data source

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By: SAP     Published Date: May 18, 2014
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: IBM     Published Date: Apr 18, 2017
Apache Hadoop technology is transforming the economics and dynamics of big data initiatives by supporting new processes and architectures that can help cut costs, increase revenue and create competitive advantage. An effective big data integration solution delivers simplicity, speed, scalability, functionality and governance to produce consumable data. To cut through this misinformation and develop an adoption plan for your Hadoop big data project, you must follow a best practices approach that takes into account emerging technologies, scalability requirements, and current resources and skill levels.
Tags : data integration, data security, data optimization, data virtualization, database security, data migration, data assets, data delivery
     IBM
By: IBM     Published Date: Aug 20, 2015
Understand the traits of successful performers and potential top talent. Using big data to uncover those traits reveals something surprising.
Tags : big data, talent management, ibm recruitment, behavioral insights, potential top talent, impactful management, unique individual characteristics, human resources
     IBM
By: BMC ASEAN     Published Date: Dec 18, 2018
Big data projects often entail moving data between multiple cloud and legacy on-premise environments. A typical scenario involves moving data from a cloud-based source to a cloud-based normalization application, to an on-premise system for consolidation with other data, and then through various cloud and on-premise applications that analyze the data. Processing and analysis turn the disparate data into business insights delivered though dashboards, reports, and data warehouses - often using cloud-based apps. The workflows that take data from ingestion to delivery are highly complex and have numerous dependencies along the way. Speed, reliability, and scalability are crucial. So, although data scientists and engineers may do things manually during proof of concept, manual processes don't scale.
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     BMC ASEAN
By: IBM     Published Date: Jan 09, 2014
While some organizations are already utilizing Big Data or various large enterprise analytics techniques, many more are still working to grasp how these new usage models might help them. There’s a lot of undiscovered value in the vast amounts of data they currently have and the data that they can get from other sources. They know that they can somehow convert this data into insights that will let them ramp up efficiency and be ready for tomorrow today.
Tags : big data, enterprise analytics, red hat, data analytics, powerlinux system, powervm virtualization
     IBM
By: Adaptive Computing     Published Date: Feb 21, 2014
Big data applications represent a fast-growing category of high-value applications that are increasingly employed by business and technical computing users. However, they have exposed an inconvenient dichotomy in the way resources are utilized in data centers. Conventional enterprise and web-based applications can be executed efficiently in virtualized server environments, where resource management and scheduling is generally confined to a single server. By contrast, data-intensive analytics and technical simulations demand large aggregated resources, necessitating intelligent scheduling and resource management that spans a computer cluster, cloud, or entire data center. Although these tools exist in isolation, they are not available in a general-purpose framework that allows them to inter operate easily and automatically within existing IT infrastructure.
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     Adaptive Computing
By: Bazaarvoice     Published Date: Sep 21, 2016
The challenge for brands and retailers is clear. To win during the holiday shopping season, they must: • Plan holiday campaigns leveraging the very best data resources you can to inform messaging and targeting • Use the fragmented holiday shopping journey to their advantage – meeting shoppers in the moments that matter • Cut through the noise on Black Friday – and throughout holiday – to reach consumers with relevant, authentic messages that resonate
Tags : black friday, holiday shopping, holiday campaigns, customer messaging, customer targeting, holiday messaging strategy
     Bazaarvoice
By: HP     Published Date: Mar 15, 2013
Blade servers bring efficiency and agility to IT infrastructures by making it easy to add and move resources and applications. Read this white paper to learn how HP has engineered its blade solutions to deliver the greatest long-term value.
Tags : blade servers, optimizing data center, discover, efficiency, agility, it infrastructure, resources, applications, it management, data management, data center
     HP
By: IBM     Published Date: May 01, 2017
Today's mobile landscape is very much a moving target. IT managers must keep track of all types of devices and platforms, hundreds if not thousands of applications and a threat landscape that changes by the minute. In this ever-changing environment, IT staff often find themselves drowning in mobile minutiae, overwhelmed by mountains of endpoint data but unable to extract meaning from it or make business decisions based on it. The tactical challenge of keeping infrastructure and business data secure while keeping workers productive each day takes precedence. And even then, IT managers can find themselves choosing between security and productivity as they decide how best to spend limited time and resources. This whitepaper will guide you how to get deep visibility into relevant endpoint data within the platform, granting actionable intelligence that can have a measurable impact on your organization.
Tags : it staff, applications, business data, data security, it managers, endpoint data, device, platforms
     IBM
By: Group M_IBM Q2'19     Published Date: May 03, 2019
"Managing and securing endpoints with conventional mobile device management (MDM) or enterprise mobile management (EMM) solutions is time-consuming and ineffective. For this reason, global IT leaders are turning towards unified endpoint management (UEM) solutions to consolidate their management of smartphones, tablets, laptops and IoT devices into a single management console. To increase operational efficiency, maximize data security and deliver on their digital transformation goals, they’ll need a UEM platform that does more than just promise success. The answer is a smarter solution, built for today, that brings new opportunities, threats, and efficiency improvements to the forefront. With Watson™, IBM® MaaS360® UEM features cognitive insights, contextual analytics, and cloud-sourced benchmarking capabilities. It helps you make sense of daily mobile details while managing your endpoints, users, apps, document, and data from one platform."
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     Group M_IBM Q2'19
By: Auth0     Published Date: May 12, 2016
Let’s be honest: If you’re just using one or two social providers for a simple web application, without needing a username/password database yourself, or any other more elaborate features, it is easy enough to DIY. By all means, leverage the basic authentication libraries you can find in any open source framework, and be done with it.
Tags : auth0, identity management, web application, framework, developer
     Auth0
By: Lucidworks     Published Date: Dec 14, 2016
You feel you’ve got a pretty good handle on the following challenges—exponentially increasing amounts of data, ever-increasing user expectations, and limited IT resources—along with your technical requirements. That’s why you chose to build your search app with Apache Solr. Download now to learn more about Apache SoIr and Lucidworks Fusion.
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     Lucidworks
By: AWS     Published Date: Oct 26, 2018
Today’s organisations are tasked with analysing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organisations are finding that in order to deliver analytic insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store enormous amounts of data in a central location, so it’s readily available to be categorised, processed, analysed, and consumed by diverse groups within an organisation? Since data—structured and unstructured—can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
Tags : data, lake, amazon, web, services, aws
     AWS
By: AWS     Published Date: Nov 02, 2017
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store massive amounts of data into a central location, so it’s readily available to be categorized, processed, analyzed, and consumed by diverse groups within an organization. Since data - structured and unstructured - can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
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     AWS
By: Amazon Web Services     Published Date: Oct 09, 2017
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyse data that addresses many of these challenges. Data Lakes allow an organization to store all of their data, structured and unstructured, in one, centralized repository.
Tags : cost effective, data storage, data collection, security, compliance, platform, big data, it resources
     Amazon Web Services
By: Amazon Web Services     Published Date: Jul 25, 2018
What is a Data Lake? Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyze data that addresses many of these challenges. A Data Lakes allows an organization to store all of their data, structured and unstructured, in one, centralized repository. Since data can be stored as-is, there is no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand. Download to find out more now.
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     Amazon Web Services
By: PernixData     Published Date: Jun 01, 2015
Flash is the savior of the virtualized datacenter. It provides incredible performance increases along with tremendous latency reduction, but maximizing its potential can be challenging. Learn how you can architect your storage platform to focus on application performance utilizing server-side resources in conjunction with storage acceleration software.
Tags : pernixdata, application-centric, storage, virtualization, storage, it management, data management
     PernixData
By: Oracle     Published Date: Apr 05, 2016
With cybercrime and security breaches sharply on the rise, protecting valuable information from cyberattacks is an ongoing challenge for companies. In this increasingly insecure world, your critical information deserves the best protection, making the database and surrounding infrastructure the best line of defense. Protect your data better through evolving your approach to data security. Learn about three key steps to reinvent the security of your surrounding infrastructure to create an information fortress by protecting your valuable data at its source.
Tags : information management, security, best practices, information secuirty
     Oracle
By: MarkLogic     Published Date: Nov 07, 2017
Business demands a single view of data, and IT strains to cobble together data from multiple data stores to present that view. Multi-model databases, however, can help you integrate data from multiple sources and formats in a simplified way. This eBook explains how organizations use multi-model databases to reduce complexity, save money, lessen risk, and shorten time to value, and includes practical examples. Read this eBook to discover how to: Get unified views across disparate data models and formats within a single database Learn how multi-model databases leverage the inherent structure of data being stored Load as is and harmonize unstructured and semi-structured data Provide agility in data access and delivery through APIs, interfaces, and indexes Learn how to scale a multi-model database, and provide ACID capabilities and security Examine how a multi-model database would fit into your existing architecture
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     MarkLogic
By: IBM     Published Date: Jan 06, 2016
Big data. We've heard the phrase for quite some time, but how can human resource leaders get into the action?
Tags : talent analytics, ibm, big data, strategy
     IBM
By: IBM     Published Date: Jun 13, 2016
Big data. We've heard the phrase for quite some time, but how can human resource leaders get into the action? One way is through the development and implementation of talent analytics strategies. Talent analytics is fundamentally changing the way organizations and practitioners are thinking about the role of HR and organizations uncovering never before seen insights.
Tags : ibm, talent acquisition, talent acquisition technology, human resources, recruiting
     IBM
By: IBM     Published Date: Jul 20, 2016
Big data. We've heard the phrase for quite some time, but how can human resource leaders get into the action? One way is through the development and implementation of talent analytics strategies. Talent analytics is fundamentally changing the way organizations and practitioners are thinking about the role of HR and organizations uncovering never before seen insights.
Tags : ibm, talent acquisition, talent acquisition technology, human resources, recruiting
     IBM
By: IBM     Published Date: Mar 28, 2016
Big data. We've heard the phrase for quite some time, but how can human resource leaders get into the action? One way is through the development and implementation of talent analytics strategies. Talent analytics is fundamentally changing the way organizations and practitioners are thinking about the role of HR and organizations uncovering never before seen insights.
Tags : ibm, smarter workforce, talent management, talent analytics
     IBM
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