This document discusses Microsoft's investments in data warehousing technologies and solutions. It outlines Microsoft's focus on column store, data quality, real-time data warehousing, and advanced analytics. It also describes Microsoft's tier 1 offerings for data warehousing including integrated ETL and reporting tools, simplified management, and predictable performance. Finally, it introduces Fast Track data warehousing reference architectures that provide pre-tested hardware configurations optimized for data warehouse workloads.
Pervasive analytics through data & analytic centricityCloudera, Inc.
Cloudera and Teradata discuss the best-in-class solution enabling companies to put data and analytics at the center of their strategy, achieve the highest forms of agility, while reducing the costs and complexity of their current environment.
Pervasive analytics through data & analytic centricityCloudera, Inc.
Cloudera and Teradata discuss the best-in-class solution enabling companies to put data and analytics at the center of their strategy, achieve the highest forms of agility, while reducing the costs and complexity of their current environment.
Glimpse of advantage, limitations of Hadoop and Goals / Business benefits of Data Warehouse and few use cases where Hadoop can be used to strengthen Enterprise Data Warehouse of any organization.
SQL Server Managing Test Data & Stress Testing January 2011Mark Ginnebaugh
A quick look at some of the available functionality for SQL Server developers who have access to Visual Studio 2010 and SQL-Hero.
With Visual Studio 2010 Premium (and Professional to a degree) delivering similar capabilities to what was available in VS 2008 Database Pro Edition, the ability to generate a mass amount of sample data for your database has only gotten more accessible with time.
Realizing that other tools exist in this space and not all SQL developers use Visual Studio, we’ll also take a look at the third party data generation facility available in SQL-Hero, seeing how we can create thousands (or millions!) of records very quickly using a powerful rules engine, plus automate this process to support continuous integration strategies.
Hybrid Data Warehouse Hadoop ImplementationsDavid Portnoy
Data Warehouse vendors are evolving to incorporate the best Hadoop has to offer. Similarly, the Hadoop ecosystem is growing to include capabilities previously available only to large scale (MPP) DW platforms.
The Future of Data Warehousing: ETL Will Never be the SameCloudera, Inc.
Traditional data warehouse ETL has become too slow, too complicated, and too expensive to address the torrent of new data sources and new analytic approaches needed for decision making. The new ETL environment is already looking drastically different.
In this webinar, Ralph Kimball, founder of the Kimball Group, and Manish Vipani, Vice President and Chief Architect of Enterprise Architecture at Kaiser Permanente will describe how this new ETL environment is actually implemented at Kaiser Permanente. They will describe the successes, the unsolved challenges, and their visions of the future for data warehouse ETL.
Building the Enterprise Data Lake: A look at architecturemark madsen
The topic is building an Enterprise Data Lake, discussing high level data and technology architecture. We will describe the architecture of a data warehouse, how a data lake needs to differ, and show a high level functional and data architecture for a data lake. This webinar will cover:
Why dumping data into Hadoop and letting users get it out doesn't work
The difference between a Hadoop application and a Data Lake
Why new ideas about data architecture are a key element
An Enterprise Data Lake reference architecture to frame what must be built
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.
Reconciling your Enterprise Data Warehouse to Source SystemsMethod360
Implementing and an enterprise BI system is a significant organization investment. Too many times the expected benefit of that investment isn’t realized due to inconsistent data between the organization’s operational and BI systems.
This webcast will explain several options to enable your organization to leverage its investment by providing options to reconcile the data from source operational systems to BI.
Complement Your Existing Data Warehouse with Big Data & HadoopDatameer
To view the full webinar, please go to: http://info.datameer.com/Slideshare-Complement-Your-Existing-EDW-with-Hadoop-OnDemand.html
With 40% yearly growth in data volumes, traditional data warehouses have become increasingly expensive and challenging.
Much of today’s new data sources are unstructured, making the structured data warehouse an unsuitable platform for analyses. As a result, organizations now look at Hadoop as a data platform to complement existing BI data warehouses, and a scalable, flexible and cost-effective solution for data storage and analysis.
Join Datameer and Cloudera in this webinar to discuss how Hadoop and big data analytics can help to:
-Get all the data your business needs quickly into one environment
Shorten the time to insight from months to days
Extend the life of your existing data warehouse investments
Enable your business analysts to ask and answer bigger questions
Business intelligence requirements are changing and business users are moving more and more from historical reporting into predictive analytics in an attempt to get both a better and deeper understanding of their data. Traditionally, building an analytical platform has required an expensive infrastructure and a considerable amount of time for setup and deployment. Here we look at a quick and simple alternative.
Microsoft Data Platform - What's includedJames Serra
The pace of Microsoft product innovation is so fast that even though I spend half my days learning, I struggle to keep up. And as I work with customers I find they are often in the dark about many of the products that we have since they are focused on just keeping what they have running and putting out fires. So, let me cover what products you might have missed in the Microsoft data platform world. Be prepared to discover all the various Microsoft technologies and products for collecting data, transforming it, storing it, and visualizing it. My goal is to help you not only understand each product but understand how they all fit together and there proper use case, allowing you to build the appropriate solution that can incorporate any data in the future no matter the size, frequency, or type. Along the way we will touch on technologies covering NoSQL, Hadoop, and open source.
Understanding Metadata: Why it's essential to your big data solution and how ...Zaloni
In this O'Reilly webcast, Ben Sharma (cofounder and CEO of Zaloni) and Vikram Sreekanti (software engineer in the AMPLab at UC Berkeley) discuss the value of collecting and analyzing metadata, and its potential to impact your big data solution and your business.
Watch the replay here: http://oreil.ly/28LO7IW
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.
This is our general introduction of the DWE; DataWarehouse Explorer; which is the flagship product of CNS for intuitive analytics and standard reporting
Glimpse of advantage, limitations of Hadoop and Goals / Business benefits of Data Warehouse and few use cases where Hadoop can be used to strengthen Enterprise Data Warehouse of any organization.
SQL Server Managing Test Data & Stress Testing January 2011Mark Ginnebaugh
A quick look at some of the available functionality for SQL Server developers who have access to Visual Studio 2010 and SQL-Hero.
With Visual Studio 2010 Premium (and Professional to a degree) delivering similar capabilities to what was available in VS 2008 Database Pro Edition, the ability to generate a mass amount of sample data for your database has only gotten more accessible with time.
Realizing that other tools exist in this space and not all SQL developers use Visual Studio, we’ll also take a look at the third party data generation facility available in SQL-Hero, seeing how we can create thousands (or millions!) of records very quickly using a powerful rules engine, plus automate this process to support continuous integration strategies.
Hybrid Data Warehouse Hadoop ImplementationsDavid Portnoy
Data Warehouse vendors are evolving to incorporate the best Hadoop has to offer. Similarly, the Hadoop ecosystem is growing to include capabilities previously available only to large scale (MPP) DW platforms.
The Future of Data Warehousing: ETL Will Never be the SameCloudera, Inc.
Traditional data warehouse ETL has become too slow, too complicated, and too expensive to address the torrent of new data sources and new analytic approaches needed for decision making. The new ETL environment is already looking drastically different.
In this webinar, Ralph Kimball, founder of the Kimball Group, and Manish Vipani, Vice President and Chief Architect of Enterprise Architecture at Kaiser Permanente will describe how this new ETL environment is actually implemented at Kaiser Permanente. They will describe the successes, the unsolved challenges, and their visions of the future for data warehouse ETL.
Building the Enterprise Data Lake: A look at architecturemark madsen
The topic is building an Enterprise Data Lake, discussing high level data and technology architecture. We will describe the architecture of a data warehouse, how a data lake needs to differ, and show a high level functional and data architecture for a data lake. This webinar will cover:
Why dumping data into Hadoop and letting users get it out doesn't work
The difference between a Hadoop application and a Data Lake
Why new ideas about data architecture are a key element
An Enterprise Data Lake reference architecture to frame what must be built
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.
Reconciling your Enterprise Data Warehouse to Source SystemsMethod360
Implementing and an enterprise BI system is a significant organization investment. Too many times the expected benefit of that investment isn’t realized due to inconsistent data between the organization’s operational and BI systems.
This webcast will explain several options to enable your organization to leverage its investment by providing options to reconcile the data from source operational systems to BI.
Complement Your Existing Data Warehouse with Big Data & HadoopDatameer
To view the full webinar, please go to: http://info.datameer.com/Slideshare-Complement-Your-Existing-EDW-with-Hadoop-OnDemand.html
With 40% yearly growth in data volumes, traditional data warehouses have become increasingly expensive and challenging.
Much of today’s new data sources are unstructured, making the structured data warehouse an unsuitable platform for analyses. As a result, organizations now look at Hadoop as a data platform to complement existing BI data warehouses, and a scalable, flexible and cost-effective solution for data storage and analysis.
Join Datameer and Cloudera in this webinar to discuss how Hadoop and big data analytics can help to:
-Get all the data your business needs quickly into one environment
Shorten the time to insight from months to days
Extend the life of your existing data warehouse investments
Enable your business analysts to ask and answer bigger questions
Business intelligence requirements are changing and business users are moving more and more from historical reporting into predictive analytics in an attempt to get both a better and deeper understanding of their data. Traditionally, building an analytical platform has required an expensive infrastructure and a considerable amount of time for setup and deployment. Here we look at a quick and simple alternative.
Microsoft Data Platform - What's includedJames Serra
The pace of Microsoft product innovation is so fast that even though I spend half my days learning, I struggle to keep up. And as I work with customers I find they are often in the dark about many of the products that we have since they are focused on just keeping what they have running and putting out fires. So, let me cover what products you might have missed in the Microsoft data platform world. Be prepared to discover all the various Microsoft technologies and products for collecting data, transforming it, storing it, and visualizing it. My goal is to help you not only understand each product but understand how they all fit together and there proper use case, allowing you to build the appropriate solution that can incorporate any data in the future no matter the size, frequency, or type. Along the way we will touch on technologies covering NoSQL, Hadoop, and open source.
Understanding Metadata: Why it's essential to your big data solution and how ...Zaloni
In this O'Reilly webcast, Ben Sharma (cofounder and CEO of Zaloni) and Vikram Sreekanti (software engineer in the AMPLab at UC Berkeley) discuss the value of collecting and analyzing metadata, and its potential to impact your big data solution and your business.
Watch the replay here: http://oreil.ly/28LO7IW
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.
This is our general introduction of the DWE; DataWarehouse Explorer; which is the flagship product of CNS for intuitive analytics and standard reporting
Designing high performance datawarehouseUday Kothari
Just when the world of “Data 1.0” showed some signs of maturing; the “Outside In” driven demands seem to have already initiated some the disruptive changes to the data landscape. Parallel growth in volume, velocity and variety of data coupled with incessant war on finding newer insights and value from data has posed a Big Question: Is Your Data Warehouse Relevant?
In short, the surrounding changes happening real time is the new “Data 2.0”. It is characterized by feeding the ever hungry minds with sharper insights whether it is related to regulation, finance, corporate action, risk management or purely aimed at improving operational efficiencies. The source in this new “Data 2.0” has to be commensurate to the outside in demands from customers, regulators, stakeholders and business users; and hence, you would need a high relformance (relevance + performance) data warehouse which will be relevant to your business eco-system and will have the power to scale exponentially.
We starts this webinar by giving the audiences a sneak preview of what happened in the Data 1.0 world & which characteristics are shaping the new Data 2.0 world. It then delves deep on the challenges that growing data volumes have posed to the Data warehouse teams. It also presents the audiences some of the practical and proven methodologies to address these performance challenges. Finally, in the end it will highlight some of the thought provoking ways to turbo charge your data warehouse related initiatives by leveraging some of the newer technologies like Hadoop. Overall, the webinar will educate audiences with building high performance and relevant data warehouses which is capable of meeting the newer demands while significantly driving down the total cost of ownership.
Take your reports to the next dimension! In this session we will discuss how to combine the power of SSRS and SSAS to create cube driven reports. We will talk about using SSAS as a data source, writing MDX queries, using report parameters, passing parameters for drill down reports, performance tuning, and the pro’s and con’s of using a cube as your data source.
Jeff Prom is a Senior Consultant with Magenic Technologies. He holds a bachelor’s degree, three SQL Server certifications, and is an active PASS member. Jeff has been working in the IT industry for over 14 years and currently specializes in data and business intelligence.
Data Warehouse Design and Best PracticesIvo Andreev
A data warehouse is a database designed for query and analysis rather than for transaction processing. An appropriate design leads to scalable, balanced and flexible architecture that is capable to meet both present and long-term future needs. This session covers a comparison of the main data warehouse architectures together with best practices for the logical and physical design that support staging, load and querying.
Got data?… now what? An introduction to modern data platformsJamesAnderson599331
What are Data Analytics Platforms? What decision points are necessary in creating a modern, unified analytics data platform? What benefits are there to building your analytics data platform on Google Cloud Platform? Susan Pierce walks us through it all.
Embarking on building a modern data warehouse in the cloud can be an overwhelming experience due to the sheer number of products that can be used, especially when the use cases for many products overlap others. In this talk I will cover the use cases of many of the Microsoft products that you can use when building a modern data warehouse, broken down into four areas: ingest, store, prep, and model & serve. It’s a complicated story that I will try to simplify, giving blunt opinions of when to use what products and the pros/cons of each.
Exploring the Wider World of Big Data- Vasalis KapsalisNetAppUK
Every second of every day you hear about Electronic systems creating ever increasing quantities of data. Systems in markets such as finance, media, healthcare, government and scientific research feature strongly in the Big Data processing conversation. While extracting business value from Big Data is forecast to bring customer and competitive advantage and benefits. In this session hear Vas Kapsalis, NetApp Big Data Business Development Manager, discuss his views and experience on the wider world of Big Data.
The Most Trusted In-Memory database in the world- AltibaseAltibase
Life is a database. How you manage data defines business. ALTIBASE HDB with its Hybrid architecture combines the extreme speed of an In-Memory Database with the storage capacity of an On-Disk Database’ in a single unified engine.
ALTIBASE® HDB™ is the only Hybrid DBMS in the industry that combines an in-memory DBMS with an on-disk DBMS, with a single uniform interface, enabling real-time access to large volumes of data, while simplifying and revolutionizing data processing. ALTIBASE XDB is the world’s fastest in-memory DBMS, featuring unprecedented high performance, and supports SQL-99 standard for wide applicability.
Altibase is provider of In-Memory data solutions for real-time access, analysis and distribution of high volumes of data in mission-critical environments.
Please visit our website (www.altibase.com) to learn more about our products and read more about our case studies. Or contact us at info@altibase.com. We look forward to helping you!
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
Bring Your SAP and Enterprise Data to Hadoop, Kafka, and the CloudDataWorks Summit
The world’s largest enterprises run their infrastructure on Oracle, DB2 and SQL and their critical business operations on SAP applications. Organisations need this data to be available in real-time to conduct necessary analytics. However, delivering this heterogeneous data at the speed it’s required can be a huge challenge because of the complex underlying data models and structures and legacy manual processes which are prone to errors and delays.
Unlock these silos of data and enable the new advanced analytics platforms by attending this session.
Find out how to:
• To overcome common challenges faced by enterprises trying to access their SAP data
• You can integrate SAP data in real-time with change data capture (CDC) technology
• Organisations are using Attunity Replicate for SAP to stream SAP data in to Kafka
Speakers:
John Hol, Regional Director, Attunity
Mike Hollobon, Director Business Development, IBT
Choosing technologies for a big data solution in the cloudJames Serra
Has your company been building data warehouses for years using SQL Server? And are you now tasked with creating or moving your data warehouse to the cloud and modernizing it to support “Big Data”? What technologies and tools should use? That is what this presentation will help you answer. First we will cover what questions to ask concerning data (type, size, frequency), reporting, performance needs, on-prem vs cloud, staff technology skills, OSS requirements, cost, and MDM needs. Then we will show you common big data architecture solutions and help you to answer questions such as: Where do I store the data? Should I use a data lake? Do I still need a cube? What about Hadoop/NoSQL? Do I need the power of MPP? Should I build a "logical data warehouse"? What is this lambda architecture? Can I use Hadoop for my DW? Finally, we’ll show some architectures of real-world customer big data solutions. Come to this session to get started down the path to making the proper technology choices in moving to the cloud.
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...DATAVERSITY
Thirty years is a long time for a technology foundation to be as active as relational databases. Are their replacements here?
In this webinar, we look at this foundational technology for modern Data Management and show how it evolved to meet the workloads of today, as well as when other platforms make sense for enterprise data.
Building Analytic Apps for SaaS: “Analytics as a Service”Amazon Web Services
TIBCO Jaspersoft® for AWS is a business intelligence suite that helps you deliver stunning interactive reports and dashboards inside your app that make it easy for your customers to get answers. Purpose-built for AWS, our reporting and analytics server quickly and easily connects to Amazon Relational Database Service (RDS), Amazon Redshift, and Amazon EMR. It includes ad-hoc reporting, dashboards, data analysis, data visualization, and data blending. In less than 10 minutes, you can be analyzing and reporting on your data. You get a full Cloud BI server starting at less than $1/hour, with no user or data limits and no additional fees.
This webinar deck shows how embeddable analytics with TIBCO Jaspersoft for AWS gives you the power to create the experience your end users demand and how to scale and manage that experience across your customer base with AWS.
Introduction to microsoft sql server 2008 r2Eduardo Castro
In this presentation we review the new features in SQL 2008 R2.
Regards,
Ing. Eduardo Castro Martinez, PhD
http://comunidadwindows.org
http://ecastrom.blogspot.com
Data lakes are central repositories that store large volumes of structured, unstructured, and semi-structured data. They are ideal for machine learning use cases and support SQL-based access and programmatic distributed data processing frameworks. Data lakes can store data in the same format as its source systems or transform it before storing it. They support native streaming and are best suited for storing raw data without an intended use case. Data quality and governance practices are crucial to avoid a data swamp. Data lakes enable end-users to leverage insights for improved business performance and enable advanced analytics.
Building the Perfect SharePoint 2010 Farm - SPS SacramentoMichael Noel
Slide deck from Michael Noel's session on Best Practices SharePoint 2010 infrastructure, as presented at SharePoint Saturday Sacramento, 18 June, 2011.
Similar to Next gen bi and datawarehouse solutions ross lo forte (20)
Next gen bi and datawarehouse solutions ross lo forte
1. Next Generation BI and Data Warehouse Solutions Ross LoForte SQL Technology Architect Microsoft Technology Centers
2. Data Warehouse Industry Trends Microsoft has steadily invested in the most important data warehouse technologies Column Store Data Quality Real-Time DW and Streaming Data Advanced Analytics Key Trends MPP MDM Secure and Robust MPP(Parallel Data Warehouse) Master Data Services Database Security StreamInsight (Streaming Data) Data Quality (Zoomix) Column Store (Project Apollo)
3. Microsoft’s on-going investments in Data Warehousing Futures 2008 2005 10s of TB Warehouses Parallel partitioning Data compression New Reference Architectures Policy Based Admin. DB Resource Governance High Perf. Connectors(Oracle, Teradata, SAP BW) Data Profiling Policy based auditing Data Warehouse Scale Multi TB Warehouses Enterprise scalability DW Reference Architectures Unified manageability Enterprise class ETL tool Data Cleansing(Fuzzy lookup/matching) Data Protection & Tracing PB Warehouses >64 Core Processing Scale out through MPP Perf. Management Tools BI Resource Governance Improved Predictability Mixed workload support Continuous Loading Master Data Management(Stratature Integration) Integrated DQ Services (Zoomix) Rights Management Data Warehouse Management Heterogeneous Connectivity & Workloads Data Integrity & Quality Compliance & Security
5. Tier 1 offerings Tier 1 Services and Support Microsoft Data Warehousing solutions
6. Tier 1 offerings Microsoft Data Warehousing solutions Integrated ETL and Reporting tools Simplified management Predictable response Lower storage costs Integrated Master Data Management tool
7. Tier 1 offerings Microsoft Data Warehousing solutions All features and benefits of SQL Server 2008 R2 Enterprise Ability to scale up to 256 logical processors Ability to scale memory beyond 2TB Continuous loading using StreamInsight
8. Tier 1 offerings Microsoft Data Warehousing solutions Balanced solution for scan-centric workloads Best price-to-performance ratio Features 12 reference architectures validated by Microsoft Ability to scale up to 80 terabytes
9. Some Data Warehouses Today Big SAN Big SMP Server Connected together Server can consume 32 GB/Sec of IO, but SAN can only deliver 12 GB/Sec Queries are slow Despite significant investment in both Server and Storage
10. Challenges of traditionalData Warehouse IO Channel Sequential IO capacity of storage System CPU 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 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010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 010101010101010101011101101011101010110101010101010101010110111101010101101101011010110101 CPU Constraint CPU IO Channel Sequential IO capacity of storage System Storage System Constraint Sequential IO capacity of storage System CPU IO Channel IO Channel constraint
11. What is Fast Track Data Warehouse? A methodfor designing a cost-effective, balanced system for Data Warehouse workloads Reference hardware configurationsdeveloped in conjunction with hardware partners using this method Bestpracticesfor data layout, loading and management Relational Database Only – Not SSAS, IS, RS
16. Scale Out or Up within limits of Server and SANOLTP Applications
17. Reference architectures boost performance and reduce risk HP Fast Track data warehouse configurations scale from SMB to Enterprise Prescriptive guidance and optimized methodology for data warehouse query workloads with large sequential data reads Balanced hardware approach ideal for data marts or small to mid-sized DW with scan-centric workloads Supports 1 to 80TB Data Warehouse at leading price/performance Configurations, tested performance guidance and best practices for deploying/operating/managing Packaged and custom support Entry1-5TB DL370 w/D2700 DAS Basic6 – 12TBDL38x w/MSA P2000 Mainstream12 – 24TBDL585 w/MSA P2000 Mainstream16 – 32 TB DL580 w/MSA P2000 Premium24 – 80 TBDL980 w/MSA P2000
19. Tier 1 offerings Microsoft Data Warehousing solutions Enterprise Data Warehouse Appliance offering High Scalability and performance Flexibility and choice Integrated with Microsoft BI
20. Parallel Data WarehouseAn appliance experience All hardware from a single vendor Orderable at the rack level Vendor will: Assemble appliances Image appliances with OS, SQL Server, and PDW software Appliance installed in 1 – 2 days Support: Microsoft provides first call support Hardware partner provides onsite break/fix support
21. Control Rack Data Rack Compute Nodes Storage Nodes SQL SQL SQL SQL SQL SQL SQL SQL SQL SQL SQL Control Nodes Active / Passive Management Node Dual Fiber Channel Dual Infiniband Landing Zone Backup node Spare Compute Node
23. Admin Console – Home Page Menu options listed left to right by PDW activity and status.
24. Admin Console – Appliance State Appliance State tab lists the state of all active nodes within the appliance.
25. Admin Console – Dashboard Customizations Can optionally include up to 38 available performance counters. …
26. Admin Console – Dashboard The Dashboard tab provides near real-time performance counters.
27. Distributed Data Warehouse Architecture Each business unit has own Data Marts More responsive to business needs Fits budget realities Hub provides centralized data governance etc. Node-to-node data movement Parallel over Infiniband >500GB per min Parallel Database Export (PDE) 23
47. Use Reports to Drive Decisions Create and share reports Maintain a single version of truth with your Excel Workbooks Drive decision based on facts
48. Use Dashboards to Drive Decisions Visual displays of information needed to achieve one or more objectives Single-Screen display of information Answer fundamental questions Alerts the user to issues or problems Span Operational, Performance, Personal Align strategies and organizational goals Measure and manage Key Performance Indicators (KPI) Modeled after the business, not the data
49. Use PowerPivot to Drive Self-Services PowerPivotfor Excel PowerPivotfor SharePoint 29
50. Microsoft Business Decision Appliance End-to-end, pre-configured stack quickly enables BI for Excel power users Rich insight: Empower users to easily create PowerPivot workbooks from real-time business data for faster, more accurate insights Reduced complexity: Overcome cost and complexity of BI; shift IT resources from running ad-hoc reports to innovation initiatives Easy manageability: Custom code for management dashboard and scripted data source integration ease deployment and simplify administration
51. Microsoft Data Warehouse Vision Make SQL Server the fastest and most affordable database for customers of all sizes Complete Data Warehouse Solution Flexibility and Choice Massive Scalability at a Low Cost Simplified Data Warehouse Management
This chart, taken from the TDWI Next Generation Data Warehouse Platforms report, shows data warehouse features and techniques plotted for delta (growth) and plan to use (commitment).As you’ll see in the rest of this presentation, Microsoft’s strategy for data warehousing aligns extremely well with the features and techniques that have broadcommitment and good growth. The ticks show specific technology areas Microsoft is strategically investing in.
Introduction to Microsoft DW solutions training in resources
Changed slide with animation
The Fast Track Data Warehouse reduces time, cost, and unknowns of selecting and configuring hardware for SQL Server data warehouses based on HP’s success in SQL Server deployments. In fact, HP is the #1 platform for SQL Server Fast Track deployments.The reference architecture supports a continuum of performance and scalability, up to 48 TB,at industry leading price/performance. These pre-integrated, pre-optimized solutions eliminate the need for second-touch customization at a configuration center for faster deployment and lower costs.Components include:2-8P HP servers, either HP ProLiant DL38x, DL58x, or DL785 serversHP Storage Works P2000 MSA storageHP networkingMicrosoft SQL Server Enterprise EditionWe will soon be introducing a new “entry-level” configuration that dramatically simplifies deployment of small data warehouses on a cost-effective, compact form factor for lower TCO.And the entire solution is surrounded with expert installation and support services from HP and Microsoft to provide a seamless experience and low-risk installation and operation.
Problems illustrated in the detail rows include a link to the Alerts page.
Your customization selections persist until you log out (or close) the Admin Console session.
Displays a very animated view of PDW activity.Silverlight is required
Point of the Slide: Here is the solution, show some detail on how we think of the BI architecture in 3 main layers. Point out that self-service analysis takes place in Office and SharePoint, but the Business Intelligence Platform is there to take popular user-generated solutions and convert them into full organizational solutions.Prove that our better together (Microsoft BI) story is real! Flow of the Slide: A trusted BI platform is critical for a business intelligence solution to work today. If we’re going to achieve the promise of BI, we need to have the confidence and trust in the data, we need to know where it came from, and that it is both timely and reliable for us to use to make a decision. That’s where the power of an integrated BI platform like SQL Server comes into play.Once you have the data ready to use, the middle tier comes into play, where business users actually interact with the data and turn it into something that is useful to them to make the right decision. The numbers that we pull from other systems are just that—we need applications and content to turn them into actionable items—and that’s where the middle tier comes into play. Finally, we need the right tools and applications to ensure that we can use that data in the way we want to in order to make our decisions. Applications and tools that range from personal, to team, to organizational and corporate tools, all with a familiar look and feel, all integrated and working with my Operating system, email, Internet search function. And this is what the power of integration through Microsoft Office brings you. From the Office productivity tools like Excel, through to the team and collaboration tools of SharePoint. By integrating BI seamlessly into a broader business productivity suite that includes search, collaboration, unified communications, and content management, we offer the end user a much richer experience.
Point of the Slide: Here is the solution, show some detail on how we think of the BI architecture in 3 main layers. Point out that self-service analysis takes place in Office and SharePoint, but the Business Intelligence Platform is there to take popular user-generated solutions and convert them into full organizational solutions.Prove that our better together (Microsoft BI) story is real! Flow of the Slide: A trusted BI platform is critical for a business intelligence solution to work today. If we’re going to achieve the promise of BI, we need to have the confidence and trust in the data, we need to know where it came from, and that it is both timely and reliable for us to use to make a decision. That’s where the power of an integrated BI platform like SQL Server comes into play.Once you have the data ready to use, the middle tier comes into play, where business users actually interact with the data and turn it into something that is useful to them to make the right decision. The numbers that we pull from other systems are just that—we need applications and content to turn them into actionable items—and that’s where the middle tier comes into play. Finally, we need the right tools and applications to ensure that we can use that data in the way we want to in order to make our decisions. Applications and tools that range from personal, to team, to organizational and corporate tools, all with a familiar look and feel, all integrated and working with my Operating system, email, Internet search function. And this is what the power of integration through Microsoft Office brings you. From the Office productivity tools like Excel, through to the team and collaboration tools of SharePoint. By integrating BI seamlessly into a broader business productivity suite that includes search, collaboration, unified communications, and content management, we offer the end user a much richer experience.
Point of the Slide: Here is the solution, show some detail on how we think of the BI architecture in 3 main layers. Point out that self-service analysis takes place in Office and SharePoint, but the Business Intelligence Platform is there to take popular user-generated solutions and convert them into full organizational solutions.Prove that our better together (Microsoft BI) story is real! Flow of the Slide: A trusted BI platform is critical for a business intelligence solution to work today. If we’re going to achieve the promise of BI, we need to have the confidence and trust in the data, we need to know where it came from, and that it is both timely and reliable for us to use to make a decision. That’s where the power of an integrated BI platform like SQL Server comes into play.Once you have the data ready to use, the middle tier comes into play, where business users actually interact with the data and turn it into something that is useful to them to make the right decision. The numbers that we pull from other systems are just that—we need applications and content to turn them into actionable items—and that’s where the middle tier comes into play. Finally, we need the right tools and applications to ensure that we can use that data in the way we want to in order to make our decisions. Applications and tools that range from personal, to team, to organizational and corporate tools, all with a familiar look and feel, all integrated and working with my Operating system, email, Internet search function. And this is what the power of integration through Microsoft Office brings you. From the Office productivity tools like Excel, through to the team and collaboration tools of SharePoint. By integrating BI seamlessly into a broader business productivity suite that includes search, collaboration, unified communications, and content management, we offer the end user a much richer experience.
Point of slide: To introduce PowerPivot for Excel and SharePoint.Script:The revolutionary PowerPivot technology includes both an Excel add-in and server-based technology that integrates with SharePoint. This allows your users to quickly manipulate very large data sets and share analysis with co-workers—with little or no IT assistance. PowerPivot supports the unmatched analytical power and ease-of-use of Excel while allowing users to connect to any data source—databases, reports, data feeds, Web pages, Excel files, and more. After performing analysis, you can publish it to SharePoint 2010, further enabling collaboration with others. These capabilities provide a single version of truth for all users. IT also benefits from the managed self-service capabilities within PowerPivot. IT can now create reports using SQL Server Reporting Services R2 and SharePoint 2010 andtrack the usage of PowerPivot applications and discover mission-critical Excel applications. Conclusion: PowerPivot is the key to managed self-service BI and empowering end users. PowerPivotenables seamless and secure sharing and collaboration on user-generated BI solutions, while helping IT organizations increase efficiency through the PowerPivot Management Dashboard.
Here is the product specs, HW and SW configuration for your reference. I will not spend time on this. You can read the deck later.
The Microsoft vision is to make SQL Server the fastest, simplest and most affordable database management system for data warehouse customers of all sizes. In 2008, Microsoft acquired DATAllegro and its MPP appliance that is now Parallel Data Warehouse. Its shared nothing architecture delivers enterprise-class performance and scales for the most demanding data warehouses. Microsoft investments in complementary technologies will significantly improve data warehouse performance and scalability. Microsoft aims to simplify IT for customers through innovation. Since its inception, SQL Server has proudly followed this tradition by simplifying the creation and deployment of databases. Microsoft is committed to building the most easily managed data warehouses through manageability improvements in the software and continuous investment in Reference Architectures and data warehouse appliances. Future appliances from Microsoft will dramatically simplify the deployment and management of a broader range data warehouses. Microsoft is committed to offering the lowest cost solutions for data warehouse customers of any size and achieves this through:The most competitive pricing across its data warehouse offerings (Fast Track Data Warehouse starts at under $11,000 per terabyte; Parallel Data Warehouse starts at under $20,000 per terabyte). Providing a complete Enterprise Data Warehouse and BI toolkit, including SQL Server Analysis Services, Reporting Services, Master Data Services, PowerPivot, and StreamInsight (in the R2 release, customers get all of these tools with the database at no extra cost).Hardware choice with a wide range of hardware platforms that helps customers avoid vendor lock-in and reduce their hardware acquisition and maintenance costs.The use of industry-standard hardware instead of proprietary components.