Teradata is a global leader in data warehousing and analytics. It provides a range of products including data warehouse appliances, an enterprise data warehouse, and database technology. Teradata's solutions leverage the latest technology and are optimized for performance, flexibility, and integrated analytics to deliver insights faster.
Working with informtiaca teradata parallel transporterAnjaneyulu Gunti
It explains how to move data between PowerCenter and Teradata databases. It explains when to use Teradata relational connection and TPT connection. This article also lists issues we might encounter when loading data to or unloading data from Teradata and the workarounds for these issues.
Working with informtiaca teradata parallel transporterAnjaneyulu Gunti
It explains how to move data between PowerCenter and Teradata databases. It explains when to use Teradata relational connection and TPT connection. This article also lists issues we might encounter when loading data to or unloading data from Teradata and the workarounds for these issues.
The process of data warehousing is undergoing rapidtransformation, giving rise to various new terminologies, especially due to theshift from the traditional ETL to the new ELT. Forsomeone new to the process, these additional terminologies and abbreviationsmight seem overwhelming, some may even ask, “Why does it matter if the L comesbefore the T?”
The answer lies in the infrastructure and the setup. Here iswhat the fuss is all about, the sequencing of the words and more importantly,why you should be shifting from ETL to ELT.
En esta sesión revisamos las nuevas mejoras y funcionalidades que estarán implementadas en la siguiente versión de SQL Server principalmente en Seguridad, Rendimiento y Alta Disponibilidad
No matter which system you choose, data migration usually is the nominal fun part when you are shifting to a new management system. Nevertheless, by preparing your team and cleansing your data, your organization can achieve a more aerodynamic, less nerve-racking data migration process.
Data Warehouse:
A physical repository where relational data are specially organized to provide enterprise-wide, cleansed data in a standardized format.
Reconciled data: detailed, current data intended to be the single, authoritative source for all decision support.
Extraction:
The Extract step covers the data extraction from the source system and makes it accessible for further processing. The main objective of the extract step is to retrieve all the required data from the source system with as little resources as possible.
Data Transformation:
Data transformation is the component of data reconcilation that converts data from the format of the source operational systems to the format of enterprise data warehouse.
Data Loading:
During the load step, it is necessary to ensure that the load is performed correctly and with as little resources as possible. The target of the Load process is often a database. In order to make the load process efficient, it is helpful to disable any constraints and indexes before the load and enable them back only after the load completes. The referential integrity needs to be maintained by ETL tool to ensure consistency.
Organization now trying to make themselves much more operational with easy-to-interoperate data.
Data is most important part of any organization.
Data is backbone of any report and reports are the baseline on which all the vital management decisions are taken.
Data coexist in different maybe heterogeneous data sources.
Overview of Intel Data Center Manager
Why do we care about Data Center Management
Storage and Networking Support
What can you do with DCM
Go to Market Options
Case Studies
DataStax Enterprise 4.6, the fastest, most scalable distributed database now integrates Apache Spark analytics on streaming data while providing enterprise-grade backup and restore capabilities to safeguard critical and distributed customer information.
Join established database expert and DataStax's VP of Products, Robin Schumacher, as he explores new capabilities in DataStax Enterprise 4.6 including security enhancements, analytics on streaming data and increased performance for modern web, mobile and IoT applications. Robin will discuss how the new OpsCenter 5.1 makes backup and restore processes push-button simple with the option of restoring critical data to and from the cloud taking the burden off database administrators.
Watch to learn how
- Faster and easier analytics with Spark SQL and Spark Streaming and simplified search make it easy to build scalable fault-tolerant streaming applications
- Enhanced server security with LDAP and Active Directory integration for easier external security management
- An automated high availability option allows a secondary OpsCenter service to take over, should a failure occur so your maintenance operations are always running
The process of data warehousing is undergoing rapidtransformation, giving rise to various new terminologies, especially due to theshift from the traditional ETL to the new ELT. Forsomeone new to the process, these additional terminologies and abbreviationsmight seem overwhelming, some may even ask, “Why does it matter if the L comesbefore the T?”
The answer lies in the infrastructure and the setup. Here iswhat the fuss is all about, the sequencing of the words and more importantly,why you should be shifting from ETL to ELT.
En esta sesión revisamos las nuevas mejoras y funcionalidades que estarán implementadas en la siguiente versión de SQL Server principalmente en Seguridad, Rendimiento y Alta Disponibilidad
No matter which system you choose, data migration usually is the nominal fun part when you are shifting to a new management system. Nevertheless, by preparing your team and cleansing your data, your organization can achieve a more aerodynamic, less nerve-racking data migration process.
Data Warehouse:
A physical repository where relational data are specially organized to provide enterprise-wide, cleansed data in a standardized format.
Reconciled data: detailed, current data intended to be the single, authoritative source for all decision support.
Extraction:
The Extract step covers the data extraction from the source system and makes it accessible for further processing. The main objective of the extract step is to retrieve all the required data from the source system with as little resources as possible.
Data Transformation:
Data transformation is the component of data reconcilation that converts data from the format of the source operational systems to the format of enterprise data warehouse.
Data Loading:
During the load step, it is necessary to ensure that the load is performed correctly and with as little resources as possible. The target of the Load process is often a database. In order to make the load process efficient, it is helpful to disable any constraints and indexes before the load and enable them back only after the load completes. The referential integrity needs to be maintained by ETL tool to ensure consistency.
Organization now trying to make themselves much more operational with easy-to-interoperate data.
Data is most important part of any organization.
Data is backbone of any report and reports are the baseline on which all the vital management decisions are taken.
Data coexist in different maybe heterogeneous data sources.
Overview of Intel Data Center Manager
Why do we care about Data Center Management
Storage and Networking Support
What can you do with DCM
Go to Market Options
Case Studies
DataStax Enterprise 4.6, the fastest, most scalable distributed database now integrates Apache Spark analytics on streaming data while providing enterprise-grade backup and restore capabilities to safeguard critical and distributed customer information.
Join established database expert and DataStax's VP of Products, Robin Schumacher, as he explores new capabilities in DataStax Enterprise 4.6 including security enhancements, analytics on streaming data and increased performance for modern web, mobile and IoT applications. Robin will discuss how the new OpsCenter 5.1 makes backup and restore processes push-button simple with the option of restoring critical data to and from the cloud taking the burden off database administrators.
Watch to learn how
- Faster and easier analytics with Spark SQL and Spark Streaming and simplified search make it easy to build scalable fault-tolerant streaming applications
- Enhanced server security with LDAP and Active Directory integration for easier external security management
- An automated high availability option allows a secondary OpsCenter service to take over, should a failure occur so your maintenance operations are always running
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.
We have embraced Cloud and Open-Source further enabling the analytics ecosystems by creating new integration capabilities at scale.
Simplifying technology footprints to make it easier to buy
Bringing scale to analytics
Oracle Big Data Appliance and Big Data SQL for advanced analyticsjdijcks
Overview presentation showing Oracle Big Data Appliance and Oracle Big Data SQL in combination with why this really matters. Big Data SQL brings you the unique ability to analyze data across the entire spectrum of system, NoSQL, Hadoop and Oracle Database.
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.
FSI201 FINRA’s Managed Data Lake – Next Gen Analytics in the CloudAmazon Web Services
FINRA’s Data Lake unlocks the value in its data to accelerate analytics and machine learning at scale. FINRA's Technology group has changed its customer's relationship with data by creating a Managed Data Lake that enables discovery on Petabytes of capital markets data, while saving time and money over traditional analytics solutions. FINRA’s Managed Data Lake includes a centralized data catalog and separates storage from compute, allowing users to query from petabytes of data in seconds. Learn how FINRA uses Spot instances and services such as Amazon S3, Amazon EMR, Amazon Redshift, and AWS Lambda to provide the 'right tool for the right job' at each step in the data processing pipeline. All of this is done while meeting FINRA’s security and compliance responsibilities as a financial regulator.
Teradata - Presentation at Hortonworks Booth - Strata 2014Hortonworks
Hortonworks and Teradata have partnered to provide a clear path to Big Analytics via stable and reliable Hadoop for the enterprise. The Teradata® Portfolio for Hadoop is a flexible offering of products and services for customers to integrate Hadoop into their data architecture while taking advantage of the world-class service and support Teradata provides.
DataLakes kan skalere i takt med skyen, nedbryde integrationsbarrierer og data gemt i siloer og bane vejen for nye forretningsmuligheder. Det er alt sammen med til at give et bedre beslutningsgrundlag for ledelse og medarbejdere. Kom og hør hvordan.
David Bojsen, Arkitekt, Microsoft
“A Distributed Operational and Informational Technological Stack” Stratio
By Loreto Fernández Costas and Adrián Doncel Gabaldó.
Digital Transformation starts with data. What if a solution existed that put data at the center, in a single place, serving all applications around it – A distributed data centric solution that combined the operational and the informational, managed by a single data center operating system?
This session will provide a detailed explanation of such a solution, bringing the concept of data centricity to life. We will cover the details of the array of open source technologies that come together to create a transformational solution to the historic problem of physical companies: From multiple data stores, distributed run-time engines and SQL engines based on Spark, to microservices, Machine Learning and Deep Learning Algorithms. Big Data 3.0 is just round the corner.
Similar to Teradata Technology Leadership and Innovation (20)
How to Use Algorithms to Scale Digital BusinessTeradata
Gartner defines digital business as the creation of new business designs by blurring the digital and physical worlds. Digital business creates new business opportunities, but the amount of data generated will eclipse the human ability to process it. Further, many complex decisions will need to be made in timeframes, and at scales, that are impossible by human actors. Gartner analyst Chet Geschickter will explain share advice on how to leverage algorithmic business principles to drive digital business success.
Humans are sentient. We perceive. We feel. We listen. The problem is the more you put together, the more we lose these capabilities. We get slower. The idea is, how we create a company that acts like a single organism, where we identify opportunities, and that allows us to work in a faster and exponential world world where development happens in months rather than years. Don't let digital transformation become a war of competitive attrition. You may need to invest in your future to change the game.
Teradata Listener™: Radically Simplify Big Data StreamingTeradata
Teradata Listener™ is an intelligent, self-service solution for ingesting and distributing extremely fast moving data streams throughout the analytical ecosystem. Listener
is designed to be the primary ingestion framework for organizations with multiple data streams. Listener reliably delivers data without loss and provides low-latency ingestion for near real-time applications.
Telematics data provides a wealth of new, actionable insights, particularly when integrated with other enterprise data. But where do you start? How do you prioritize? What is the roadmap? In an interactive workshop learn how to derive more from data so you can do more in your business.
- Find the value of integrating telematics data with traditional data elements, including financial, customer, manufacturing, location and weather data
- How integrated telematics data can improve customer satisfaction, lifecycle management, warranty reserves, supply chain performance, and even engineering & design choices
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The Tools You Need to Build Relationships and Drive Revenue Checklist Teradata
This Campaign Manager Leadership series paper provides a checklist for marketers when considering blending offline data with online data to improve the customer experience.
Right Message, Right Time: The Secrets to Scaling Email Success Teradata
This Campaign Manager Leadership Series ebook outlines the 4 keys to an automated email marketing strategy and how marketers can scale to meet these “always-on” customer expectations.
BSI Teradata: The Shocking Case of Home Electronics PlanetTeradata
Home Electronics Planet, a big-box retailer, has digital marketing campaigns that are failing. Their Chief Marketing Officer gets some analytics and data science help from Business Scenario Investigators who recommend changing their search keywords mix, creating tighter customer segments based on product purchase sequencing coupled with real-time web page personalizations, and revising their e-mail marketing to improve business results.
How we did it: BSI: Teradata Case of the Tainted LasagnaTeradata
Great Brands, a major food producer, faces yet another recall. The government is pointing at Turkey Broccoli Lasagna as the culprit, so the Chief Risk Officer and Chief Supply Chain officer bring in BSI investigators to help them build a better/faster track and trace system, using Big Data analytics.
To see more BSI: Teradata, go to http://www.facebook.com/bsiTeradata
Teradata BSI: Case of the Retail Turnaround Teradata
This set of Powerpoint slides describes the analytics work of Teradata: Business Scenario Investigation employees who help move Taylor & Swift, a big-box retailer, from a silo’d stores vs. web approach to an integrated Omni-Channel Retailing approach to customers, marketing, and sales. The team comes up with 5 ideas, 2 of which are tried out. The story illustrates the use Teradata, Aster, Aprimo, and Tableau as tools to glean faster and deeper analytical insights on Big Data, specifically web walks.
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
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The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
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LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
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Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
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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:
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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:
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Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
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Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
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So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
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Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
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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/
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While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
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1. Insights into SAP testing best practices
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4. Demo
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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).
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Bob Boule
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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.
3. Teradata Leadership and Innovation The Best Database for Analytics Leverage unmatched performance, scalability, and manageability Architectural Flexibility Meet your requirements with any architecture, price point, and data model Integrated Analytics Discover smarter insights faster using superior in-database and analytical processes Superior Operational Execution Drive faster front line actions with better, more relevant insights
4. Teradata Leadership and Innovation The Best Database for Analytics Leverage unmatched performance, scalability, and manageability Architectural Flexibility Meet your requirements with any architecture, price point, and data model Integrated Analytics Discover smarter insights faster using superior in-database and analytical processes Superior Operational Execution Drive faster front line actions with better, more relevant insights
5. Teradata – The Clear Data Warehousing Leader Leadership in Execution and Vision Ability to Execute Completeness of Vision Gartner Magic Quadrant for Data Warehouse DBMS, 2010 The Magic Quadrant is copyrighted 28 January 2011 by Gartner, Inc. and is reused with permission. The Magic Quadrant is a graphical representation of a marketplace at and for a specific time period. It depicts Gartner's analysis of how certain vendors measure against criteria for that marketplace, as defined by Gartner. Gartner does not endorse any vendor, product or service depicted in the Magic Quadrant, and does not advise technology users to select only those vendors placed in the "Leaders" quadrant. The Magic Quadrant is intended solely as a research tool, and is not meant to be a specific guide to action. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
8. Teradata Database – Powerfully Simple Adaptable Software Solution vs. Hardware Brute Force “ Set and Go” options reduce full file scanning (Primary, Secondary, Multi-level Partitioned Primary, Aggregate Join Index, Sync Scan) Workload management options by user, application, Threshold and Filters In-database data mining, virtual OLAP/cubes, pre-built and custom application objects (User Defined Functions) drive efficient and differentiated business insight Fully parallel MPP “shared nothing” architecture scales linearly across data, users, and applications providing consistent and predictable performance and growth DBAs never have to set parameters, manage table space, or reorganize data Simple set up steps with automatic “hands off” distribution of data, along with integrated load utilities result in rapid installations “ Parallel Everything” design and smart Teradata Optimizer enables fast query execution across platforms Powerful, Embedded Analytics Easy “ Set & G0” Optimization Options Advanced Workload Management Intelligent Scan Elimination Simple to Manage Responsive to Business Change Quick Time to Value Fast Query Performance Automatic Built-In Functionality
9. Teradata Leadership and Innovation The Best Database for Analytics Leverage unmatched performance, scalability, and manageability Architectural Flexibility Meet your requirements with any architecture, price point, and data model Integrated Analytics Discover smarter insights faster using superior in-database and analytical processes Superior Operational Execution Drive faster front line actions with better, more relevant insights
10. Teradata Purpose-Built Platform Family Data Mart Appliance Extreme Data Appliance Data Warehouse Appliance Extreme Performance Appliance Active Enterprise Data Warehouse Purpose Test/ Development or Smaller Data Marts Analytics on Extreme Data Volumes from New Data Types Data Warehouse or Departmental Data Marts Extreme Performance for Operational Analytics Enterprise Scale for Strategic and Operational Intelligence EDW/ADW Scalability Up to 12TB Up to 186PB Up to 343TB Up to 17TB Up to 92PB Sub Segment Departmental Analytics, Entry-level EDW Analytical Archive, Deep Dive Analytics Strategic Intelligence, Decision Support System, Fast Scan Operational Intelligence, Lower Volume, High Performance Active Workloads, Real-Time Update, Tactical and Strategic response times
11. Teradata Software/Enterprise Analytics Cloud Teradata Data Mart Edition Teradata Express Teradata Express for Public Cloud Teradata Express for Private Cloud Teradata Agile Analytic Cloud Purpose Test/ Development or Smaller Data Marts Express for Windows Express for Amazon EC2 Cloud Express for VMWare Player Private Cloud for building elastic data marts Scalability Up to 6TB Up to 10GB Up to 1TB Up to 1TB Flexible Sub Segment Departmental Analytics, Entry-level EDW, deploy in production Free – Used for Customer Evaluation, Testing and Development Subscribe to Amazon EC2 Service – Free from Teradata. Used for Customer Evaluation, Testing and Development Free – Used for Customer Evaluation, Testing and Development Deploy Analytic Sandboxes inside Teradata Data Warehouse using Teradata Elastic Mart Builder
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18. Teradata Data Warehouse Appliance 2650 *Can configure in 3-node increments Single Operational View Across Complete System System Management SUSE Linux Operating System RAID 1 Disk Mirroring, Node Failover with Cliquing, BAR Availability Scales up to 343TB with 2TB drives Scalability Teradata BYNET ® 17.6TB Per Cabinet – 300GB 35.2TB Per Cabinet – 600GB 68.6TB Per Cabinet – 2TB (0% Compression) (216) 300GB or 600GB SAS per Cabinet (108) 2TB SAS drives per Cabinet Nine nodes per cabinet with Dual Intel Westmere Six Core Xeon Processors Total User Data Capacity *Nodes Interconnect Storage
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21. Teradata Extreme Data Appliance 1650 * Available in Half Cabinet Configurations Single Operational View Across Complete System System Management SUSE Linux Operating System RAID 1 Disk Mirroring, Optional Fallback Data Protection and Cliquing, BAR Availability Scales to 186 PB with 2 TB drives Scalability Teradata BYNET ® 91TB Per Cabinet (0% Compression) (144) 1 or 2TB SAS Drives per Cabinet Two Nodes Per Cabinet with Dual Intel Westmere Six Core Xeon Processors Total User Data Capacity *Nodes Interconnect Storage
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24. Teradata Analytical Ecosystem Overview DATA SOURCES BAR DATA MARTS ARCHIVAL BAR DATA WAREHOUSE DUAL SYSTEMS DATA LAB TEST/DEV INDEPENDENT DATA MART ADMIN BUSINESS USER
25. Trusted Advisor on Your Architecture With Teradata It’s Your Choice 3 rd Normal Form Teradata is the only database that does not lock you into a sub-optimal enterprise approach to data architecture, but supports a cross-section of approaches to address all analytical requirements Cloud Enterprise Data Warehouse Data Marts Star Schema Active Data Warehouse ™ Sand Boxes Hub & Spoke
26. Teradata Leadership and Innovation The Best Database for Analytics Leverage unmatched performance, scalability, and manageability Architectural Flexibility Meet your requirements with any architecture, price point, and data model Integrated Analytics Discover smarter insights faster using superior in-database and analytical processes Superior Operational Execution Drive faster front line actions with better, more relevant insights
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28. Teradata Integrated Analytics Teradata Purpose-Built Platform Family Advanced Analytics Temporal OLAP Optimization Geospatial Big Data Teradata Database Application Development Teradata Open Parallel Framework Custom Services Embedded Services Virtual Machines Agile Analytics Data Exploration Quantitative Analyst Mobile BI GIS Business Users Executives Frontline workers Users Teradata Integrated Analytics Extreme Performance Appliance Active Enterprise Data Warehouse Data Warehouse Appliance Extreme Data Appliance Data Mart Appliance
29. Teradata Integrated Analytics Tools and techniques to accelerate development of analytics Native temporal support to manage and update time dimension In-database data labs to accelerate exploration of new data and ideas Optimized in-database data mining technology from leading vendors, open source and Teradata Native database geospatial data types and analytics Build-in multi-dimensional analytics optimization Partner tools that converts unstructured into structured data for integration and analysis Visual data exploration to quickly understand and analyze data within the database Advanced Analytics Temporal OLAP Optimization Geospatial Big Data Teradata Database Application Development Teradata Open Parallel Framework Agile Analytics Data Exploration Custom Services Embedded Services Virtual Machines Teradata Purpose-Built Platform Family Extreme Performance Appliance Active Enterprise Data Warehouse Data Warehouse Appliance Extreme Data Appliance Data Mart Appliance Teradata Integrated Analytics
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31. Teradata Leadership and Innovation The Best Database for Analytics Leverage unmatched performance, scalability, and manageability Architectural Flexibility Meet your requirements with any architecture, price point, and data model Integrated Analytics Discover smarter insights faster using superior in-database and analytical processes Superior Operational Execution Drive faster front line actions with better, more relevant insights
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33. Active Enterprise Intelligence™ An Obvious Trend: More Speed, More Users Days Seconds 1,000’s to 1,000,000s of “Front Line” Operational Decisions 100’s of Corporate “Knowledge Workers” Operational Intelligence Strategic Intelligence
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35. Active Enterprise Intelligence™ An Obvious Trend: More Speed, More Users Days Seconds EDW Enterprise Integration SOA, BPMS, IDEs Portals/composite applications Mixed workload management Enterprise Data Warehouse BI Tools & reports Analysis & visualization Predictive Analytics Operational Intelligence Strategic Intelligence
36. STRATEGIC INTELLIGENCE Active Enterprise Intelligence™ INSIGHTS ACTION OPERATIONAL INTELLIGENCE Insights Into Action Results Intelligence Respond Assess Sense Plan Report Analyze Predict
37. Teradata Leadership and Innovation Staying Ahead of the Competition The Best Database for Analytics Leverage unmatched performance, scalability, and manageability Architectural Flexibility Meet your requirements with any architecture, price point, and data model Integrated Analytics Discover smarter insights faster using superior in-database and analytical processes Superior Operational Execution Drive faster front line actions with better, more relevant insights