hadoop

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Published By: Bitwise     Published Date: Apr 30, 2018
Organizations that adopt an enterprise data lake model for real-time, self-service and advanced analytics require a fresh approach and outlook to develop a Data Governance strategy as Hadoop changes the way that organizations ingest and store data, as well as how business partners access and use data. This paper outlines pillars for Hadoop Data Governance and Security that provide a framework that can be applied to any company.
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Bitwise
Published By: MapR Technologies     Published Date: Mar 29, 2016
Add Big Data Technologies to Get More Value from Your Stack Taking advantage of big data starts with understanding how to optimize and augment your existing infrastructure. Relational databases have endured for a reason – they fit well with the types of data that organizations use to run their business. These types of data in business applications such as ERP, CRM, EPM, etc., are not fundamentally changing, which suggests that relational databases will continue to play a foundational role in enterprise architectures for the foreseeable future. One area where emerging technologies can complement relational database technologies is big data. With the rapidly growing volumes of data, along with the many new sources of data, organizations look for ways to relieve pressure from their existing systems. That’s where Hadoop and NoSQL come in.
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MapR Technologies
Published By: Paxata     Published Date: Nov 29, 2016
Every organization looks for ways to reduce costs and run more efficiently. In fact, those are key drivers for the mainstream adoption of Hadoop and self-service BI tools. And while we can now collect and store more data than ever before, and we have enabled every information worker into a data-hungry analyst, not much consideration has been paid to the cost - including time and effort - of preparing data. Download this report to learn more about the hidden cost of data preparation.
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Paxata
Published By: Paxata     Published Date: Mar 21, 2017
Every organization looks for ways to reduce costs and run more efficiently. In fact, those are key drivers for the mainstream adoption of Hadoop and self-service BI tools. And while we can now collect and store more data than ever before, and we have enabled every information worker into a data-hungry analyst, not much consideration has been paid to the cost - including time and effort - of preparing data. Download this report to learn more about the hidden cost of data preparation.
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Paxata
Published By: Cambridge Semantics     Published Date: Aug 17, 2015
As the quantity and diversity of relevant data grows within and outside of the enterprise, business users and IT are struggling to extract maximum value from this data. Current approaches, including the rigid relational data warehouse and the unwieldy Hadoop-only Data Lake, are limited in their ability to provide users and IT with the answers they need with the proper governance and security required. Read this whitepaper to learn how The Anzo Smart Data Lake from Cambridge Semantics solves these problems by disrupting the way IT and business alike manage and analyze data at enterprise scale with unprecedented flexibility, insight and speed.
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Cambridge Semantics
Published By: Splice Machine     Published Date: Nov 16, 2014
Organizations are now looking for ways to handle exploding data volumes while reducing costs and maintaining performance. Managing large volumes and achieving high levels of concurrency on traditional scale up databases, such as Oracle, often means purchasing expensive scale-up hardware. In this white paper, learn about the different options and benefits of scale out solutions for Oracle database users.
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splice machine, oracle, oracle database, database, hadoop, nosql, white paper, data, data management, dataversity
    
Splice Machine
Published By: Pentaho     Published Date: Nov 03, 2016
While a whole ecosystem of tools has sprung up around Hadoop to handle and analyze data, many of them are specialized to just one part of a larger process. In order to fulfill the promise of Hadoop, organizations need to step back and take an end-to-end view of their analytic data pipelines.
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Pentaho
Published By: AT&T     Published Date: Sep 11, 2014
The age of Big Data is upon us. Storage costs are going down, and data analytics is becoming more capable and more user-friendly. Even your auto mechanic will be storing a petabyte of data soon. Big Data will give businesses new insights and help improve operations. With these new tools come questions about how to use them. But your mechanic knows more about fixing a transmission than developing a Hadoop cluster, and similar concerns hold true for larger enterprises. Businesses everywhere are looking for guidance.
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AT&T
Published By: Basho     Published Date: Nov 25, 2015
The landscape of Scalable Operational and Analytical Systems is changing and disrupting the norm of using relational databases for all workloads. With the growing need to process and analyze Big Data at Scale, the demand for alternative strategies has grown and has given rise to the emergence of NoSQL databases for scalable processing. Mike Ferguson, Managing Director of Intelligent Business Strategies, is an independent IT Analyst who specializes in Big Data, BI/Analytics, Data Management and Enterprise Business Integration. In this whitepaper he will discuss the movement towards NoSQL databases for scalable operational and analytical systems, what’s driving Big Data analytics from Hadoop to the emergence of Apache Spark, the value of operational analytics and the importance of in-memory processing, and why use Apache Spark as your in-memory analytical platform for operational analytics.
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Basho
Published By: MapR Technologies     Published Date: Jul 26, 2013
Enterprises are faced with new requirements for data. We now have big data that is different from the structured, cleansed corporate data repositories of the past.Before, we had to plan out structured queries. In the Hadoop world, we don’t have to sort data according to a predetermined schema when we collect it. We can store data as it arrives and decide what to do with it later. Today, there are different ways to analyze data collected in Hadoop—but which one is the best way forward?
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white paper, hadoop, nosql, mapr, mapr technologies
    
MapR Technologies
Published By: Splice Machine     Published Date: May 19, 2014
SQL-on-Hadoop solutions have become very popular recently as companies solve the data access issues with Hadoop or seek a scale-out alternative for traditional relational database management systems. However, with all of the options available, choosing which solution is right for your business can be a daunting task. This white paper discusses the options you should consider and questions to ask, including: Is it really “Real-Time”? Is it true SQL? Does it support secondary indexes? Can it efficiently handle sparse data? Can it deliver fast performance on massive joins? Read this white paper to get a better understanding of the SQL-on-Hadoop landscape and what questions you should ask to identify best solution for your business.
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white paper, splice machine, sql, hadoop, nosql, nosql white paper, hadoop white paper, dataversity
    
Splice Machine
Published By: MIT Academy of Engineering, Pune     Published Date: Mar 05, 2013
A Java application that will successfully be able to retrieve, insert & delete data from our database which will be implemented in HBase along with.Basically the idea is to provide much faster, safer method to transmit & receive huge amounts of data
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MIT Academy of Engineering, Pune
Published By: SAP     Published Date: Mar 09, 2017
Learn how CIOs can set up a system infrastructure for their business to get the best out of Big Data. Explore what the SAP HANA platform can do, how it integrates with Hadoop and related technologies, and the opportunities it offers to simplify your system landscape and significantly reduce cost of ownership.
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SAP
Published By: Hewlett Packard Enterprise     Published Date: Aug 02, 2017
In midsize and large organizations, critical business processing continues to depend on relational databases including Microsoft® SQL Server. While new tools like Hadoop help businesses analyze oceans of Big Data, conventional relational-database management systems (RDBMS) remain the backbone for online transaction processing (OLTP), online analytic processing (OLAP), and mixed OLTP/OLAP workloads.
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database usage, database management, server usage, data protection
    
Hewlett Packard Enterprise
Published By: Pentaho     Published Date: Feb 26, 2015
This TDWI Best Practices report explains the benefits that Hadoop and Hadoop-based products can bring to organizations today, both for big data analytics and as complements to existing BI and data warehousing technologies.
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big data, big data analytics, data warehousing technologies, data storage, business intelligence, data integration, enterprise applications, data management
    
Pentaho
Published By: Pentaho     Published Date: Nov 04, 2015
This report explains the benefits that Hadoop and Hadoop-based products can bring to organizations today, both for big data analytics and as complements to existing BI and data warehousing technologies based on TDWI research plus survey responses from 325 data management professionals across 13 industries. It also covers Hadoop best practices and provides an overview of tools and platforms that integrate with Hadoop.
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pentaho, analytics, platforms, hadoop, big data, predictive analytics, data management, networking, it management, knowledge management, enterprise applications, data center
    
Pentaho
Published By: Pentaho     Published Date: Nov 04, 2015
Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.
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pentaho, analytics, platforms, hadoop, big data, predictive analytics, networking, it management, knowledge management, data management
    
Pentaho
Published By: Dell EMC     Published Date: Nov 09, 2015
This business-oriented white paper summarizes the wide-ranging benefits of the Hadoop platform, highlights common data processing use cases and explores examples of specific use cases in vertical industries. The information presented here draws on the collective experiences of three leaders in the use of Hadoop technologies—Dell and its partners Cloudera and Intel.
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Dell EMC
Published By: Dell EMC     Published Date: Nov 09, 2015
While the EDW plays an all-important role in the effort to leverage big data to drive business value, it is not without its challenges. In particular, the typical EDW is being pushed to its limits by the volume, velocity and variety of data. Download this whitepaper and see how the Dell™ | Cloudera™ | Syncsort™ Data Warehouse Optimization – ETL Offload Reference Architecture can help.
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Dell EMC
Published By: Dell EMC     Published Date: Oct 08, 2015
The information presented here draws on the collective experiences of three leaders in the use of Hadoop technologies—Dell® and its partners Cloudera® and Intel®.
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Dell EMC
Published By: Dell EMC     Published Date: Oct 08, 2015
This paper discusses how the many Dell | Cloudera Hadoop solutions help organizations of all sizes, and with a variety of needs and use cases, tackle their big data requirements.
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Dell EMC
Published By: Dell EMC     Published Date: Oct 08, 2015
In order to protect big data today, organizations must have solutions that address four key areas: authentication, authorization, audit and lineage, and compliant data protection.
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Dell EMC
Published By: Dell EMC     Published Date: Oct 08, 2015
To compete in this new multi-channel environment, we’ve seen in this guide how retailers have to adopt new and innovative strategies to attract and retain customers. Big data technologies, specifically Hadoop, enable retailers to connect with customers through multiple channels at an entirely new level by harnessing the vast volumes of new data available today. Hadoop helps retailers store, transform, integrate and analyze a wide variety of online and offline customer data—POS transactions, e-commerce transactions, clickstream data, email, social media, sensor data and call center records—all in one central repository.
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Dell EMC
Published By: Dell EMC     Published Date: Oct 08, 2015
Download this white paper to learn how the company deployed a Dell and Hadoop cluster based on Dell and Intel® technologies to support a new big data insight solution that gives clients a unified view of customer data.
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Dell EMC
Published By: Dell EMC     Published Date: Oct 12, 2015
This business-oriented white paper explains four options for starting your Hadoop journey. This paper also outlines the benefits of Hadoop and highlights some of the many use cases for this new approach to managing, storing and processing big data.
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Dell EMC
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