deeper data

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Published By: SAS     Published Date: Aug 28, 2018
“Unpolluted” data is core to a successful business – particularly one that relies on analytics to survive. But preparing data for analytics is full of challenges. By some reports, most data scientists spend 50 to 80 percent of their model development time on data preparation tasks. SAS adheres to five data management best practices that help you access, cleanse, transform and shape your raw data for any analytic purpose. With a trusted data quality foundation and analytics-ready data, you can gain deeper insights, embed that knowledge into models, share new discoveries and automate decision-making processes to build a data-driven business.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
For data scientists and business analysts who prepare data for analytics, data management technology from SAS acts like a data filter – providing a single platform that lets them access, cleanse, transform and structure data for any analytical purpose. As it removes the drudgery of routine data preparation, it reveals sparkling clean data and adds value along the way. And that can lead to higher productivity, better decisions and greater agility. SAS adheres to five data management best practices that support advanced analytics and deeper insights: • Simplify access to traditional and emerging data. • Strengthen the data scientist’s arsenal with advanced analytics techniques. • Scrub data to build quality into existing processes. • Shape data using flexible manipulation techniques. • Share metadata across data management and analytics domains.
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SAS
Published By: Oracle     Published Date: Sep 26, 2019
Marketing is not getting more difficult because of data— it’s actually getting easier. In the old days you needed to guess who your audience was and plan in advance what you wanted to say and wait far too long to see if it worked. Those days are long gone—now you can determine EXACTLY who your audience is, deliver a relevant, personalized message in a nanosecond, and find out almost immediately whether it worked! You no longer have to live by the spray-and-pray method— you can be tactical in your delivery. Marketing today is data-driven and uses a wealth of insights and connection points to engage with consumers one to one. Data about our customers and prospects gives us the ability to deliver the right message to the right audience at the right time. That’s audience targeting, and it’s far deeper than demo targeting, even though targeting by demo is a nice place to start. That said, the sheer volume of data and technology can be overwhelming. Cut through the noise and tackle the ba
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Oracle
Published By: VMware AirWatch     Published Date: Jul 20, 2017
Take a deeper look into how AirWatch enables Windows management to evolve from a rigid PC-centric approach to one offering a flexible and over-the-air configuration model. This session will delve into the specific configuration, security and OS patch management technologies that AirWatch introduces, as well as leveraging AirWatch alongside conventional Windows management tools that are in use today. • Leverage product provisioning and native configuration management features for policy management from the cloud • Integrate with the new Windows Update as a Service to flexibly manage OS updates and patches on or off the domain • Ensure endpoint security and data protection via advanced security features in the management platform and Windows 10
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VMware AirWatch
Published By: IBM     Published Date: Mar 28, 2016
Workforce analytics is a very significant development in human resources. It promises the potential for deeper understanding of the ways workers contribute to organizational performance. However, workforce analytics is not just about analyzing data to reveal exciting insights; it also requires the active involvement of a firm’s workers if the potential of analytics is to be fully realized. Without active employee participation, workforce analytics efforts face at best, restricted data sources and data sets that are incomplete and at worst, the risk of damaging employee relations and, ultimately, productivity. This white paper summarizes recommendations that will encourage enthusiasm for workforce analytics and active employee participation, using the FORT (Feedback, Opt-in, Reciprocal, Transparent) framework. The FORT criteria could prove particularly useful in European countries. This is because the 1995 European Union Data Protection Directive, along with certain local legislative pr
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ibm, ibm smarter workforce institute, work trends, employee engagement
    
IBM
Published By: Red Hat     Published Date: Aug 22, 2018
In the emerging digital enterprise, there’s a good chance some application development will be taking place outside the information technology department. It’s not that the role of IT is in any way being diminished – in fact, IT managers are getting busier than ever, overseeing the technology strategies of their enterprises. Rather, the pieces are in place for business users to build and configure the essential business applications they need, on a self-service basis, with minimal or no involvement of their IT departments. As the world moves deeper into an era of ongoing disruption from digital players – be they startups, or teams within established enterprises – technology has become an essential part of every job, from the boardroom to the boiler room. Accordingly, the discipline of IT is no longer confined to the data center or development shop. Many business managers and professionals are building, launching or downloading their own applications to achieve productivity and respond
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Red Hat
Published By: IBM APAC     Published Date: Nov 22, 2017
Using IBM Watson’s cognitive capabilities, companies can quickly differentiate their customer service quality by being more pro active and responsive to customer needs. Simply put, chatbots and virtual agents are the future of customer interactions. Building apps from scratch that incorporate natural language processing, speech to text recognition, visual recognition, analytics, and artificial intelligence requires broad expertise in these disciplines, large staffs, and a huge financial commitment. Making use of IBM Watson cognitive services brings these capabilities in-house quickly and without the capital investment that would be needed to develop the technologies within an organization.
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decision making, deeper data, insights, cognitive, analytics, ibm, watson, virtual agents
    
IBM APAC
Published By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements. To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
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cloud, database, hybrid cloud, database platform
    
Group M_IBM Q1'18
Published By: Group M_IBM Q1'18     Published Date: Jan 08, 2018
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements. To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
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cloud, database, hybrid cloud, database platform
    
Group M_IBM Q1'18
Published By: DigitalPersona UK     Published Date: Jul 21, 2011
This whitepaper takes a deeper look at the steps you can take to protect your critical data and provide secure access to that data via the cloud to improve your security posture and reduce cost.
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end point security, digitalpersona, saas, security as a service, cloud, cloud security, cloud based security, saas security, strong authentication, fingerprint authentication, identity management, identity protection, data security, identity theft, loss prevention, compliance, biometrics, fraud prevention, transaction authentication, identification
    
DigitalPersona UK
Published By: Sirius Computer Solutions, Inc.     Published Date: Jul 17, 2014
To capitalize on sales opportunities through deeper insights into customer demand, CCBCC needed to crunch more data without increasing time-to-insight, while meeting existing service-level agreements.
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sirius computer solutions, ibm, application performance, storage capacity, cost of ownership, flash technology, storage, it management
    
Sirius Computer Solutions, Inc.
Published By: Cisco     Published Date: Dec 27, 2017
Hyperconvergence has been receiving a tremendous amount of attention because it represents the next step in the evolution of IT resource delivery. This technology takes the idea of integrating compute, storage and networking that started with converged systems design and has improved on those architectures by adding deeper levels of abstraction and automation. Hyperconverged infrastructure (HCI) vendors promise simplified operation and the ability to quickly and easily expand capacity by deploying and launching additional modules; simplicity has been the key selling point for the HCI pioneers. As HCI ventures even deeper into the enterprise and cloud environments, the architectures will need to become more efficient, agile and adaptable to help IT professionals shoulder the burden of rapidly growing data sets and workloads. This report discusses the benefits of HCI and the enhancements that must be made to expand HCI deeper into the mainstream enterprise datacenter.
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Cisco
Published By: Quocirca     Published Date: Dec 02, 2008
The need to share information has never been greater as cross-organizational business processes become deeper and more complex. The movement of digital information, both within a business and across its increasingly porous boundaries to external individuals and organizations, carries more and more risk as regulations are tightened around data protection and personal privacy.
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quocirca, content security, aep networks, clearswift, symantec, trend micro, websense, smtp, security, data management
    
Quocirca
Published By: AWS     Published Date: Jun 20, 2018
Data and analytics have become an indispensable part of gaining and keeping a competitive edge. But many legacy data warehouses introduce a new challenge for organizations trying to manage large data sets: only a fraction of their data is ever made available for analysis. We call this the “dark data” problem: companies know there is value in the data they collected, but their existing data warehouse is too complex, too slow, and just too expensive to use. A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated q
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AWS
Published By: Carbonite     Published Date: Oct 10, 2018
Overview Key Challenges Organizations still struggle with communication between data owners and those responsible for administering DLP systems, leading to technology-driven — rather than business-driven — implementations. Many clients who deploy enterprise DLP systems struggle to get out of the initial phases of discovering and monitoring data flows, never realizing the potential benefits of deeper data analytics or applying appropriate data protections. DLP as a technology has a reputation of being a high-maintenance control — incomplete deployments are common, tuning is a never-ending process, lack of organization buy-in is low, and calculations of ROI are complex.
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Carbonite
Published By: Gigamon     Published Date: Oct 25, 2017
Read the Joint Solution Brief Accelerate Threat Detection and Response to learn how Gigamon helps Splunk Enterprise users effectively analyze and remediate network security threats. Benefits include enhanced visibility and deeper, faster security analytics from precise, targeted network metadata generated from the traffic flowing in your network. Also learn how automation of common security tasks, across the Gigamon platform and third-party security tools, from within the Splunk platform helps increase analyst efficiency and reduce errors.
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Gigamon
Published By: Gigamon     Published Date: Oct 19, 2017
Read the Joint Solution Brief Gigamon Improves Security Visibility with Splunk Enterprise to see how to effectively analyze network events for security threats. Benefits include enhanced visibility and deeper, faster security analytics and intelligence based on all machine data (not just security events), among many others. Download now!
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Gigamon
Published By: HP Inc.     Published Date: Feb 03, 2016
Almost every organization takes its desktop/laptop security seriously – but most simply rely on software-level solutions, missing out on a deeper level of protection. Are these traditional software solutions keeping data safe enough? Not according to a recent Spiceworks survey, in which only about half of IT professionals in the Americas feel like their current, software-level solutions are very effective. Where does your organization rank?
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HP Inc.
Published By: Group M_IBM Q1'18     Published Date: Jan 04, 2018
IBM® InfoSphere® Big Match for Hadoop helps you analyze massive volumes of structured and unstructured customer data to gain deeper customer insights. It can enable fast, efficient linking of data from multiple sources to provide complete and accurate customer information—without the risks of moving data from source to source. The solution supports platforms running Apache Hadoop such as IBM Open Platform, IBM BigInsights, Hortonworks and Cloudera.
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hadoop, infosphere, data, customer insights
    
Group M_IBM Q1'18
Published By: SAS     Published Date: Apr 16, 2015
The synergy of creative work and powerful analytics is the route to impactful, innovative campaigns for iris Worldwide, the global creative innovation network. iris has made this strategy a reality using the advanced analytics capabilities offered by SAS, which has given the agency the ability to garner deeper insights using larger data sets, ultimately resulting in higher returns for its customers.
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SAS
Published By: Hewlett Packard Enterprise     Published Date: May 11, 2018
Digital transformation (DX) is a must for midsize firms (those with 100 to 999 employees) to thrive in the digital economy. DX enables firms to increase competitive advantage through initiatives such as automating business processes, creating greater operational efficiencies, building deeper customer relationships, and creating new revenue streams based on technology-enabled products and services. DX is a journey, and it starts with firms embracing an IT-centric vision that guides a data-driven, analytics-first strategy. The outcome of DX initiatives depends on the ability of a firm to efficiently leverage people (talent), process, platforms, and governance to meet the firm’s business objectives.
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Hewlett Packard Enterprise
Published By: AWS     Published Date: Aug 20, 2018
A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated querying: ability to run a query across heterogeneous sources of data • Data consumption: support numerous types of analysis - ad-hoc exploration, predefined reporting/dashboards, predictive and advanced analytics
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AWS
Published By: Experian     Published Date: Aug 29, 2019
Card-not-present fraud is estimated to reach $19.3 billion by 2022. Online payment fraud will grow 13.7% from 2017-2022 – Juniper Dive deeper into these data points with a focus on assessing the impact, challenges and opportunities presented by emerging payment mechanisms and regulation, as well as an in-depth assessment of sector-specific trends and outlook in regard to digital fraud. It provides essential reading for those wishing to understand where the key strategic focus should lie and how market forces are affecting the industry.
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Experian
Published By: SAS     Published Date: Jun 05, 2017
Analytics is now an expected part of the bottom line. The irony is that as more companies become adept at analytics, it becomes less of a competitive advantage. Enter machine learning. Recent advances have led to increased interest in adopting this technology as part of a larger, more comprehensive analytics strategy. But incorporating modern machine learning techniques into production data infrastructures is not easy.Businesses are now being forced to look deeper into their data to increase efficiency and competitiveness. Read this report to learn more about modern applications for machine learning, including recommendation systems, streaming analytics, deep learning and cognitive computing. And learn from the experiences of two companies that have successfully navigated both organizational and technological challenges to adopt machine learning and embark on their own analytics evolution.
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SAS
Published By: SAP Concur     Published Date: Aug 07, 2019
"Analyst Report: New growth strategies from cost-conscious businesses Use these insights to navigate business expansion and growth New research from Oxford Economics shows why “cost-conscious” SMBs are growing more successfully than their peers…(hint: more efficient cash flow management). Dig deeper into the data, and you’ll discover why some peers excel at business growth by using processes and tools that allow them to: • Why spending control is linked to smart business expansion • How spend management can improve agility and responsiveness • Which processes to automate for continued growth"
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SAP Concur
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