vault Data ModelingKent Graziano
This is a presentation I gave at OUGF14 in Helsinki, Finland.
Data Vault Data Modeling is an agile data modeling technique for designing highly flexible, scalable, and adaptable data structures for enterprise data warehouse repositories. It is a hybrid approach using the best of 3NF and dimensional modeling. It is not a replacement for star schema data marts (and should not be used as such). This approach has been used in projects around the world (Europe, Australia, USA) for the last 10 years but is still not widely known or understood. The purpose of this presentation is to provide attendees with a detailed introduction to the components of the Data Vault Data Model, what they are for and how to build them. The examples will give attendees the basics for how to build, and design structures incrementally, without constant refactoring, when using the Data Vault modeling technique. This technique works well for:
• Building the Enterprise Data Warehouse repository in a CIF architecture
• Building a Persistent Staging Area (PSA) in a Kimball Bus Architecture
• Building your data model incrementally, one sprint at a time using a repeatable technique
• Providing a model that is easily extensible without need to re-engineer existing structure or load processes
These are the slides from my talk at Data Day Texas 2016 (#ddtx16).
The world of data warehousing has changed! With the advent of Big Data, Streaming Data, IoT, and The Cloud, what is a modern data management professional to do? It may seem to be a very different world with different concepts, terms, and techniques. Or is it? Lots of people still talk about having a data warehouse or several data marts across their organization. But what does that really mean today in 2016? How about the Corporate Information Factory (CIF), the Data Vault, an Operational Data Store (ODS), or just star schemas? Where do they fit now (or do they)? And now we have the Extended Data Warehouse (XDW) as well. How do all these things help us bring value and data-based decisions to our organizations? Where do Big Data and the Cloud fit? Is there a coherent architecture we can define? This talk will endeavor to cut through the hype and the buzzword bingo to help you figure out what part of this is helpful. I will discuss what I have seen in the real world (working and not working!) and a bit of where I think we are going and need to go in 2016 and beyond.
Demystifying Data Warehouse as a Service (DWaaS)Kent Graziano
This is from the talk I gave at the 30th Anniversary NoCOUG meeting in San Jose, CA.
We all know that data warehouses and best practices for them are changing dramatically today. As organizations build new data warehouses and modernize established ones, they are turning to Data Warehousing as a Service (DWaaS) in hopes of taking advantage of the performance, concurrency, simplicity, and lower cost of a SaaS solution or simply to reduce their data center footprint (and the maintenance that goes with that).
But what is a DWaaS really? How is it different from traditional on-premises data warehousing?
In this talk I will:
• Demystify DWaaS by defining it and its goals
• Discuss the real-world benefits of DWaaS
• Discuss some of the coolest features in a DWaaS solution as exemplified by the Snowflake Elastic Data Warehouse.
Every development shop is unique, and sometimes that uniqueness can hinder using tools. SQL Developer and Data Modeler have multiple mechanisms that allow for customizations. These customizations can range from simple to complex and can help tailor the tooling to any environment. Some are as simple as colored warning to remind the user what is production vs. development. Some could auto-generate code by walking over a data model. The most complex can change anything at all in the tool. Ever think of a command that should be in SQL Plus scripting? Want to auto-generate table APIs?
Yes, Oracle SQL Developer allows you to make a JDBC connection to SQL Server. Here's a quick overview of things you can do, plus a reminder that it's also the official migration platform for Oracle Database migrations.
Your Raw Data is Ready - Introduction to Analytics Engineering | SMX Advanced...Christopher Gutknecht
In this SMX Advanced 2022 session, Christopher talks about the potential of working with raw data and how to properly approach the task of transforming raw data into high-quality reusable tables in your data warehouse. dbt as a transformation framework plays a key role in delivering quality and structure for this process. The chance for search marketers is to acquire data modeling skills and learn to build their own custom data products around Google Ads and Google Analytics. This talk is not just for inhouse-teams, also for agencies seeking to extend their services into data management.
How Oracle Sales Cloud Release 12 Will Boost Sales ProductivityPerficient, Inc.
Release 12 of Oracle Sales Cloud is just around the corner and with it comes some great improvements that make it an even more compelling solution for enabling modern sales in the cloud.
Oracle Engagement Cloud is the crown jewel of the release, combining Oracle’s leading sales and service capabilities. From a single screen, users can stay abreast of customer needs with a unique combination of sales automation, service request management, and knowledge management for a comprehensive customer experience.
Our discussion on release 12 of Oracle Sales Cloud included:
-Review of key release changes
-Upgrade preparations
-Engagement Cloud and what to expect
Learn about best practices for developing Moodle code from custom plugins to submitting bug fixes for core Moodle code. Topics covered will include:
Overview of Moodle plugin systems and available API's
Working with the Moodle tracker
Peer review process
Maintaining a custom plugin using Github
Submitting core patches / bug fixes to Moodle HQ
Canadian Experts Discuss Modern Data Stacks and Cloud Computing for 5 Years o...Daniel Zivkovic
Two #ModernDataStack talks and one DevOps talk: https://youtu.be/4R--iLnjCmU
1. "From Data-driven Business to Business-driven Data: Hands-on #DataModelling exercise" by Jacob Frackson of Montreal Analytics
2. "Trends in the #DataEngineering Consulting Landscape" by Nadji Bessa of Infostrux Solutions
3. "Building Secure #Serverless Delivery Pipelines on #GCP" by Ugo Udokporo of Google Cloud Canada
We ran out of time for the 4th presenter, so the event will CONTINUE in March... stay tuned! Compliments of #ServerlessTO.
An overview on how we have approached dataops to allow analysts and data scientists to work quickly and release frequently with high confidence. Covers:
- Cloud/multi-cloud architecture
- CI/CD in the data space
- Development, testing, and deployment
- Monitoring and alerting
Oracle Product Hub Cloud: A True Enterprise Product Master SolutionKPIT
Session Panel Discussion that includes:
Thermo Fisher Scientific- Their Vision of Enterprise Product Master Data Solution and its benefits for Thermo Fisher. Why they chose Oracle Product Hub Cloud for their strategy
Pella Corporation- Their story of Oracle Product Hub Cloud Implementation, Roadmap, Benefits and Lesson Learnt
KPIT- as Product Hub Cloud System Integrator of Thermo Fisher and Pella sharing best practices and point of view
IBM Notes and Domino 9 Social Edition includes many new controls to make it easier to develop a great web 2.0 user interface for your XPages applications. This webinar will focus on those new controls that deliver the most in terms of rapidly building an exceptional user experience.
Learn how to use the form table and the data view controls to surface IBM Domino data with a modern web interface. Then learn to use navigators, dialogs, value pickers, the in place form, tooltips and Dojo UI controls to allow your users to interact with your application. Finally, you'll learn how to set up the application layout control to provide an interface framework with menus using the IBM OneUI interface, or even Twitter Bootstrap.
Creating a Great XPages User Interface, TLCC Teamstudio Webinar - Feb, 2014Howard Greenberg
IBM Notes and Domino 9 Social Edition includes many new controls to make it easier to develop a great web 2.0 user interface for your XPages applications. This webinar will focus on those new controls that deliver the most in terms of rapidly building an exceptional user experience. Learn how to use the form table and the data view controls to surface IBM Domino data with a modern web interface. Then learn to use navigators, dialogs, value pickers, the in place form, tooltips and Dojo UI controls to allow your users to interact with your application. Finally, you'll learn how to set up the application layout control to provide an interface framework with menus using the IBM OneUI interface or even Twitter Bootstrap.
Slide deck from the BrightGen webinar on the new features in the Salesforce Winter 22 release. Presented by Keir Bowden CTO, and Clive Platt, Senior Service Management Consultant.
You can access the video at : https://www.youtube.com/watch?v=JV_g_QgAfq0
Supercharge your data analytics with BigQueryMárton Kodok
Powering interactive data analysis require massive architecture, and Know-How to build a fast real-time computing system. BigQuery solves this problem by enabling super-fast, SQL-like queries against petabytes of data using the processing power of Google’s infrastructure. We will cover its core features, creating tables, columns, views, working with partitions, clustering for cost optimizations, streaming inserts, User Defined Functions, and several use cases for everydaay developer: funnel analytics, behavioral analytics, exploring unstructured data.
The other part will be about BigQuery ML, which enables users to create and execute machine learning models in BigQuery using standard SQL queries. BigQuery ML democratizes machine learning by enabling SQL practitioners to build models using existing SQL tools and skills. BigQuery ML increases development speed by eliminating the need to move data.
SmartProfiler for Active Directory Office 365 and Azure Virtual Desktop Asses...googleservice3
Microsoft AVD Assessment, Active Directory Assessment, Office 365 Assessment, and FSLogix Assessment are the four functions provided by SmartProfiler. The tool is intended to detect problems in the aforementioned environments and generate an actionable report in Word/HTML format. SmartProfiler Assessment is intended to be used as one-time assessment tool. Please use DCA if you want to perform continuous assessment. DCA also supports more features and ability to create more modules.
Similar to Top Five Cool Features in Oracle SQL Developer Data Modeler (20)
Balance agility and governance with #TrueDataOps and The Data CloudKent Graziano
DataOps is the application of DevOps concepts to data. The DataOps Manifesto outlines WHAT that means, similar to how the Agile Manifesto outlines the goals of the Agile Software movement. But, as the demand for data governance has increased, and the demand to do “more with less” and be more agile has put more pressure on data teams, we all need more guidance on HOW to manage all this. Seeing that need, a small group of industry thought leaders and practitioners got together and created the #TrueDataOps philosophy to describe the best way to deliver DataOps by defining the core pillars that must underpin a successful approach. Combining this approach with an agile and governed platform like Snowflake’s Data Cloud allows organizations to indeed balance these seemingly competing goals while still delivering value at scale.
Given in Montreal on 14-Dec-2021
Wonder what this data mesh stuff is all about? What are the principles of data mesh? Can you or should you consider data mesh as the approach for your analytics platform? And most important - how can Snowflake help?
Given in Montreal on 14-Dec-2021
HOW TO SAVE PILEs of $$$BY CREATING THE BEST DATA MODEL THE FIRST TIME (Ksc...Kent Graziano
A good data model, done right the first time, can save you time and money. We have all seen the charts on the increasing cost of finding a mistake/bug/error late in a software development cycle. Would you like to reduce, or even eliminate, your risk of finding one of those errors late in the game? Of course you would! Who wouldn't? Nobody plans to miss a requirement or make a bad design decision (well nobody sane anyway). No data modeler or database designer worth their salt wants to leave a model incomplete or incorrect. So what can you do to minimize the risk?
In this talk I will show you a best practice approach to developing your data models and database designs that I have been using for over 15 years. It is a simple, repeatable process for reviewing your data models. It is one that even a non-modeler could follow. I will share my checklist of what to look for and what to ask the data modeler (or yourself) to make sure you get the best possible data model. As a bonus I will share how I use SQL Developer Data Modeler (a no-cost data modeling tool) to collect the information and report it.
This talk will introduce you to the Data Cloud, how it works, and the problems it solves for companies across the globe and across industries. The Data Cloud is a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the Data Cloud
Delivering Data Democratization in the Cloud with SnowflakeKent Graziano
This is a brief introduction to Snowflake Cloud Data Platform and our revolutionary architecture. It contains a discussion of some of our unique features along with some real world metrics from our global customer base.
Demystifying Data Warehousing as a Service (GLOC 2019)Kent Graziano
Extended deck from the 2019 GLOC event in Cleveland. Discusses what a DWaaS is, the top 10 features of Snowflake that represent that, and a check list for what questions to ask when choosing a cloud based data warehouse.
[Given at DAMA WI, Nov 2018] With the increasing prevalence of semi-structured data from IoT devices, web logs, and other sources, data architects and modelers have to learn how to interpret and project data from things like JSON. While the concept of loading data without upfront modeling is appealing to many, ultimately, in order to make sense of the data and use it to drive business value, we have to turn that schema-on-read data into a real schema! That means data modeling! In this session I will walk through both simple and complex JSON documents, decompose them, then turn them into a representative data model using Oracle SQL Developer Data Modeler. I will show you how they might look using both traditional 3NF and data vault styles of modeling. In this session you will:
1. See what a JSON document looks like
2. Understand how to read it
3. Learn how to convert it to a standard data model
Using OBIEE and Data Vault to Virtualize Your BI Environment: An Agile ApproachKent Graziano
First we interview the users, then we design a reporting model based on those interviews. We follow that up with mounds of ETL development to load the new model, basically keeping the user community in the dark during all that development. Does this sound familiar?
This presentation will demonstrate an alternative approach using the Data Vault Data Modeling technique to build a flexible, easily-extensible “Foundation” layer in our data warehouse with an Agile, iterative methodology. Relying on the Business Model and Mapping (BMM) functionality of OBIEE, we can rapidly virtualize a dimensional reporting model using the pattern-based Data Vault Foundation layer to decrease the time, and money, it takes to get BI content in front of end users. Attendees will see a sample Data Vault model designed iteratively and deployed to the semantic model of OBIEE.
Given at Oracle Open World 2011: Not to be confused with Oracle Database Vault (a commercial db security product), Data Vault Modeling is a specific data modeling technique for designing highly flexible, scalable, and adaptable data structures for enterprise data warehouse repositories. It has been in use globally for over 10 years now but is not widely known. The purpose of this presentation is to provide an overview of the features of a Data Vault modeled EDW that distinguish it from the more traditional third normal form (3NF) or dimensional (i.e., star schema) modeling approaches used in most shops today. Topics will include dealing with evolving data requirements in an EDW (i.e., model agility), partitioning of data elements based on rate of change (and how that affects load speed and storage requirements), and where it fits in a typical Oracle EDW architecture. See more content like this by following my blog http://kentgraziano.com or follow me on twitter @kentgraziano.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Top Five Cool Features in Oracle SQL Developer Data Modeler
1. Five Cool Features in Oracle SQL Developer
Data Modeler
Kent Graziano
Data Warrior LLC
Twitter @KentGraziano
Blog: kentgraziano.com
2. Bio
Oracle ACE Director (BI/DW)
Blogger: Oracle Data Warrior
Data Architecture and Data Warehouse Specialist
● 30+ years in IT
● 25+ years of Oracle-related work
● 20+ years of data warehousing experience
Member: Boulder BI Brain Trust
Co-Author of
● The Business of Data Vault Modeling
● The Data Model Resource Book (1st Edition)
Past-President of ODTUG and RMOUG
Copyright 2014 Data Warrior LLC
3. Agenda
What is the SDDM?
Cool Features
● Using Object Naming Templates
● Built in Report Tool
● DDL Preview
● Adding Audit Columns to Every Table
● Using the New “Search” Feature
● Whatever else we have time for…
Copyright 2014 Data Warrior LLC
4. What is SDDM?
Modern Data Modeling Tool
Latest Release 4.0.1.XX
FREE FREE FREE
Does Logical, Relational, Physical, and
Multi Dimensional Models
Lots of options
Copyright 2014 Data Warrior LLC
5. #5 - Using Object Naming Templates
Do you have naming standards?
Get some!
Set them here:
● Right Mouse Menu on Design
● Properties -> Settings -> Naming Standard
-> Templates
Lots of options
Set (or change) then apply
Copyright 2014 Data Warrior LLC
9. #4 - Built in Report Tool
File -> Reports
Lots of options
● Object type to report on
● Pick output format (PDF, RTF, HTML)
● Create or use reusable template
● Create specific configuration
● Pick models and subviews to filter objects
Copyright 2014 Data Warrior LLC
11. #3- DDL Preview
Can you say “agile”?
Check and test your design on the fly
Right mouse on a table
● Pick DDL Preview
Cut and paste into SQL Developer window
● Execute
Go back make fixes if needed
Select another table with window open
● DDL changes on the fly for the new focus
Copyright 2014 Data Warrior LLC
13. #2 - Adding Audit Columns
Use Table Template and Transformation Script
● New in 4.x – apply during forward engineering
Tools -> Design Rules -> Custom Transformations
Look for “table template” delivered script
● No change needed
Create table called table_template
● With required columns and properties to be copied
Select “Apply”
● Changes all tables in design
Note: can script all sorts of stuff
● Check /datamodeler/xmlmetadata/doc
Copyright 2014 Data Warrior LLC
16. #1 - Using the New Search Feature
Available since 3.3
● Edit -> Find
● Pull up bottom pane to see it
Simply or complex search
● Use ‘*’ as wildcard
● Filter based on object type
Can then export or report the results
● Define a reusable output format
Exported text can be edited then re-imported!
● Right mouse option on Logical or Relational
● Great way to get users to edit definitions
Copyright 2014 Data Warrior LLC
19. Extra - Using Built in Quality Checks
AKA Design Rules
Tools -> Design Rules -> Design Rules
Pick rule to check
● Apply Selected
Or just Apply All
Errors and warnings
● Can drill to problem object
Build custom rule set for standard checks
● Use “edit” button to add rules
Copyright 2014 Data Warrior LLC
22. In Review…
Get the latest version
● Production 4.0.1
● Did I mention that it is FREE?
Lots of options
Get on the OTN Forum
● Great support from product developers
Follow @thatJeffSmith
● Product Manager
● ThatJeffSmith.com
Copyright 2014 Data Warrior LLC
23. SHAMELASS PLUG: Available on Amazon.com
http://www.amazon.com/Check-Doing-Design-
Reviews-ebook/dp/B008RG9L5E/
25. Contact Information
Kent Graziano
The Oracle Data Warrior
Data Warrior LLC
Kent.graziano@att.net
On Twitter @KentGraziano
Visit my blog at
http://kentgraziano.com