The document discusses SQL Server 2008 R2 Analysis Services and provides an overview of its key components including OLAP, multidimensional data analysis using dimensions and hierarchies, and how it utilizes a dimensional data warehouse with fact and dimension tables to store and retrieve data for analysis. It also explains how Analysis Services provides scalable and extensible solutions for analytics and delivers pervasive business insights.
As we move from experience and intuition based decision making to factual decision making, it is increasingly important to capture data and store it in a way that allows us to make smarter decisions. This is where Data warehouse/Business Intelligence comes into picture. There is a huge demand for There is a huge demand for Business Intelligence professionals and this course acts as a foundation which opens the door to a variety of opportunities in Business Intelligence space. Though there are many vendors providing BI tools, very few of them provide end-end BI suite and huge customer base. Microsoft stands as leader with its user-friendly and cost effective Business Intelligence suite helping customers to get a 360 degree view of their businesses.
Introduction to Microsoft’s Master Data Services (MDS)James Serra
Master Data Services is bundled with SQL Server 2012 to help resolve many of the Master Data Management issues that companies are faced with when integrating data. In this session, James will show an overview of Master Data Services 2012, including the out of the box Web UI, the highly developed Excel Add-in, and how to get started with loading MDS with your data.
As we move from experience and intuition based decision making to factual decision making, it is increasingly important to capture data and store it in a way that allows us to make smarter decisions. This is where Data warehouse/Business Intelligence comes into picture. There is a huge demand for There is a huge demand for Business Intelligence professionals and this course acts as a foundation which opens the door to a variety of opportunities in Business Intelligence space. Though there are many vendors providing BI tools, very few of them provide end-end BI suite and huge customer base. Microsoft stands as leader with its user-friendly and cost effective Business Intelligence suite helping customers to get a 360 degree view of their businesses.
Introduction to Microsoft’s Master Data Services (MDS)James Serra
Master Data Services is bundled with SQL Server 2012 to help resolve many of the Master Data Management issues that companies are faced with when integrating data. In this session, James will show an overview of Master Data Services 2012, including the out of the box Web UI, the highly developed Excel Add-in, and how to get started with loading MDS with your data.
Microsoft master data services mds overviewEugene Zozulya
Master data management (MDM) is a technology discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise's official shared master data assets.
Master data management tools can be used to support master data management by removing duplicates, standardizing data (mass maintaining), and incorporating rules to eliminate incorrect data from entering the system in order to create an authoritative source of master data.
Microsoft Master Data Services (MDS) is the SQL Server solution for master data management. Master data management (MDM) describes the efforts made by an organization to discover and define non-transactional lists of data, with the goal of compiling maintainable master lists. An MDM project generally includes an evaluation and restructuring of internal business processes along with the implementation of MDM technology. The result of a successful MDM solution is reliable, centralized data that can be analyzed, resulting in better business decisions.
Other Master Data Services features include hierarchies, granular security, transactions, data versioning, and business rules.
Master Data Services includes the following components and tools:
- Master Data Services Configuration Manager, a tool you use to create and configure Master Data Services databases and web applications.
- Master Data Manager, a web application you use to perform administrative tasks (like creating a model or business rule), and that users access to update data.
- MDSModelDeploy.exe, a tool you use to create packages of your model objects and data so you can deploy them to other environments.
- Master Data Services web service, which developers can use to extend or develop custom solutions for Master Data Services.
As a follow-on to the presentation "Building an Effective Data Warehouse Architecture", this presentation will explain exactly what Big Data is and its benefits, including use cases. We will discuss how Hadoop, the cloud and massively parallel processing (MPP) is changing the way data warehouses are being built. We will talk about hybrid architectures that combine on-premise data with data in the cloud as well as relational data and non-relational (unstructured) data. We will look at the benefits of MPP over SMP and how to integrate data from Internet of Things (IoT) devices. You will learn what a modern data warehouse should look like and how the role of a Data Lake and Hadoop fit in. In the end you will have guidance on the best solution for your data warehouse going forward.
Creating a Tabular Model Using SQL Server 2012 Analysis ServicesCode Mastery
At Code Mastery Boston Steve Hughes, Principal Consultant at Magenic, highlights: Basics of SQL Server 2012 Analysis Services, Multidimensional Model, VS PowerPivot, Creating a Tabular Model
A Crash Course in SQL Server Administration for Reluctant Database Administra...Chad Petrovay
Reluctant DBAs are those of us who aren’t formally trained in database administration, but manage through a combination of our wits, technical manuals, and online forums. This practical session will explore best practices for installing, configuring, and maintaining Microsoft SQL Server, and highlight some SQL Server features (and Easter eggs) that can improve your user experience and institutional ROI.
Enabling Data as a Service with the JBoss Enterprise Data Services Platformprajods
This presentation was given at JUDCon 2013, Jan 17,18 at Bangalore. Presented by Prajod Vettiyattil and Gnanaguru Sattanathan. The presentation deals with the Why, What and How of Data Services and Data Services Platforms. It also explains the features of the JBoss Enterprise Data Services Platform.
The need for Data Services is explained with 3 Business use cases:
1. Post purchase customer experience improvement for an Auto manufacturer
2. Enterprise Data Access Layer
3. Data Services for Regulatory Reporting requirements like Dodd Frank
Myth Busters II: BI Tools and Data Virtualization are InterchangeableDenodo
Watch Here: https://bit.ly/2NcqU6F
We take on the 2nd myth about data virtualization and it’s one that suggests a BI tool can substitute a data virtualization software.
You might be thinking: If I can have multi-source queries and define a logical model in my reporting tool, why would I need a data virtualization software?
Reporting tools, no doubt important and necessary, focus on the visualization of data and it’s presentation to the business user. Data virtualization is a governed data access layer designed to connect to and provide transparency of all enterprise data.
Yet the myth suggests that these technologies are interchangeable. So we’re going to take it on!
Watch this webinar as we compare and contrast BI tools and data virtualization to draw a final conclusion.
This session was about Master Data Services and what it also could be used as - the client wanted an application to validate and submit warehouse inventories.
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.
Big Data and BI Tools - BI Reporting for Bay Area Startups User GroupScott Mitchell
This presentation was presented at the July 8th 2014 user group meeting for BI Reporting for Bay Area Start Ups
Content - Creation Infocepts/DWApplications
Presented by: Scott Mitchell - DWApplications
My presentation on the Visual Data Vault modeling language, presented during WWDVC 2014 in St. Albans, VT, USA.
To download the Visio stencils, check out
http://www.doerffler.com/know-how/data-vault/visual-data-vault/
and http://www.visualdatavault.com
Microsoft master data services mds overviewEugene Zozulya
Master data management (MDM) is a technology discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise's official shared master data assets.
Master data management tools can be used to support master data management by removing duplicates, standardizing data (mass maintaining), and incorporating rules to eliminate incorrect data from entering the system in order to create an authoritative source of master data.
Microsoft Master Data Services (MDS) is the SQL Server solution for master data management. Master data management (MDM) describes the efforts made by an organization to discover and define non-transactional lists of data, with the goal of compiling maintainable master lists. An MDM project generally includes an evaluation and restructuring of internal business processes along with the implementation of MDM technology. The result of a successful MDM solution is reliable, centralized data that can be analyzed, resulting in better business decisions.
Other Master Data Services features include hierarchies, granular security, transactions, data versioning, and business rules.
Master Data Services includes the following components and tools:
- Master Data Services Configuration Manager, a tool you use to create and configure Master Data Services databases and web applications.
- Master Data Manager, a web application you use to perform administrative tasks (like creating a model or business rule), and that users access to update data.
- MDSModelDeploy.exe, a tool you use to create packages of your model objects and data so you can deploy them to other environments.
- Master Data Services web service, which developers can use to extend or develop custom solutions for Master Data Services.
As a follow-on to the presentation "Building an Effective Data Warehouse Architecture", this presentation will explain exactly what Big Data is and its benefits, including use cases. We will discuss how Hadoop, the cloud and massively parallel processing (MPP) is changing the way data warehouses are being built. We will talk about hybrid architectures that combine on-premise data with data in the cloud as well as relational data and non-relational (unstructured) data. We will look at the benefits of MPP over SMP and how to integrate data from Internet of Things (IoT) devices. You will learn what a modern data warehouse should look like and how the role of a Data Lake and Hadoop fit in. In the end you will have guidance on the best solution for your data warehouse going forward.
Creating a Tabular Model Using SQL Server 2012 Analysis ServicesCode Mastery
At Code Mastery Boston Steve Hughes, Principal Consultant at Magenic, highlights: Basics of SQL Server 2012 Analysis Services, Multidimensional Model, VS PowerPivot, Creating a Tabular Model
A Crash Course in SQL Server Administration for Reluctant Database Administra...Chad Petrovay
Reluctant DBAs are those of us who aren’t formally trained in database administration, but manage through a combination of our wits, technical manuals, and online forums. This practical session will explore best practices for installing, configuring, and maintaining Microsoft SQL Server, and highlight some SQL Server features (and Easter eggs) that can improve your user experience and institutional ROI.
Enabling Data as a Service with the JBoss Enterprise Data Services Platformprajods
This presentation was given at JUDCon 2013, Jan 17,18 at Bangalore. Presented by Prajod Vettiyattil and Gnanaguru Sattanathan. The presentation deals with the Why, What and How of Data Services and Data Services Platforms. It also explains the features of the JBoss Enterprise Data Services Platform.
The need for Data Services is explained with 3 Business use cases:
1. Post purchase customer experience improvement for an Auto manufacturer
2. Enterprise Data Access Layer
3. Data Services for Regulatory Reporting requirements like Dodd Frank
Myth Busters II: BI Tools and Data Virtualization are InterchangeableDenodo
Watch Here: https://bit.ly/2NcqU6F
We take on the 2nd myth about data virtualization and it’s one that suggests a BI tool can substitute a data virtualization software.
You might be thinking: If I can have multi-source queries and define a logical model in my reporting tool, why would I need a data virtualization software?
Reporting tools, no doubt important and necessary, focus on the visualization of data and it’s presentation to the business user. Data virtualization is a governed data access layer designed to connect to and provide transparency of all enterprise data.
Yet the myth suggests that these technologies are interchangeable. So we’re going to take it on!
Watch this webinar as we compare and contrast BI tools and data virtualization to draw a final conclusion.
This session was about Master Data Services and what it also could be used as - the client wanted an application to validate and submit warehouse inventories.
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.
Big Data and BI Tools - BI Reporting for Bay Area Startups User GroupScott Mitchell
This presentation was presented at the July 8th 2014 user group meeting for BI Reporting for Bay Area Start Ups
Content - Creation Infocepts/DWApplications
Presented by: Scott Mitchell - DWApplications
My presentation on the Visual Data Vault modeling language, presented during WWDVC 2014 in St. Albans, VT, USA.
To download the Visio stencils, check out
http://www.doerffler.com/know-how/data-vault/visual-data-vault/
and http://www.visualdatavault.com
Focus op hoe het aanwezig talent op de arbeidsmarkt mobieler en flexibeler kan gemaakt worden (en dit aan de hand van het continu certificeren van competenties & testdata om deze vervolgens flexibel te kunnen delen via bv. Open Badges).
Self service BI with sql server 2008 R2 and microsoft power pivot shortEduardo Castro
In this presentation we summarize BI improvements in SQL Server 2008 R2 and PowerPivot.
Regards,
Dr. Eduardo Castro
http://ecastrom.blogspot.com
http://comunidadwindows.org
Introduction to SQL Server Analysis services 2008Tobias Koprowski
This is my presentation from 17th Polish SQL server User Group Meeting in Wroclaw. It\'s first part of Quadrology Bussiness Intelligence for ITPros Cycle.
Bi For It Professionals Part 3 Building And Querying Multidimensional CubesMicrosoft TechNet
In this session, we will discuss how to build multidimensional cubes using SQL Server Analysis Services from System Center Operations Manager Data Warehouse and then how to use multidimensional expression queries.
What's New with BI in SQL Server Denali (SQL11)Dan English
During this session we are going to go over some of the new BI features that have been enhanced and added in SQL Server "Denali" (SQL11). We will look at new features that have been added into Integration Services, Analysis Services, and Reporting Services. Along with this we will talk about and go over the new report authoring tool "Crescent" showing how this tool will provide you the ability to access, explore, and visualize your data in a whole new way and have fun at the same time.
MAIA Intelligence was invited to give a technical session on MS-SQL at Microsoft Dreamspark Yatra 2012 event in which around 300 budding techies learnt about the emerging technologies
Business Intelligence For It Professionals Part 4 Scorecards Dashboards And...Microsoft TechNet
In this session we will discuss how Office PerformancePoint Server 2007 builds KPI's, scorecards, and dashboards by accessing IT system performance data from the System Center Operations Manager data warehouse.
In this presentation we cover the main features of BI Dashboard with SQL Server 2008 R2.
Regards,
Eduardo Castro Martinez
Microsoft SQL Server MVP
http://ecastrom.blogspot.com
In this presentation we review the main topics about BI Dashboards with SQL Server 2008 R2.
Regards,
Ing. Eduardo Castro
Microsoft SQL Server MVP
http://ecastrom.blogspot.com
http://comunidadwindows.org
So you got a handle on what Big Data is and how you can use it to find business value in your data. Now you need an understanding of the Microsoft products that can be used to create a Big Data solution. Microsoft has many pieces of the puzzle and in this presentation I will show how they fit together. How does Microsoft enhance and add value to Big Data? From collecting data, transforming it, storing it, to visualizing it, I will show you Microsoft’s solutions for every step of the way
Extending the reach of the business application to more users in the organization leads to better data management and better access to information.
After a short intro on Microsoft Dynamics AX you will learn about the new MS Office Add-ins for Microsoft Dynamics AX and discover the mobile capabilities for end users within the travel and expense module.
Learn how to create state-of-the-art, self-service BI solutions for Dynamics AX 2012 using SQL Server 2012 PowerPivot for SharePoint, BISM and Power View.
TDD - Test Driven Dvelopment | Test First DesignQuang Nguyễn Bá
This presentation introduce to you what is TDD, the RGR concept in TDD and what is the benefits of TDD.
This presentation have been created internally for the Software Team in Hyperlogy
Lập kế hoạch dự án Scrum
Làm thế nào để lập kế hoạch cho toàn bộ dự án?
Lập kế hoạch toàn bộ dự án trong TFS 2012
Lập kế hoạch cho một Sprint
Lập kế hoạch cho một Sprint là gì?
Cách lập kế hoạch cho một Sprint trong TFS 2012
Thực hiện một Sprint
Thực hiện một Sprint như thế nào?
Cách thực hiện một Sprint trong TFS 2012
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
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.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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
4. Contents
• Understand the Analysis Services 2008 R2
• Understand the OLAP and OLAP database
• Understand the dimensional OLAP
• Understand the multidimensional data
analysis
• Understand dimensional data warehouse
http://techmaster.vn
5. SQL Server 2008 R2 BI Structure
Reporting and Visualization Tools (Dashboard, KPI,
Presentation Layer
Scorecard,…)
Turn data into information (analysis)
Analytical Layer
Multidimensional OLAP Database
Data Storage and Retrieval Layer Data Warehouse in RDBMS
1. Extract the data from the multiple sources
Data Transformation Layer 2. Modify the data to consistent
3. Load the data into Data Storage system
Data Source Layer Text, MS Excel, MS Access, MS SQL, Oracle,…| External Sources
http://techmaster.vn
6. Microsoft Business Intelligence Platform
Analytic Scorecards, Analytics, Planning
Applications (PerformancePoint Service)
Portal
(SharePoint)
Data Delivery Report Builder End-user Analysis
SSRS (Excel)
Integrate Analyze Report
(SQL Integration Services) (SQL Analysis Services) (SQL Reporting Services)
Infrastructure
Platform Data Warehouse, Data Marts,
Operational Data
(SQL Server 2008 R2)
Office SQL
http://techmaster.vn
7. Analysis Challenges
How Do You Deal With:
Data stored in The cost of developing The costs of
multiple data sources analytical solutions learning new tools
Deploy for today’s
problem but scale ‘Real-Time’ data
over time access
Multiple Users, Diverse analytical Inconsistent data
Multiple Tools needs
http://techmaster.vn
8. Analysis Services 2008 R2
Design Scalable Solutions
Productivity enhancing designers
Scalable Infrastructure
Superior Performance
Extend Beyond OLAP
Unified meta data model
Central KPI manageability
Predictive Analysis
Deliver Pervasive Insight
Optimized Office interoperability
Rich partner extensibility
Open, embeddable architecture
http://techmaster.vn
9. Design Scalable Solutions
Productivity Enhancing Designers
Optimized design experience
Best Practice Design Alerts
Project Lifecycle support
Scalable Infrastructure
Heterogeneous data Integration
Robust Scale-Out Configuration
Advanced Resource Monitoring
User-differentiated perspectives
Superior Performance
Market leading MOLAP Engine
Near real-time data access
Subspace computation optimization
MOLAP enabled write-back
http://techmaster.vn
10. Extend Beyond OLAP
Unified Metadata Model
One consolidated business view
Integrated relational & OLAP analysis
Business information modeling
Time- and financial intelligence
Central KPI Manageability
Server based KPI framework
Centrally managed repository
Pervasive end-user accessibility
Predictive Analytics
Complete data mining framework
Embeddable viewers
Predictive capabilities available to
everyone through Microsoft Office
http://techmaster.vn
11. Predictive Analysis
Bring Data Mining to the Masses through Microsoft Office
Enable easy to use predictive
analysis
At every desktop
For every information worker
Through three powerful add-ins
to Microsoft Office
Predictive capabilities readily
available for business users in Excel
Data mining client for building data
mining models in Excel
Data mining templates for project
visualization in Visio
“What Microsoft has done is to make data mining available on the desktop to
everyone” (David Norris, Associate Analyst, Bloor Research).
http://techmaster.vn
12. Deliver Pervasive Insight
Optimized Office Interoperability
Massive data analysis for everyone with
PowerPivot for Excel 2010
Team Collaboration through PowerPivot for
SharePoint 2010
Corporate performance management
through PerformancePoint Services 2010
Rich Partner Ecosystem Extensibility
Vertically specialized solutions
Packaged applications
API support from all major BI vendors
Open, embeddable architecture
Open API’s and XML/A based protocols
Native web service functionality
Close loop analysis
http://techmaster.vn
13. Office 2010 Integration
Excel 2010
Great cross product investments optimizing
Excel 2010 as analytical client for Analysis
Services
Enhancements around local cubes
Significant performance and functionality
investments
Data Mining Add-Ins for predictive analysis
PowerPivot for massive data analysis on
the desktop
PerformancePoint Services 2010
Great cross product investments for thin
analytic client for Analysis Services
Rich web capabilities for data exploration.
Guided and contextual analysis through
integrated dashboards
Predictive analytics by integrating with SQL
Server Data Mining
http://techmaster.vn
15. What is OLAP
Online Analytical • Benefits
Processing
– Consistently fast response
Online Transaction
Processing 1993. – Metadata-based queries
1985. OLAP – Spreadsheet-style formulas
OLTP
http://techmaster.vn
16. Consistently Fast Response
• Calculating and storing aggregate values and
the results of formulas when a cube is loaded
(calculation in advance)
• Aggregate tables can be created to provide
fast query results
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17. Metadata-Based Queries
SQL Query
• SQL is suitable for SELECT
transaction system [Store].[Store Country].[Canada].[Vancouver]
ON COLUMNS,
not for reporting [Product].[All Products].[Clothing].[Mittens]
applications ON ROWS
FROM [Sales]
• Query language for WHERE ([Measures].[Unit Sales],
[Date].[2010].[February])
OLAP data source MDX Query
– Multidimensional SELECT SUM(Sales.[Unit Sales])
expression
FROM (Sales INNER JOIN Stores
ON Sales.StoreID = Stores.StoreID)
INNER JOIN Products
– MDX ON Sales.ProductID = Products.ProductID
WHERE Stores.StoreCity = 'Vancouver'
AND Products.ProductName = 'Mittens'
AND Sales.SaleDate BETWEEN '01-02-2010' AND
'28-02-2010'
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18. Spreadsheet-Style Formulas
• MDX formulas use named references
– C14/D14 (Spreadsheet) | [Actual]/[Budget] (MDX)
• MDX formulas are easy to manage
• MDX formulas are multidimensional
– Spreadsheet is two dimensional
• MDX formulas take advantage of metadata (its
relationship)
– There is no relationship in cells on the sheet.
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20. Measure and Metadata
• Measure: A summarizable numerical value
– Sales Dollars, Shipment Units,...
• Metadata: Data about data
– Label, Order by,...
Metadata
Units Sold
70 70
Measure
Adventure Works Sales Adventure Works Sales
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21. Unit sold by Product and Month report
Product Jan 2011 Feb 2011 Mar 2011 Apr 2011
Mountain-500 Black, 40 1 3 1 2
Mountain-500 Black, 44 2 1
Mountain-500 Black, 48 1 2 1
Mountain-500 Silver, 40 1 2 1
Mountain-500 Silver, 44 1 1 1
Mountain-500 Silver, 48 2
Road-750 Black, 44 10 7
Road-750 Black, 48 5 9
Hitch Rack 1 6 6 3
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22. Grouping/Aggregating/Attribute/Member
• Grouping – Aggregating: is the
Product Model Color Size way humans deal with too much
Mountain-500 Black, 40 Mountain- Black 40 detail
500
Mountain-500 Black, 44 Mountain- Black 44 – Ex: group Products by model,
500 subcategory, and category groups
Attribute: Product (Key), Model,
Mountain-500 Black, 48 Mountain- Black 48
500 •
Mountain-500 Silver, 40 Mountain- Silver 40
Color, Size
500
Mountain-500 Silver, 44 Mountain- Silver 44
• Member
500
– Model, Mountain-500, Road-
Mountain-500 Silver, 48 Mountain- Silver 48
750…
500
Road-750 Black, 44 Road-750 Black 44 – Color: Black, Silver
Road-750 Black, 48 Road-750 Black 48
Hitch Rack Hitch Rack – Size: 40, 44, 48
Product Attributes
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24. Hierarchy
• Hierarchy is created by
arranging related
attributes into levels
• Hierarchy level: 2, 3,…n
• Hierarchy type:
– Balance (Date)
– Unbalance
(Organization)
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25. Dimensions
Jan Feb Mar Apr
2011 2011 2011 2011
Mountain- 3 8 6 6
500
Road-750 15 16
Hitch Rack 1 6 6 3
Units Sold by Model and Month
• Attribute:
– Model (3)
– Month (4)
• Potential number of values: 12 = 3x4
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26. Dimensions
Jan 2011 Feb 2011 Mar 2011 Apr 2011
Units $ Units $ Units $ Units $
WA Hitch Rack 4 $480 3 $360 2 $240
Mountain- 2 $1.105 6 $3.256 5 $2.775 5 $2.750
500
Road-750 9 $4.860 10 $5.400
OR Hitch Rack 2 $240 3 $360 1 $120
Mountain- 1 $120 2 $1.105 1 $540 1 $540
500
Road-750 1 $565 6 $3.240 6 $3.240
• Attribute:
– State (2), Model (3), Month (4), Measure (2: Units sold, Sales dollars)
• Potential number of values: 2x3x4x2 = 48
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27. Dimensions
• Examples:
– State attribute belongs to the Geography
dimension
– Model attribute belongs to the Product
dimension
– Month attribute belongs to the Date dimension
– Units sold and Sale Dollars belongs to the
Measure dimension
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28. Dimensions
• The independent attributes and hierarchies are the
dimension
• A dimension may contain more than one attributes
– Ex: Product dimension contain Color and Size attribute
• Dimension also contain hierarchies
– Ex: Product by Model hierarchy is composed of attributes
contained in the Product dimension, so the hierarchy also
belongs in the Product dimension
• Measure dimension are displayed on columns
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30. Dimension Data Warehouse
• Dimension Data Warehouse is the data
storage and retrieval layer of BI system
• In dimension data warehouse:
– Dimension are stored in dimension tables
– Measure are called facts and are stored in fact
tables
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31. Fact Table
• Fact table: table that stores the detailed values for measures
• Key Column: State, Product, Month
• Fact Column: UnitsSold, SalesDollars
State Product Month UnitsSol SalesDollar
d s
OR Hitch Rack Jan 2011 1 $120.00
OR Mountain-500 Silver, 40 Jan 2011 1 $565.00
OR Mountain-500 Silver, 48 Jan 2011 1 $552.50
WA Mountain-500 Silver, 48 Jan 2011 1 $552.50
OR Hitch Rack Feb 2011 2 $240.00
WA Hitch Rack Feb 2011 4 $480.00
FactSales table
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32. Fact Table
• The value in the key columns relate the facts
in the fact table row to a row in each
dimension table
• Fact table may have other type of column for
reference purposes
• Fact table might contain one or more
measure columns
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33. Fact Table
• The level of detail stored in a fact table is
called granularity
• The dimensions that a fact table is related to
is called dimensionality of the fact table
• Facts that have different granularity of
different dimensionality must be stored in
separate fact tables
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34. Fact table: Dimension key
• Actually a fact table almost
always uses an integer, called
a dimension key, for each State Product Month UnitsSold SalesDollars
dimension member 1 483 201101 1 120.00
1 591 201101 1 565.00
• There must be a dimension 1 594 201101 1 552.50
table for each dimension key 2 594 201101 1 552.50
in a fact table 1 483 201102 2 240.00
2 483 201102 4 480.00
FactSales table using Dimension key
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35. Dimension Table
• A dimension table contain one row
for each member of the key
attribute of the dimension ProductKey Product
596 Mountain-500 Black, 40
• The key attribute has two column: 598 Mountain-500 Black, 44
599 Mountain-500 Black, 48
– Integer dimension key (PK)
591 Mountain-500 Silver, 40
– Attribute label 593 Mountain-500 Silver, 44
594 Mountain-500 Silver, 48
• A dimension table may contain 604 Road-750 Black, 44
other columns for other attributes 605 Road-750 Black, 48
of the dimension 483 Hitch Rack
DimProduct Dimension Table
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37. Aggregatable and Aggregate
• Aggregatable: Attributes that can be used to create groups
• Non aggregatable attributes are referred to as member
properties
– Ex: List Price, Telephone Number, Street Address…
• Aggregate: Summary value in the group of aggregatable
• Example:
– Aggregatable: Category, Color…
– Aggregate: Number of Units Sold for each Category
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39. Multidimensional OLAP
• Multidimensional OLAP database resides
between the data storage and retrieval layer
and the presentation layer
• It converts the relation data warehouse data
into a fully implemented dimensional model
for creating analytical reports and data
visualizations
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40. Measure Group and Cube
• Measure group corresponds to a single fact table
• Measure group may contains data for single level of detail and
aggregated data for all higher levels of detail
• Cube: Combination of several related measure groups and a
set of dimensions
State Product Date Units Sold Sales Amount
All All All 70 31.305
WA All All 46 21.235
WA Bikes All 37 20.115
WA Road Bikes All 19 10.260
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