big data

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Published By: Amazon Web Services     Published Date: Jul 25, 2018
Organizations are collecting and analyzing increasing amounts of data making it difficult for traditional on-premises solutions for data storage, data management, and analytics to keep pace. Amazon S3 and Amazon Glacier provide an ideal storage solution for data lakes. They provide options such as a breadth and depth of integration with traditional big data analytics tools as well as innovative query-in-place analytics tools that help you eliminate costly and complex extract, transform, and load processes. This guide explains each of these options and provides best practices for building your Amazon S3-based data lake.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
As easy as it is to get swept up by the hype surrounding big data, it’s just as easy for organizations to become discouraged by the challenges they encounter while implementing a big data initiative. Concerns regarding big data skill sets (and the lack thereof), security, the unpredictability of data, unsustainable costs, and the need to make a business case can bring a big data initiative to a screeching halt. However, given big data’s power to transform business, it’s critical that organizations overcome these challenges and realize the value of big data. Download now to find out more.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Defining the Data Lake “Big data” is an idea as much as a particular methodology or technology, yet it’s an idea that is enabling powerful insights, faster and better decisions, and even business transformations across many industries. In general, big data can be characterized as an approach to extracting insights from very large quantities of structured and unstructured data from varied sources at a speed that is immediate (enough) for the particular analytics use case.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Il est tout aussi facile d'être submergé par l'omniprésent Big Data qu'il l'est pour les organisations d'être découragées par les défis qu'elles rencontrent lorsqu'elles implémentent une initiative en matière de Big Data. Les préoccupations liées aux ensembles de compétences associées au Big Data (et à leur absence), à la sécurité, à l'imprévisibilité des données, aux coûts non viables et à la nécessité d'effectuer une analyse de rentabilité peuvent mettre brutalement fin à une initiative en matière de Big Data.
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Amazon Web Services
Published By: Dell Server     Published Date: Aug 07, 2018
IT is in the midst of one of its major transformations. IDC has characterized this paradigm shift as the “third platform,” driven by innovations in cloud, big data, mobility and social technologies. Progressive enterprises are seeking to leverage third-platform technologies to create new business opportunities and competitive differentiation through new products and services, new business models and new ways of engaging customers.
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Dell Server
Published By: IBM     Published Date: Jun 13, 2018
The cloud offers elasticity and flexibility to meet a range of demands
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IBM
Published By: TIBCO Software APAC     Published Date: Aug 13, 2018
The popularity of integration platform as a service (iPaaS) started with business users looking to gain control and share data among their proliferating SaaS apps?without needing IT intervention. iPaaS was then adopted by IT to support business users to ensure security measures were being maintained and to provide more of a self-service environment. Now, iPaaS has evolved from a niche solution to taking a much bigger role: Read this whitepaper to learn about: Drivers for cloud integration Five emerging uses cases for iPaaS that enable better responsiveness, APIs, event-driven capabilities, human workflows, and data analysis Questions to ask when evaluating your current solution
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TIBCO Software APAC
Published By: TIBCO Software APAC     Published Date: Aug 13, 2018
Big data has raised the bar for data virtualization products. To keep pace, TIBCO® Data Virtualization added a massively parallel processing engine that supports big-data scale workloads. Read this whitepaper to learn how it works.
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TIBCO Software APAC
Published By: TIBCO Software APAC     Published Date: Aug 15, 2018
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms. Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
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TIBCO Software APAC
Published By: Splunk     Published Date: Sep 10, 2018
The financial services industry has unique challenges that often prevent it from achieving its strategic goals. The keys to solving these issues are hidden in machine data—the largest category of big data—which is both untapped and full of potential. Download this white paper to learn: *How organizations can answer critical questions that have been impeding business success *How the financial services industry can make great strides in security, compliance and IT *Common machine data sources in financial services firms
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cloud monitoring, aws, azure, gcp, cloud, aws monitoring, hybrid infrastructure, distributed cloud infrastructures, reduce mttr/mtti, cloud monitoring free, cloud monitoring tools, cloud monitoring service, cloud billing monitoring, cloud monitoring architecture, cloud data monitoring, host monitoring, *nix, unix, linux, servers
    
Splunk
Published By: IBM     Published Date: Apr 19, 2018
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
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db2, data migration, ibm, oracle
    
IBM
Published By: IBM     Published Date: Jul 02, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does. From an IT perspective, there is a fairly straightforward sequence of applications that businesses can adopt over time that will help put direction into this journey. IDC outlines this sequence to e
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IBM
Published By: IBM     Published Date: Aug 08, 2018
An IBM Cloud configuration completed a big data analytics workload in less time and with greater throughput than an AWS solution
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IBM
Published By: Artemis Health     Published Date: Jul 10, 2018
By looking at benefits data for self-insured employers, Artemis and its clients are finding wins, identifying trends, and positively impacting care.
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Artemis Health
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Big data alone does not guarantee better business decisions. Often that data needs to be moved and transformed so Insight Platforms can discern useful business intelligence. To deliver those results faster than traditional Extract, Transform, and Load (ETL) technologies, use Matillion ETL for Amazon Redshift. This cloud- native ETL/ELT offering, built specifically for Amazon Redshift, simplifies the process of loading and transforming data and can help reduce your development time. This white paper will focus on approaches that can help you maximize your investment in Amazon Redshift. Learn how the scalable, cloud- native architecture and fast, secure integrations can benefit your organization, and discover ways this cost- effective solution is designed with cloud computing in mind. In addition, we will explore how Matillion ETL and Amazon Redshift make it possible for you to automate data transformation directly in the data warehouse to deliver analytics and business intelligence (BI
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Amazon Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. Organizations choose Amazon Redshift for its affordability, flexibility, and powerful feature set: • Enterprise-class relational database query and management system • Supports client connections with many types of applications, including business intelligence (BI), reporting, data, and analytics tools • Execute analytic queries in order to retrieve, compare, and evaluate large amounts of data in multiple-stage operations
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. It’s designed for speed and ease of use — but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether you’ve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technolog
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Amazon Web Services
Published By: Adverity     Published Date: Jun 15, 2018
A Beginner's Guide to Marketing Data Analytics Marketing Data is big & highly fragmented Big data is messy. It’s scattered across platforms, it’s diverse, and in its raw form, it’s practically unusable. We know, it’s a painful truth. The fact of the matter is that having a lot of data doesn’t necessarily mean that you have the answers to your most pressing questions. Looking for the most relevant bits in your pile of big data is like looking for a needle in a haystack. But don't you worry - we are here to help. This handy e-book will give you a short overview what quality matters, why data is so important and what you need to pay attention to. Best thing is: getting this ebook is super easy. Just fill out the form to the right and voilá - your download is ready. Enjoy this read!
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marketing business intelligence, saas marketing optimization, measuring marketing performance, roi analytics, automated report generator, performance based marketing, online marketing data, roi metrics, marketing reports, roi reporting, reporting generator, automated reporting tool, marketing dashboard, marketing data, marketing intelligence, report software, marketing reporting, marketing metrics, performance marketing, marketing performance
    
Adverity
Published By: Adverity     Published Date: Jun 15, 2018
In this whitepaper, we take a closer look at some of the biggest challenges facing e-commerce businesses, namely understanding your data in general and, more precisely, your customer acquisition costs (CAC). It's full of inspiration, useful tips and actionable insights for you to step up your marketing game. In order to reap the fruits from your data seeds, you have to make sure you tackle these five challenges full-frontal: Knowing what data to capture Understanding customer behaviour Finding your technology solution Ensuring analysis is impartial Optimising website content - especially for your offline users
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marketing business intelligence, saas marketing optimization, measuring marketing performance, roi analytics, automated report generator, performance based marketing, online marketing data, roi metrics, marketing reports, roi reporting, reporting generator, automated reporting tool, marketing dashboard, marketing data, marketing intelligence, report software, marketing reporting, marketing metrics, performance marketing, marketing performance
    
Adverity
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: IBM     Published Date: Jul 17, 2018
As of May 25, 2018, organizations around the world—not just those based in the EU—need to be prepared to meet the requirements outlined within the EU General Data Protection Regulation (GDPR). Those requirements apply to any organization doing business with any of the more than 700 million EU residents, whether or not it has a physical presence in the EU. IBM® Security can help your organization secure and protect personal data with a holistic GDPR-focused Framework that includes software, services and GDPR-specific tools. With deep industry expertise, established delivery models and key insights gained from helping organizations like yours navigate complex regulatory environments, IBM is well positioned to help you assess your needs, identify your challenges and get your GDPR program up and running
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IBM
Published By: SAP     Published Date: Mar 09, 2017
There’s strong evidence organizations are challenged by the opportunities presented by external information sources such as social media, government trend data, and sensor data from the Internet of Things (IoT). No longer content to use internal databases alone, they see big data resources augmented with external information resources as what they need in order to bring about meaningful change. According to a September 2015 global survey of 251 respondents conducted by Harvard Business Review Analytic Services, 78 percent of organizations agree or strongly agree that within two years the use of externally generated big data will be “transformational.” But there’s work to be done, since only 21 percent of respondents strongly agree that external data has already had a transformational effect on their firms.
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SAP
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: HPE APAC     Published Date: Jun 16, 2017
The bar has been raised higher than ever, and the role of IT is evolving to meet it. As a result, IT must support applications and services that make it possible for the business to provide new, diverse customer experiences while generating expanding revenues via the emergent crown jewels of business: big data, cloud, and mobility. Read on to find out more.
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HPE APAC
Published By: Cisco EMEA Tier 3 ABM     Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
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big data, analytics, virtualization, cloudera, ibm, sas, sap, splunk
    
Cisco EMEA Tier 3 ABM
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