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Hadoop is a top-level Apache project that provides a Java software framework for storing, managing, processing and analysing the massive datasets produced by enterprise web and cloud computing applications. Inspired by Google’s internal software framework and file system, Hadoop includes the HBase distributed database, HDFS distributed file system, MapReduce application framework, Hive data warehousing application and a number of other open source tools, languages and common utilities.
The Best Open Source for Big Data http://bigdatastudio.com/2013/09/01/the-best-of-open-source-for-big-data/
OpenBTS® is an open-source Unix application that uses a software defined radio (like the USRP) to present a GSM air interface to standard GSM handset and uses a software PBX (Asterisk or Freeswitch) to connect calls. The combination of the ubiquitous GSM air interface with VoIP backhaul could form t
Big data and Hadoop have received a lot of press lately. For all the hype, Hadoop does look like an attractive, low-cost solution that your company could leverage. Aside from limited knowledge on how the technology works, a primary reason organizations struggle to achieve value from big data is lack of a compelling business use case.
The team at MetaScale has given this common roadblock plenty of consideration ? first while making big data decisions within Sears Holdings and now as a "big data accelerator" helping clients find the right answers. Tune in for this A2 Radio broadcast as Ankur Gupta, a big data director at Sears and head of sales, marketing, and operations for MetaScale, shares tips on:
Making a case for Hadoop in your organization
Enabling business analytics by speeding up data workloads
Avoiding common missteps and roadblocks
Developing a clearly defined, long-term big data strategy
Whether you think your company's analytics initiative is at the head of the class or struggling to catch up to the competition, you'll want to learn what Blue Hill Research discovered in its survey of enterprise analytics professionals. You might be surprised to learn that your use of analytics isn't quite as advanced as you think, or maybe that you aren't so far behind the state of the art..
Blue Hill's James Haight will be our guest on September 24, sharing some of what he learned in the consulting firm's recent survey looking at which advanced tools and techniques big data analytics teams are using, which types of applications they are investing in, and what their typical workday looks like.
In this online interview you will learn:
About where organizations are finding success with analytics and where they will be implementing analytics over the next two years
About how they are using Hadoop
How some organizations are finding efficiency in data collection and preparation
Join A2 and James Haight at 2 pm (EDT) on Thursday, September 24 to learn more about the state of the analytics in the enterprise.
Building an enterprise analytics team isn't just about competing for talent. The team that leads a big data analytics initiative needs to include the right mix of technical skills -- experience with data management and development of algorithms, models and applications -- as well as what we call soft skills, such as business experience and the ability to communicate with business unit leaders. Don't forget issues like identifying leaders, and rewarding and retaining your analytics talent in a competitive environment.
Manav Misra, who leads a 70-person analytics team at Internet service provider CenturyLink, joins All Analytics Radio to share his experiences and his advice with the A2 community. Misra understands that the statistician, the visualization expert, and the Hadoop specialist bring different but vital talents to a team, and that the skills mix can vary from company to company.
In this event you will learn:
About recruiting analytics team members, whether they are fresh from college or bring 30 years of data-focused experience, at a time when it seems that every company is searching for the same talent
How to identify the right mix of skills and experiences for your own organization
How factors such as corporate demands for tight cybersecurity and the evolution of the Internet of Things raise the bar for the analytics team
How you can motivate, reward, and retain data science talent
Join us on Tuesday, September 1 at 3 pm (EDT) and bring your questions for Manav Misra.
Learn of the increased focus placed on data security, compliance, and privacy to deal with the constant threats to enterprises, and how a leading industry actor effectively makes data protection possible in their growing diverse IT ecosystem. As company's environments become more open and complex, sensitive data can be found not only on internal databases, but also in datawarehouses, Big Data (Hadoop or NoSQL) platforms, and file systems including those outsourced and in the Cloud. We will be discussing best practices approaches (like data activity monitoring and SIEM) to make data protection and regulation compliance a reality for the organization, while keeping costs down in an ever growing and changing IT deployment.
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-avaiability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-availabile service on top of a cluster of computers, each of which may be prone to failures. Cloudera's open-source Apache Hadoop distribution, CDH , targets enterprise-class deployments of that technology
Learn how to lay down the technology foundation for your analytics transformation. In this session, we'll walk you through the relative advantages and disadvantages for midsized firms of public cloud, private cloud, HPC and clusters, scaling up vs. scaling out, placing data close to compute resources, and more. Find out how midsized firms can get the most from Hadoop, Flash storage, and other tools. We'll introduce you to the infrastructure requirements of big-data, and give you a solid idea of the infrastructure choices midmarket firms have for different types of big-data problems.
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