eMetrics SF 2011 - Integrating Analytics and Testing at Delljoel_wright
Presentation from eMetrics SF 2011: Joel Wright, Global Analytics Manager, and Charles Hua, Global Testing Manager explain the concepts and processes that Dell uses to manage the testing pipeline/roadmap planning and execution to ensure high quality tests, learnings, and actionable outcomes.
Framework for creating Analytics that delivers cost effective Value. From what to output, to how to scale and motivate a team, passing through data acquisition. Analytics has become a critical asset for the most competitive organizations; practitioners must ensure their ability to create and communicate insight, especially the most senior decision-makers is effective and efficient.
Slides from a recent Big Data Warehousing Meetup titled, Big Data Analytics with Microsoft.
See Power Pivot/ Power Query/ Power View/ Power Maps and Azure Machine Learning be used to analyze Big Data.
One challenge of dealing with Big Data project is to acquire both structured and instructed information in order to find the right correlation. During the event, we explained all the steps to build your model and enhance your existing data through Microsoft's Power BI.
We had an in-depth discussion about the innovations built into the latest stack of Microsoft Business Intelligence, and practical tips from Technology Specialist’s from Microsoft.
The session also featured demos to help you see the technology as an end-to-end solution.
For more information, visit www.casertaconcepts.com
MT101 Dell OCIO: Delivering data and analytics in real timeDell EMC World
Today’s business operations increasingly rely on sophisticated integration of data streaming across the enterprise. This requires an analytics ecosystem that is highly current and highly available. This session explores the infrastructure and methods Dell IT used for keeping the complex flows, integration processes, BI, and analytics operating 24x7.
Linkedin Analytics Week 11 MKT 9715 baruch mba program Prof Marshall SponderMarshall Sponder
This LinkedIn Analytics presentation is part of my MBA class at Baruch College that I teach on Monday nights -- MKT 9715 - I will also be teaching the undergrad class next semester as well as the graduate class.
eMetrics SF 2011 - Integrating Analytics and Testing at Delljoel_wright
Presentation from eMetrics SF 2011: Joel Wright, Global Analytics Manager, and Charles Hua, Global Testing Manager explain the concepts and processes that Dell uses to manage the testing pipeline/roadmap planning and execution to ensure high quality tests, learnings, and actionable outcomes.
Framework for creating Analytics that delivers cost effective Value. From what to output, to how to scale and motivate a team, passing through data acquisition. Analytics has become a critical asset for the most competitive organizations; practitioners must ensure their ability to create and communicate insight, especially the most senior decision-makers is effective and efficient.
Slides from a recent Big Data Warehousing Meetup titled, Big Data Analytics with Microsoft.
See Power Pivot/ Power Query/ Power View/ Power Maps and Azure Machine Learning be used to analyze Big Data.
One challenge of dealing with Big Data project is to acquire both structured and instructed information in order to find the right correlation. During the event, we explained all the steps to build your model and enhance your existing data through Microsoft's Power BI.
We had an in-depth discussion about the innovations built into the latest stack of Microsoft Business Intelligence, and practical tips from Technology Specialist’s from Microsoft.
The session also featured demos to help you see the technology as an end-to-end solution.
For more information, visit www.casertaconcepts.com
MT101 Dell OCIO: Delivering data and analytics in real timeDell EMC World
Today’s business operations increasingly rely on sophisticated integration of data streaming across the enterprise. This requires an analytics ecosystem that is highly current and highly available. This session explores the infrastructure and methods Dell IT used for keeping the complex flows, integration processes, BI, and analytics operating 24x7.
Linkedin Analytics Week 11 MKT 9715 baruch mba program Prof Marshall SponderMarshall Sponder
This LinkedIn Analytics presentation is part of my MBA class at Baruch College that I teach on Monday nights -- MKT 9715 - I will also be teaching the undergrad class next semester as well as the graduate class.
This presentation provides a brief insight into the need to undertake an analytics project, particularly as it pertains to claims management and fraud. To this end the presentation will touch on the general challenges confronting the property and casualty insurance industry, as well as the challenges and lessons learnt from early adopters of business intelligence. In the face of these challenges analytics holds the potential to generate substantial value as evidenced by several short case study examples. The presentation concludes with a look at the issue of fraud as it pertains to the industry and some of the metrics that are influenced by it.
The presentation draws extensively, and focuses on, the work and viewpoints from industry participants including; Accenture, IBM, Ernst & Young, Strategy Meets Action, Ordnance Survey, Gartner, Insurance Institute of America, American Institute for Chartered Property Casualty Underwriters, International Risk Management Institute and John Standish Consulting. References are included on each slide as well as on the “References” slides at the end of the presentation.
The Analytics Value Chain - Key to Delivering Business Value in IoTPeter Nguyen
In the IoT, new analytics approaches are needed to handle the time critical nature of IoT challenges.
The first step in designing a new approach is to simplify the process by integrating all the data for an IoT application. That includes all the structured, unstructured, and semi-structured data in your organization.
The second key step in the streamlining process is to unify the analytics layer.
This includes historical analytics (descriptive & diagnostic), real-time streaming analytics, predictive analytics, and prescriptive analytics.
The approach to analytics outlined above is a good first step for IoT. However, it is the ability to execute analytics in real-time across the analytics value chain (streaming, historical, predictive, and prescriptive analytics) with relevant contextual and situational data that addresses the critical “last mile” for timely outcomes.
Then this must be combined with the ability to take the next best action in any particular scenario to create the greatest value.
Big Data Real Time Analytics - A Facebook Case StudyNati Shalom
Building Your Own Facebook Real Time Analytics System with Cassandra and GigaSpaces.
Facebook's real time analytics system is a good reference for those looking to build their real time analytics system for big data.
The first part covers the lessons from Facebook's experience and the reason they chose HBase over Cassandra.
In the second part of the session, we learn how we can build our own Real Time Analytics system, achieve better performance, gain real business insights, and business analytics on our big data, and make the deployment and scaling significantly simpler using the new version of Cassandra and GigaSpaces Cloudify.
This particular project is based on ratio analysis of Coca-Cola International. I have analyzed two years financial performance of Coke i.e. from 2011 to 2012. I hope my this effort will help other interested students.
Product Camp Austin 26 - Technology organizations continue to lag behind other critical business functions in moving to a product-led mindset for defining high-value work. Many have made the jump too agile for managing work, but still rely on outdated methods to prioritize and align with key corporate initiatives. Joey will speak about tools and techniques to use when establishing a product mindset within traditional IT organizations, how to educate business partners on partnering for successful product definitions and what organizational structures best enable this shift. Come to learn more about moving traditional IT organizations to product-led teams.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
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
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
This presentation provides a brief insight into the need to undertake an analytics project, particularly as it pertains to claims management and fraud. To this end the presentation will touch on the general challenges confronting the property and casualty insurance industry, as well as the challenges and lessons learnt from early adopters of business intelligence. In the face of these challenges analytics holds the potential to generate substantial value as evidenced by several short case study examples. The presentation concludes with a look at the issue of fraud as it pertains to the industry and some of the metrics that are influenced by it.
The presentation draws extensively, and focuses on, the work and viewpoints from industry participants including; Accenture, IBM, Ernst & Young, Strategy Meets Action, Ordnance Survey, Gartner, Insurance Institute of America, American Institute for Chartered Property Casualty Underwriters, International Risk Management Institute and John Standish Consulting. References are included on each slide as well as on the “References” slides at the end of the presentation.
The Analytics Value Chain - Key to Delivering Business Value in IoTPeter Nguyen
In the IoT, new analytics approaches are needed to handle the time critical nature of IoT challenges.
The first step in designing a new approach is to simplify the process by integrating all the data for an IoT application. That includes all the structured, unstructured, and semi-structured data in your organization.
The second key step in the streamlining process is to unify the analytics layer.
This includes historical analytics (descriptive & diagnostic), real-time streaming analytics, predictive analytics, and prescriptive analytics.
The approach to analytics outlined above is a good first step for IoT. However, it is the ability to execute analytics in real-time across the analytics value chain (streaming, historical, predictive, and prescriptive analytics) with relevant contextual and situational data that addresses the critical “last mile” for timely outcomes.
Then this must be combined with the ability to take the next best action in any particular scenario to create the greatest value.
Big Data Real Time Analytics - A Facebook Case StudyNati Shalom
Building Your Own Facebook Real Time Analytics System with Cassandra and GigaSpaces.
Facebook's real time analytics system is a good reference for those looking to build their real time analytics system for big data.
The first part covers the lessons from Facebook's experience and the reason they chose HBase over Cassandra.
In the second part of the session, we learn how we can build our own Real Time Analytics system, achieve better performance, gain real business insights, and business analytics on our big data, and make the deployment and scaling significantly simpler using the new version of Cassandra and GigaSpaces Cloudify.
This particular project is based on ratio analysis of Coca-Cola International. I have analyzed two years financial performance of Coke i.e. from 2011 to 2012. I hope my this effort will help other interested students.
Product Camp Austin 26 - Technology organizations continue to lag behind other critical business functions in moving to a product-led mindset for defining high-value work. Many have made the jump too agile for managing work, but still rely on outdated methods to prioritize and align with key corporate initiatives. Joey will speak about tools and techniques to use when establishing a product mindset within traditional IT organizations, how to educate business partners on partnering for successful product definitions and what organizational structures best enable this shift. Come to learn more about moving traditional IT organizations to product-led teams.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
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
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
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The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
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We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
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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.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
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My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Climate Impact of Software Testing at Nordic Testing Days
Kitenga - Enabling Insight Through Analytics
1. Kitenga Analytic Suite
Enabling insight through analytics
Written by Author Joey Jablonski, Director of Product Management, Kitenga Analytics, Dell, Inc.
Abstract
Organizations today have a lot of data. To make the most
of it, they need the right tools—tools that can be deployed
rapidly and that make it easy for both IT staff and less technical
employees to turn that data into information meaningful to
the business. This tech brief explores analytics and introduces
several powerful tools that make it easy for you to rapidly
deploy a powerful analytical environment in your organization.
Introduction
Today, companies focus greater and greater resources to
ensure they are able to respond to changing market conditions,
customer preferences and competitive threats in a timely
manner. Today’s analytic technologies enable companies to
respond to these changes faster and more effectively.
Analytics is about transforming data into meaningful that
decisions makers can use to make appropriate changes to
how they operate the business and respond to the market.
Analytics is a collection of technologies that align with business
needs and enable deep visibility into corporate data assets,
while allowing iterative feedback to re-create reports based on
needs, questions and market conditions.
Kitenga Analytics Suite from Dell Software is an advanced
analytics toolkit that brings together natural language
processing, machine learning, search and advanced
visualization, connected by an integrated workbench meant for
non-developer staff. Kitenga is a business enabling technology
to provide access to big data to more staff who are closer to
the business and the decision-making process.
How analytics can help organizations like yours
Exactly how can analytics benefit organizations today? Let’s
look at two examples of how analytics can help organizations
improve their operations and their bottom lines.
2. 2
Healthcare organizations can provide
better care by analyzing patient data.
Every time a patient arrives at a
medical facility, an intake assessment is
completed. This assessment includes a
variety of standard questions, such as the
reason for the visit, symptoms, previous
visits and current medications. This
assessment enables the medical provider
to quickly determine the severity level
and the appropriate place within the
facility to route the patient.
With the right tools, though, intake
assessments can be even more useful.
By automatically comparing the current
patient to previous patient populations
and discerning patterns, the healthcare
facility could improve patient care, and
the organization’s bottom line.
Kitenga enables these proactive, advanced
analytics. It automatically analyzes patient
data and provides recommendations
to medical staff based on patterns that
may not be obvious at the time of initial
consultation with the patient.
Financial services organizations can
better assess transactions and risk by
performing contract valuation.
Companies that buy and sell baskets
of contracts (such as mortgages and
insurance policies) must complete a
due diligence process to review those
contracts for errors and discrepancies,
and to price and model the risk
associated with them. The pricing
and financial default models for these
baskets of contracts are often assumed
but not verified, despite the risk of these
complex transactions.
Kitenga can compare both structured
and unstructured data, enabling
organizations to review large groups
of contracts and access external
information (such as credit scores,
payment history and banking
information) for validation when
assessing a complex transaction.
Kitenga Analytics Suite delivers the
advanced analytics organizations
need today.
Today’s business problems require the
integrated analysis of a multitude of data
types, from a variety of sources. Kitenga
enables users to analyze, compare and
report on unstructured, semi-structured
and structured data from the same tool,
using the same algorithms, without
accounting for the data type or source.
This single source enables analysts to
quickly find meaning in complex data
sets and make decisions about the best
course for the business.
Core technologies
Kitenga contains four core technologies,
integrated for use from a single
workbench, and flexible in the workflow
required by the data analyst:
• Natural language processing (NLP)—
Kitenga can extract meaning from raw
text, including information about people
and places, as well as relationships
between entities.
• Machine learning (ML)—Kitenga has the
ability to “learn” from a given data set
and be trained over time to increase
the accuracy of sentiment grouping,
relationships and visualizations.
Figure 1. Dell’s solutions enable business users—not just IT staff—to access, analyze
and understand data.
Kitenga enables
users to analyze,
compare and report
on unstructured,
semi-structured and
structured data—all
from the same tool,
without accounting
for the data type
or source.
Integration
Boomi / Toad
Curation
Hadoop
Understanding
Kitenga
Share:
3. 3
• Visualization—Kitenga has the ability to
visualize the data that was extracted during
the NLP and ML phases of data analysis.
• Search—Search has become a powerful
enabling technology for accessing large,
complex information sets. Kitenga’s
advanced search capabilities enable users
to mine piles of data, and then presents not
only results that match the search query,
but also related data that the users may not
have initially thought to search for.
Kitenga enables non-technical staff
members to analyze complex data sets.
Kitenga’s intuitive interface enables a
broad range of staff to interact with and
analyze complex data sets that were
previously limited to software developers
and IT departments. Some common
users of Kitenga include:
• Medical researcher—Medical researchers
commonly review complex data sets to
identify patterns that were not previously
known so that processes can be modified
to improve patient care.
• Business analyst—Business analysts can
creating advanced analysis jobs and view
the results in a visualizing interface. Kitenga
makes it easy for them to take an iterative
approach, refining the data as understating
increases and data volumes grow.
• Data scientist—Data scientists can create
reusable analytics modules, called
extractors, to execute algorithms and
iterate over the results using Kitenga’s self-
service portal.
• Product manager—Product managers can
pull together separate data sets into a single
analysis to compare product information,
sentiment and market conditions to plan
new products, consider changes and
anticipate market conditions.
• Legal researcher—Legal researchers can
identify relationships across large, complex
data sets and narrow the set of documents
that must be manually reviewed by staff,
ensuring a higher success rate over manual
document reviews.
Kitenga’s intuitive
interface
enables non-IT
staff—including
researchers,
analysts, data
scientists and
product managers—
to interact with and
analyze complex
data sets.
Figure 2. Kitenga combines four core technologies, integrated for use from a
single workbench.
Search Visualization
KitengaTM
Machine
learning
Natural
language
processing
Share:
4. 4
Dell delivers complete analytics
solutions, as well as components
that integrate with your existing
environment.
Analytics requires not only data analysis
but effective presentation and interaction.
Analytics is more than just a single
application; it is a presentation and
interaction layer that empowers users,
powered by a strong data integration
layer and infrastructure. All components
must be rapid to deploy and must
operate together to provide flexibility as
business needs change.
With Dell, you can rapidly deploy a
powerful analytical environment Dell
offers complete analytical solutions,
as well as components for integration
with existing environments to ensure
maximum flexibility when deploying
analytical environments (see Figure 3).
We have already reviewed the key
capabilities of Kitenga. Let’s look at
some of the other Dell solutions that
help organizations perform effective
data analysis.
Toad for Hadoop
In data analytics projects, most of the
time is spent doing data integration—
that is, most of the project is spent
simply getting data into and out of
Hadoop. Toad for Hadoop enables
staff to quickly develop processes to
ingest data into Hadoop and format
it in a way that advanced tools,
including Kitenga, can analyze and
visualize. Toad for Hadoop allows for
a set of diverse connectors between a
Hadoop Distributed File System (HDFS)
environment and traditional databases,
including MySQL, Microsoft SQL Server
and DB2, along with a growing list of
other data sources and targets.
Shareplex
Shareplex is a high performance
solution for connecting Oracle database
environments to HDFS to enable bi-
directional data movement. Shareplex
enables administrators to replicate Oracle
redo logs into a Hadoop environment for
advanced analysis, recovery and efficient
data storage and archiving.
Dell | Cloudera Solution for
Apache Hadoop
The Dell | Cloudera Solution, shown
in Figure 4, delivers all the hardware,
software, resources and services
needed to run Hadoop in a production
environment. This end-to-end solution
enables you to be in production with
Hadoop in a shorter time than is typically
possible with homegrown solutions. By
listening to its customers, Dell designed
a Hadoop solution that is unique in
the marketplace, combining optimized
hardware, software and services to
streamline deployment and improve
customer experience.
Figure 3. Dell provides the components you need to create a powerful
analytics environment.
In a data analytics
project, a great
deal of time is
often spent simply
getting data into
and out of Hadoop.
Toad for Hadoop
makes it quick and
easy to put data
into Hadoop and
format it for use by
advanced tools
like Kitenga.
Advanced Analytics & Visualization (Kitenga)
Business Intelligence (Toad Intelligence Central)
Data Integration (Toad for Hadoop, SharePlex)
Structured Unstructured (Cloudera)
Advanced Analytics & Visualization (Kitenga)
Share:
5. 5
The Dell | Cloudera Solution is based on
the Cloudera Enterprise distribution of
Hadoop, including CDH4. Cloudera has
created a quality-controlled distribution
of Hadoop and offers commercial
management software, updates, support
and consulting services.
The server platform for the Dell
| Cloudera Solution is the Dell
PowerEdge™ C or R series. Dell
PowerEdge servers are focused on
hyperscale and cloud capabilities.
Rather than emphasizing gigahertz
and gigabytes, these servers deliver
maximum density, memory and
serviceability while minimizing total cost
of ownership.
Dell’s solution includes components that
that span the entire solution stack:
• Reference architecture and best practices
• Optimized server configurations for
PowerEdge R and PowerEdge C Series
• Optimized network infrastructure based on
Dell Force10 S4810 and S60 devices
• Dell Crowbar software framework for
deployment and management at scale.
• Cloudera CDH Enterprise software
• Hadoop infrastructure management tools
• Monitoring with Ganglia and Nagios
Conclusion
Analytics turn data into insight that
empowers organizations to make better
decisions. Dell delivers unsurpassed
visibility into complex data sets, enabling
you to identify patterns and discover
relationships, and then iteratively review
and understand the data. With Dell’s
unique analytic capabilities, you can build
an environment with a single analytic
tool chain across your unstructured,
semi-structured and structured data,
giving staff across the organization the
information they need to improve the
organization’s bottom line.
To learn more about Dell’s big
data solutions, contact your Dell
representative or visit www.quest.com/
kitenga-analytics-suite/.
Figure 4. The Dell | Cloudera Solution
The Dell | Cloudera
Solution delivers
all the hardware,
software, resources
and services needed
to run Hadoop
in a production
environment, so
you can be up and
running quickly.
Share: