1. The document discusses Pentaho's approach to big data analytics using a component-based data integration and visualization platform.
2. The platform allows business analysts and data scientists to prepare and analyze big data without advanced technical skills.
3. It provides a visual interface for building reusable data pipelines that can be run locally or deployed to Hadoop for analytics on large datasets.
Pentaho - Jake Cornelius - Hadoop World 2010Cloudera, Inc.
Putting Analytics in Big Data Analytics
Jake Cornelius
Director of Product Management, Pentaho Corporation
Learn more @ http://www.cloudera.com/hadoop/
Webinar | Using Hadoop Analytics to Gain a Big Data AdvantageCloudera, Inc.
Learn about:
Why big data matters to your business: realize revenue, increase customer loyalty, and pinpoint effective strategies
The business and technical challenges of big data solutions
How to leverage big data for competitive advantage
The “must haves” of an effective big data solution
Real-world examples of Cloudera, Pentaho and Dell big data solutions in action
Pentaho - Jake Cornelius - Hadoop World 2010Cloudera, Inc.
Putting Analytics in Big Data Analytics
Jake Cornelius
Director of Product Management, Pentaho Corporation
Learn more @ http://www.cloudera.com/hadoop/
Webinar | Using Hadoop Analytics to Gain a Big Data AdvantageCloudera, Inc.
Learn about:
Why big data matters to your business: realize revenue, increase customer loyalty, and pinpoint effective strategies
The business and technical challenges of big data solutions
How to leverage big data for competitive advantage
The “must haves” of an effective big data solution
Real-world examples of Cloudera, Pentaho and Dell big data solutions in action
30 for 30: Quick Start Your Pentaho EvaluationPentaho
These slides are from our recent 30 for 30 webinar tailored towards people that have downloaded the Pentaho evaluation and want to know more about all the data integration and business analytics components part of the trial, how to easily integrate data, and best practices for installing/developing content.
Check out this presentation from Pentaho and ESRG to learn why product managers should understand Big Data and hear about real-life products that have been elevated with these innovative technologies.
Learn more in the brief that inspired the presentation, Product Innovation with Big Data: http://www.pentaho.com/resources/whitepaper/product-innovation-big-data
Expand a Data warehouse with Hadoop and Big Datajdijcks
After investing years in the data warehouse, are you now supposed to start over? Nope. This session discusses how to leverage Hadoop and big data technologies to augment the data warehouse with new data, new capabilities and new business models.
Oracle Big Data Discovery working together with Cloudera Hadoop is the fastest way to ingest and understand data. Powerful data transformation capabilities mean that data can quickly be prepared for consumption by the extended organisation.
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014Pentaho
Bo Borland presentation at MongoDB World in NYC, June 24, 2014. Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyze Disparate Data in a Single MongoDB View
Syncsort, Tableau, & Cloudera present: Break the Barriers to Big Data InsightPrecisely
Demand for quicker access to multiple integrated sources of data continues to rise. Immediate access to data stored in a variety of systems - such as mainframes, data warehouses, and data marts - to mine visually for business intelligence is the competitive differentiation enterprises need to win in today’s economy.
Stop playing the waiting game and learn about a new end-to-end solution for combining, analyzing, and visualizing data from practically any source in your enterprise environment.
Leading organizations are already taking advantage of this architectural innovation to gain modern insights while reducing costs and propelling their businesses ahead of the competition.
Are you tired of waiting? Don't let your architecture hold you back. Access this webinar and hear from a team of industry experts on how you can Break the Barriers to Big Data Insight.
With the advent of Big Data in the Threat Analytics space needs emerge to perform near real-time (NRT) threat detection and automated interpretation that speed counter measures and remediation. AT&T Chief Security Organization (CSO) has developed an enterprise architecture that includes near real-time outlier processes necessary to protect its network from cyber threats using the Hadoop ecosystem. One enterprise challenge that CSO has faced is summarized in the statement by Brian Rexroad, Executive Director of Technology and Security: "I feel there is too much emphasis is on "detecting". Significantly more emphasis is needed in automated extraction of related information/activity and interpretation of that information." Therefore; CSO Engineering team developed the Stratum™ architecture that includes many open source and commercial products facilitating the rapid development and operationalization of outliner detectors and interpreters. Extensive use of NRT data ingestion, enrichment, organization and random access storage patterns, make these capabilities possible on top of a Hadoop based ecosystem. The Stratum™ architecture offers the CSO the ability to minimize the time and effects of many cyber threats. Using Big Data technologies for cyber threat analysis is becoming quite common, but the need for outlier detection and interpretation is crucial for enterprise protection.
Oracle's BigData solutions consist of a number of new products and solutions to support customers looking to gain maximum business value from data sets such as weblogs, social media feeds, smart meters, sensors and other devices that generate massive volumes of data (commonly defined as ‘Big Data’) that isn’t readily accessible in enterprise data warehouses and business intelligence applications today.
Syncsort, Tableau, & Cloudera present: Break the Barriers to Big Data InsightSteven Totman
Demand for quicker access to multiple integrated sources of data continues to rise. Immediate access to data stored in a variety of systems - such as mainframes, data warehouses, and data marts - to mine visually for business intelligence is the competitive differentiation enterprises need to win in today’s economy.
Stop playing the waiting game and learn about a new end-to-end solution for combining, analyzing, and visualizing data from practically any source in your enterprise environment.
Leading organizations are already taking advantage of this architectural innovation to gain modern insights while reducing costs and propelling their businesses ahead of the competition.
Are you tired of waiting? Don't let your architecture hold you back. Access this webinar and hear from a team of industry experts on how you can Break the Barriers to Big Data Insight.
Explore how data integration (or “mashups”) can maximize analytic value and help business teams create streamlined data pipelines that enables ad-hoc analytic inquiries. You’ll learn why businesses increasingly focused on blending data on demand and at the source, the concrete analytic advantages that this approach delivers, and the type of architectures required for delivering trusted, blended data. We provide a checklist to assess your data integration needs and capabilities, and review some real-world examples of how blending various data types has created significant analytic value and concrete business impact.
Putting Business Intelligence to Work on Hadoop Data StoresDATAVERSITY
An inexpensive way of storing large volumes of data, Hadoop is also scalable and redundant. But getting data out of Hadoop is tough due to a lack of a built-in query language. Also, because users experience high latency (up to several minutes per query), Hadoop is not appropriate for ad hoc query, reporting, and business analysis with traditional tools.
The first step in overcoming Hadoop's constraints is connecting to HIVE, a data warehouse infrastructure built on top of Hadoop, which provides the relational structure necessary for schedule reporting of large datasets data stored in Hadoop files. HIVE also provides a simple query language called Hive QL which is based on SQL and which enables users familiar with SQL to query this data.
But to really unlock the power of Hadoop, you must be able to efficiently extract data stored across multiple (often tens or hundreds) of nodes with a user-friendly ETL (extract, transform and load) tool that will then allow you to move your Hadoop data into a relational data mart or warehouse where you can use BI tools for analysis.
Pentaho Big Data Analytics with Vertica and HadoopMark Kromer
Overview of the Pentaho Big Data Analytics Suite from the Pentaho + Vertica presentation at Big Data Techcon 2014 in Boston for the session called "The Ultimate Selfie | Picture Yourself with the Fastest Analytics on Hadoop with HP Vertica and Pentaho"
30 for 30: Quick Start Your Pentaho EvaluationPentaho
These slides are from our recent 30 for 30 webinar tailored towards people that have downloaded the Pentaho evaluation and want to know more about all the data integration and business analytics components part of the trial, how to easily integrate data, and best practices for installing/developing content.
Check out this presentation from Pentaho and ESRG to learn why product managers should understand Big Data and hear about real-life products that have been elevated with these innovative technologies.
Learn more in the brief that inspired the presentation, Product Innovation with Big Data: http://www.pentaho.com/resources/whitepaper/product-innovation-big-data
Expand a Data warehouse with Hadoop and Big Datajdijcks
After investing years in the data warehouse, are you now supposed to start over? Nope. This session discusses how to leverage Hadoop and big data technologies to augment the data warehouse with new data, new capabilities and new business models.
Oracle Big Data Discovery working together with Cloudera Hadoop is the fastest way to ingest and understand data. Powerful data transformation capabilities mean that data can quickly be prepared for consumption by the extended organisation.
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014Pentaho
Bo Borland presentation at MongoDB World in NYC, June 24, 2014. Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyze Disparate Data in a Single MongoDB View
Syncsort, Tableau, & Cloudera present: Break the Barriers to Big Data InsightPrecisely
Demand for quicker access to multiple integrated sources of data continues to rise. Immediate access to data stored in a variety of systems - such as mainframes, data warehouses, and data marts - to mine visually for business intelligence is the competitive differentiation enterprises need to win in today’s economy.
Stop playing the waiting game and learn about a new end-to-end solution for combining, analyzing, and visualizing data from practically any source in your enterprise environment.
Leading organizations are already taking advantage of this architectural innovation to gain modern insights while reducing costs and propelling their businesses ahead of the competition.
Are you tired of waiting? Don't let your architecture hold you back. Access this webinar and hear from a team of industry experts on how you can Break the Barriers to Big Data Insight.
With the advent of Big Data in the Threat Analytics space needs emerge to perform near real-time (NRT) threat detection and automated interpretation that speed counter measures and remediation. AT&T Chief Security Organization (CSO) has developed an enterprise architecture that includes near real-time outlier processes necessary to protect its network from cyber threats using the Hadoop ecosystem. One enterprise challenge that CSO has faced is summarized in the statement by Brian Rexroad, Executive Director of Technology and Security: "I feel there is too much emphasis is on "detecting". Significantly more emphasis is needed in automated extraction of related information/activity and interpretation of that information." Therefore; CSO Engineering team developed the Stratum™ architecture that includes many open source and commercial products facilitating the rapid development and operationalization of outliner detectors and interpreters. Extensive use of NRT data ingestion, enrichment, organization and random access storage patterns, make these capabilities possible on top of a Hadoop based ecosystem. The Stratum™ architecture offers the CSO the ability to minimize the time and effects of many cyber threats. Using Big Data technologies for cyber threat analysis is becoming quite common, but the need for outlier detection and interpretation is crucial for enterprise protection.
Oracle's BigData solutions consist of a number of new products and solutions to support customers looking to gain maximum business value from data sets such as weblogs, social media feeds, smart meters, sensors and other devices that generate massive volumes of data (commonly defined as ‘Big Data’) that isn’t readily accessible in enterprise data warehouses and business intelligence applications today.
Syncsort, Tableau, & Cloudera present: Break the Barriers to Big Data InsightSteven Totman
Demand for quicker access to multiple integrated sources of data continues to rise. Immediate access to data stored in a variety of systems - such as mainframes, data warehouses, and data marts - to mine visually for business intelligence is the competitive differentiation enterprises need to win in today’s economy.
Stop playing the waiting game and learn about a new end-to-end solution for combining, analyzing, and visualizing data from practically any source in your enterprise environment.
Leading organizations are already taking advantage of this architectural innovation to gain modern insights while reducing costs and propelling their businesses ahead of the competition.
Are you tired of waiting? Don't let your architecture hold you back. Access this webinar and hear from a team of industry experts on how you can Break the Barriers to Big Data Insight.
Explore how data integration (or “mashups”) can maximize analytic value and help business teams create streamlined data pipelines that enables ad-hoc analytic inquiries. You’ll learn why businesses increasingly focused on blending data on demand and at the source, the concrete analytic advantages that this approach delivers, and the type of architectures required for delivering trusted, blended data. We provide a checklist to assess your data integration needs and capabilities, and review some real-world examples of how blending various data types has created significant analytic value and concrete business impact.
Putting Business Intelligence to Work on Hadoop Data StoresDATAVERSITY
An inexpensive way of storing large volumes of data, Hadoop is also scalable and redundant. But getting data out of Hadoop is tough due to a lack of a built-in query language. Also, because users experience high latency (up to several minutes per query), Hadoop is not appropriate for ad hoc query, reporting, and business analysis with traditional tools.
The first step in overcoming Hadoop's constraints is connecting to HIVE, a data warehouse infrastructure built on top of Hadoop, which provides the relational structure necessary for schedule reporting of large datasets data stored in Hadoop files. HIVE also provides a simple query language called Hive QL which is based on SQL and which enables users familiar with SQL to query this data.
But to really unlock the power of Hadoop, you must be able to efficiently extract data stored across multiple (often tens or hundreds) of nodes with a user-friendly ETL (extract, transform and load) tool that will then allow you to move your Hadoop data into a relational data mart or warehouse where you can use BI tools for analysis.
Pentaho Big Data Analytics with Vertica and HadoopMark Kromer
Overview of the Pentaho Big Data Analytics Suite from the Pentaho + Vertica presentation at Big Data Techcon 2014 in Boston for the session called "The Ultimate Selfie | Picture Yourself with the Fastest Analytics on Hadoop with HP Vertica and Pentaho"
Explores the notion of "Hadoop as a Data Refinery" within an organisation, be it one with an existing Business Intelligence system or none - looks at 'agile data' as a a benefit of using Hadoop as the store for historical, unstructured and very-large-scale datasets.
The final slides look at the challenge of an organisation becoming "data driven"
Hadoop as Data Refinery - Steve LoughranJAX London
Apache Hadoop is often described as a "Big Data Platform" but what does that mean? One way to better understand Hadoop is to talk about how Hadoop is used. This talk discusses using Hadoop as a "Data Refinery", which is a common use case. The concept is very much like a traditional oil refinery except with data, pulling in large quantities of "crude data" over pipelines, refining some into useful business intelligence; refining other pieces into slightly less crude data that stays in the cluster until needed later. This metaphor proves useful when considering how Hadoop could be adopted in an organisation that already has data warehousing and business intelligence systems -and when contemplating how to hook up a Hadoop cluster to the sources of data inside and outside that organisation. A key point to remember is that storing data in Hadoop is not a means to an end any more than storing data in a database is: it is extracting information from that data. Using Hadoop as a front end "data refinery" means that it can integrate with existing Business Intelligence systems, while providing the platform for new applications.
Create a Smarter Data Lake with HP Haven and Apache HadoopHortonworks
An organization’s information is spread across multiple repositories, on-premise and in the cloud, with limited ability to correlate information and derive insights. The Smart Content Hub solution from HP and Hortonworks enables a shared content infrastructure that transparently synchronizes information with existing systems and offers an open standards-based platform for deep analysis and data monetization.
- Leverage 100% of your data: Text, images, audio, video, and many more data types can be automatically consumed and enriched using HP Haven (powered by HP IDOL and HP Vertica), making it possible to integrate this valuable content and insights into various line of business applications.
- Democratize and enable multi-dimensional content analysis: - Empower your analysts, business users, and data scientists to search and analyze Hadoop data with ease, using the 100% open source Hortonworks Data Platform.
- Extend the enterprise data warehouse: Synchronize and manage content from content management systems, and crack open the files in whatever format they happen to be in.
- Dramatically reduce complexity with enterprise-ready SQL engine: Tap into the richest analytics that support JOINs, complex data types, and other capabilities only available with HP Vertica SQL on the Hortonworks Data Platform.
Speakers:
- Ajay Singh, Director, Technical Channels, Hortonworks
- Will Gardella, Product Management, HP Big Data
A modern, flexible approach to Hadoop implementation incorporating innovation...DataWorks Summit
A modern, flexible approach to Hadoop implementation incorporating innovations from HP Haven
Jeff Veis
Vice President
HP Software Big Data
Gilles Noisette
Master Solution Architect
HP EMEA Big Data CoE
Hadoop World 2011: Big Data Analytics – Data Professionals: The New Enterpris...Cloudera, Inc.
This presentation will explore how Hadoop and Big Data are re-inventing enterprise workflows, and the pivotal role of the Data Analyst. It will examine the changing face of analytics and the streamlining of iterative queries through evolved user interfaces. The speaker will cut through hype around “shorter time to insight” and explain how combining Hadoop and SQL-based analytics help companies discover emergent trends hidden in unstructured data, without having to retrain data miners or restaff. In particular, it will highlight changes to Big Data analysis from this paradigm and illustrate stepwise how analysts can now connect to Big Data platforms, assemble working data sets from disparate sources, analyze and mine that data for actionable insight, publish the results as visualizations and for feeding reporting tools, and operationalize Map-Reduce and Big Data outcomes into company workflows – all without touching the command line.
BI congres 2014-5: from BI to big data - Jan Aertsen - PentahoBICC Thomas More
7de BI congres van het BICC-Thomas More: 3 april 2014
Reisverslag van Business Intelligence naar Big Data
De reisbranche is sterk in beweging. Deze presentatie zal een reis door klassieke en moderne BI bestemmingen zijn, toont een serie snapshots van verschillende use cases in de reisbranche. Tijdens de sessie benadrukken we de capaciteit en flexibiliteit die een BI-tool nodig heeft om u te begeleiden op uw reis van klassieke BI-implementaties naar de moderne big data uitdagingen .
As users gain more experience with Hadoop, they are building on their early success and expanding the size and scope of Hadoop projects. Syncsort’s third annual Hadoop Market Adoption Survey reflects the fact that Hadoop is no longer considered a technology for the future as it was when we first started conducting this research.
Get an in-depth look at the survey results and five trends to watch for in 2017. You’ll also learn:
• The best uses for Hadoop in 2017 – real-word examples of how Enterprises are realizing the value of Big Data
• Solutions to help you address the challenges enterprises still face in employing Hadoop
• What the future of Hadoop means for your business
Explore how data integration (or “mashups”) can maximize analytic value and help business teams create streamlined data pipelines that enables ad-hoc analytic inquiries. You’ll learn why businesses increasingly focused on blending data on demand and at the source, the concrete analytic advantages that this approach delivers, and the type of architectures required for delivering trusted, blended data. We provide a checklist to assess your data integration needs and capabilities, and review some real-world examples of how blending various data types has created significant analytic value and concrete business impact.
Filling the Data Lake - Strata + HadoopWorld San Jose 2016 Preview PresentationPentaho
Preview of the Strata + Hadoop World Strata San Jose 2016 session about truly scalable and automated data onboarding for Hadoop
Attend the presentation at the conference to learn how to tackle repeatable, self-service Hadoop ingestion without coding
Filling the Data Lake
Thursday, March 31 11:50a-12:30p
Room 230B
http://conferences.oreilly.com/strata/hadoop-big-data-ca/public/schedule/detail/50677
James Dixon has a unique perspective on the big data space - he coined the term "data lake." In this on-demand webinar the Big Data Maverick talks big data - watch to learn more about the technology landscape and evolving use cases. He covers topics such as:
- What are today's technologies of choice - where did they come from and why?
- Why is the emergence and definition of these use cases so important?
- What technologies are likely to come next?
- Why did the data explosion start and will it continue?
- Why are data scientists in such huge demand?
- What is the role of open source in big data, and the role of big data in open source?
What's in store for Big Data in 2015? Will the 'Internet of Things' fuel the Industrial Internet? Will Big Data get Cloudy? Check out the top five Big Data predictions for 2015 according to Quentin Gallivan, CEO, Pentah0
With the combination of Pentaho and MongoDB, it’s drastically simpler and faster to build single analytical views of clients by aggregating and blending data from a variety of internal sources (customer, transaction, position data) and external sources (social networking, central bank, news, pricing) with fast response times.
Webinar covers:
An insider’s view of new ways financial services companies are using MongoDB to rapidly store and consume unlimited shapes and sizes of data
How Pentaho makes it easy to enrich data in MongoDB with predictive scoring, visual data integration tools, reports, interactive dashboards, and data visualizations
A live demo of blending Twitter, equity pricing, and news data into a single analytical view that unlocks market intelligence to create investment opportunities
Users and customers don't just want products and services anymore - they also want the data and analytics that are under the hood! The good news is that delivering value with data is more achievable than ever before thanks to greater access to diverse data sources and the ability to process, blend, and refine data at unprecedented scale.
Up Your Analytics Game with Pentaho and Vertica Pentaho
Big Data is a game-changer.
In the face of exploding volumes and varieties of data, traditional data management and ETL systems just aren’t cutting it anymore. A new way of sifting through vast volumes of data to find the most relevant info, combining this data with other data sources to extract faster insights is desperately needed. Enter HP|Vertica and Pentaho with a proven solution for lightning fast queries and blended data and analytics capabilities for your business users.
Predictive Analytics with Pentaho Data Mining - Análisis Predictivo con Penta...Pentaho
This webinar is in Spanish -
El uso de análisis predictivo o minería de datos está en auge. A nivel mundial, cada vez más, las empresas contratan servicios especializados de análisis de información que ayuden a marcar una diferencia con la competencia. Por otro lado, el volumen creciente de data así como su naturaleza cambiante y compleja, hacen inmanejable el proceso de análisis de forma tradicional y está siendo necesario incorporar tecnología y consultoría de punta, basada en el uso de modelos matemáticos avanzados. Pentaho Corporation y Matrix CPM Solutions los invita a participar en el seminario en línea “Análisis Predictivo con Pentaho Data Mining”, en donde se revisarán las grandes oportunidades que existen para su uso y aplicación.
3. The Big Data Fabric
Data Integration Big Analytics
Pentaho Business Analytics 3rd Party Tools
R
Visualization Dashboards 3rd Party BI Tools
Interactive Analysis Reports Applications
Data Integration Scheduling
Job Orchestration High Performance
Workflow Visual IDE
Hadoop Analytic Databases
NoSQL Databases
Big Data Mgmt
3
Leveraging PDI to incorporate Big Data into your data fabric provides immediate access to analytics, examples: Batch and Ad Hoc reporting directly against Big Data Data sources using familiar BI tools with no coding – Report Designer, Interactive Reporting Agile framework to quickly generate/house/manage data marts for interactive analysis, data discovery, etc.