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The document discusses big data analytics. It defines big data analytics as extracting value from large volumes of a wide variety of data by analyzing it to reveal patterns, trends and associations. This analysis can help companies gain competitive advantages by using the insights for applications like predictive analytics, risk analysis, personalization, fraud detection and recommendations. It notes that while big data analytics can provide opportunities, it also presents challenges due to its complexity. It proposes a big data analytics suite that would make these tools more accessible to businesses.
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InterConnect 2013 Big Data & Analytics Keynote: Mychelle Mollot
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http://ibm.com/interconnect
Bigdata
SUM TWO is making 'serious investments' in big data, cloud, mobility !!! “Big data refers to the datasets whose size is beyond the ability of atypical database software tools to capture ,store, manage and analyze.defines big data the following way: “Big data is data that exceeds theprocessing capacity of conventional database systems. The data is too big, moves toofast, or doesnt fit the strictures of your database architectures. The 3 Vs of Big data.Apache Hadoop is 100% open source, and pioneered a fundamentally new way of storing and processing data. Instead of relying on expensive, proprietary hardware and different systems to store and process data, Hadoop enables distributed parallel processing of huge amounts of data across inexpensive, industry-standard servers that both store and process the data, and can scale without limits. With Hadoop, no data is too big. And in today’s hyper-connected world where more and more data is being created every day, Hadoop’s breakthrough advantages mean that businesses and organizations can now find value in data that was recently considered useless.Hadoop’s cost advantages over legacy systems redefine the economics of data. Legacy systems, while fine for certain workloads, simply were not engineered with the needs of Big Data in mind and are far too expensive to be used for general purpose with today's largest data sets.One of the cost advantages of Hadoop is that because it relies in an internally redundant data structure and is deployed on industry standard servers rather than expensive specialized data storage systems, you can afford to store data not previously viable . And we all know that once data is on tape, it’s essentially the same as if it had been deleted - accessible only in extreme circumstances.Make Big Data the Lifeblood of Your Enterprise
With data growing so rapidly and the rise of unstructured data accounting for 90% of the data today, the time has come for enterprises to re-evaluate their approach to data storage, management and analytics. Legacy systems will remain necessary for specific high-value, low-volume workloads, and compliment the use of Hadoop-optimizing the data management structure in your organization by putting the right Big Data workloads in the right systems. The cost-effectiveness, scalability and streamlined architectures of Hadoop will make the technology more and more attractive. In fact, the need for Hadoop is no longer a question.
Ibm big data-platform
The document discusses IBM's Big Data and analytics solutions, including Watson Explorer which provides a single interface to access both structured and unstructured data. It also outlines several common use cases for big data such as customer analytics, security intelligence, and operations analysis. The final section provides contact information for an IBM sales manager to discuss these big data solutions.
Managing your Assets with Big Data Tools
This presentation was given by Karthigai Muthu, Lead Big Data Analyst, at a meetup organized by the group Internet of Everything in March 2015.
Through his presentation, Karthik provided a comprehensive understanding of available ecosystem tools and how they can be used to perform data engineering and data analytics. Karthik covers the following topics in his presentation:
• Establishment of complete data pipeline using big data ecosystem tools.
• Tackling of high velocity streams using various stream processing engines on cloud and performing Real Time analytics.
• Tackling of historical data using big data ecosystem tools and migration of traditional infrastructure to big data environments.
• Integration of big data ecosystem for data analysis using SAMOA , R and Mahout.
• Deployments of big data environments on the cloud.
130214 copy
This document discusses the future of big data and new approaches for processing large and complex datasets. It defines big data as collections of data that are too large for traditional database systems to handle due to volume, velocity and variety. The document outlines sources of big data like social media, mobile devices, and networked sensors. It also describes frameworks like Hadoop and NoSQL databases that can analyze petabytes of distributed data in parallel. The conclusions state that new big data systems will extend and possibly replace traditional databases as more data becomes available from various sources.
WCIT 2014 Rohit Tandon - Big Data to Drive Business Results: HP HAVEn
Keynote address at the WCIT 2014
Big Data to Drive Business Results: HP HAVEn
Rohit Tandon, VP - Corporate Strategy, WW Head of HP Global Analytics
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This document discusses how a big data fabric can enable machine learning and artificial intelligence by providing a flexible and agile way for users to access and analyze large amounts of data from various sources. It explains that a big data fabric, powered by data virtualization, allows organizations to build a modern data ecosystem that provides governed access to both structured and unstructured data stored in different systems. This helps users develop new production analytics and insights. The document also provides an example of how Logitech used a big data fabric and data virtualization to improve their customer analytics.
Seminário Big Data, 19/05/2014 - Apresentação Federico Grosso
The document discusses Hewlett-Packard's big data solutions. It describes the opportunity for companies to gain insights from vast amounts of data, but also the challenges of analyzing unstructured data across different sources. The solution proposed uses HP's HAVEn platform, which includes Autonomy, Vertica, and Hadoop to collect, process and analyze human, machine, social and transactional data at scale. Examples are given of political campaigns and NASCAR using HP's big data tools to better engage with customers and fans.
Take the Big Data Challenge - Take Advantage of ALL of Your Data 16 Sept 2014
A customer service call can transform internal processes. Information in Tweets and reviews can lead to better products. Structured and unstructured data brought together can reveal patterns and relationships that unlock powerful business opportunities. We will discuss real-world use cases and best practices for building the infrastructure you need to power Big Data analytics solutions. From the latest in Hadoop innovation, cognitive computing, and cloud-based analytical web services, you will learn how organizations large and small can harness the power of unstructured human information to create, deploy, and deliver the next generation of analytics applications.
Powered by HP IDOL, HP Autonomy delivers intelligent applications that allow your organization to understand the concepts and context of all information in real time, mitigating risk and identifying opportunity. Join us at this session to learn how HP Autonomy can unlock the value of your company’s structured and unstructured data for better insight and greater competitive advantage. HP IDOL, the OS for human information, enables you to index, manage, and process all your data, both structured and unstructured. Learn how HP IDOL delivers unprecedented insights into optimized architecture, scalability, performance, mapped security, and connectivity. Find out more about IDOLOnDemand.com and how you can leverage this revolutionary technology in your own organization.
Worry free security breach - Gemalto
The document discusses Gemalto's solutions for securing data in today's digital environments. It outlines Gemalto's capabilities in key management, encryption, access control, and multi-factor authentication. Gemalto provides security solutions for large enterprises, financial services, governments, healthcare organizations, retailers, cloud service providers, and the Internet of Things. The challenges of securing data across multiple borders, silos, and service providers are discussed. Gemalto's SafeNet Data Protection On Demand is presented as automating security processes and providing unified security that can be consumed on demand, on-premises, or in the cloud.
IBM's big data seminar programme -moving beyond Hadoop - Ian Radmore, IBM
Big Data Meets Big Analytics Theatre - June 18th, 15:00-15:30
Eighty percent of the world's data is unstructured, and most businesses don't even attempt to use this data to their advantage. Imagine if you could afford to keep and analyse all the data generated by your business. Imagine that you had a way to analyse and exploit that data as it is created! Whether you're a telecoms provider trying to minimise customer churn, a utility company looking to exploit the potential of smart-metering or a surveillance company ensuring the security of clients' premises, there are genuine business opportunities from deploying big data analytics in real-time. Using live client examples, Ian will show how real-time analytics provide a powerful extension to any big data platform and is applicable across many types of information and real-world problems to deliver tangible business value.
Big Data & Analytics – beyond Hadoop
Ian Radmore, an IBM Big Data Specialist spoke about the velocity aspect of the 4Vs associated with Big Data at the recent Internet World conference, this is the supporting presentation.
SplunkLive! Paris 2016 - Plenary session
Splunk provides a platform for operational intelligence that allows users to analyze machine data from any source. The document discusses Splunk products and solutions for IT service management, security intelligence, and Internet of Things applications. Splunk has over 11,000 customers across various industries.
Top 10 renowned big data companies
In today’s context, the big data market is rapidly undergoing contortions that define market maturity, such as consolidation. Big data refers to large volumes of data. This can be both structured and unstructured data. Big data is data that is huge in size and grows exponentially with time. As the data is too large and complex, traditional data management tools are not sufficient for storing or processing it efficiently. But analyzing big data is crucial to know the patterns and trends to be adopted to improve your business.
Big data
Big data refers to large and complex datasets that require new techniques and technologies to capture, manage, and analyze the data. Common characteristics of big data include large volumes of data generated from sources like social media, sensors, and mobile devices with high velocity and variety of structured and unstructured data types. Managing and analyzing big data allows organizations to extract hidden patterns and insights to improve decision making.
Impacto del Big Data en la empresa española
Dirigida a directivos y analistas de mediana y gran empresa, Big Data Spain celebró una charla previa a la conferencia de la segunda edición del 7y 8 de noviembre del 2013.
Vídeo youtube: https://www.youtube.com/watch?v=6HbWErRCD1g
¿Quieres saber más?
http://www.paradigmatecnologico.com/
Oscar Méndez, co-fundador de www.paradigmatecnologico.com y www.stratio.com, habló de Big Data desde un punto de vista de negocio, y despejó dudas acerca del coste y recursos necesarios para aprovechar esta tecnología.
Las plataformas v2.0 post-Hadoop permiten el despligue rápido y simple de herramientas integradas de data mining, data processing, data analysis y data visualization. Los avances de los últimos 12 meses dejan atrás las limitaciones de sistemas de Business Intelligence tradicionales.
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1 big datacampdell2013
- 1. What is Big Data Analytics? Guy Harrison Executive Director, R&D Information Management 1 Confidential Software Group
- 7. 7
- 8. What is Big Data? Value Competitive or Collective advantage Variety Volume Structured Unstructured Human Generated Machine Generated Terabytes Petabytes Exabytes Zetabytes Velocity User populations x Transaction rates x Machine data 8 Confidential Software Group
- 10. Fed by cloud, social and mobile 10 Confidential Software Group
- 14. The instrumented human Compass Camera Mike/earphones Heads up display Emotion/Attention monitor • • • • • • Bluetooth Personal Area Network 3G/WiFi Wide Area Network GPS • Storage • • 14 Confidential • • • Pulse, temp monitor Silent alarms Pedometer, sleep monitoring Software Group
- 16. Big Data Analytics More Data Smarter Algorithms Operational Integration Competitive Advantage 16 Confidential Software Group
- 17. Social Media Demographics Online Systems Marketing Automation Dynamic Pricing 17 Confidential Big Data Analytic Algorithms Business Intelligence Customer Acquisition Personalization Customer Retention Software Group
- 18. Big Data Analytics Big Data Analytics AKA Data Science Collective Intelligence Machine Learning Programs that use inputs from “crowds’ to seem intelligent Programs that evolve with “experience” Predictive Analytics Programs that extrapolate from existing data into the future 18 Confidential Software Group
- 27. Search Optimization Advertising • Targeting • Tailoring Game optimization Recommendation Systems Big Data Analytics Medical • Risk analysis • Diagnosis • Prognosis Security • Vulnerability • Penetration Detection Fraud Detection Predictive Analytics • Churn • Defaults 27 Software Group
- 28. Big Data Analytics is HARD! • Machine learning, collective intelligence, Hadoop, predictive analytics, R, Weka, Mahout, are HARD • Small-medium businesses need help to compete • Data scientists to the rescue? 28 Software Group
- 30. We need a Big Data Analytics Suite Kitenga Analytics Suite 30 Confidential Software Group
Editor's Notes
- Insanely popular – literally millions of users