business analytics

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Published By: SAS     Published Date: Jun 05, 2017
This TDWI Best Practices Report focuses on how organizations can and are operationalizing analytics to derive business value. It provides in-depth survey analysis of current strategies and future trends for embedded analytics across both organizational and technical dimensions, including organizational culture, infrastructure, data and processes. It looks at challenges and how organizations are overcoming them, and offers recommendations and best practices for successfully operationalizing analytics in the organization.
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SAS
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: SAS     Published Date: Jun 05, 2017
It’s there for the taking – real-time information about every physical operation of a business. All you need is a key: data analytics.  This paper is based on Blue Hill Research’s interviews of three organizations – a US-based oil and gas company, a US municipality and an international truck manufacturer – each of which heavily invested in IoT analytics. Focusing on the key themes and lessons learned from their initiatives, this paper will help business decision makers make informed investment decisions about the future of their own IoT analytics projects.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
The Internet of Things is fast becoming a fixture in some industries, and the technologies for transformative business applications are at hand. Yet many organizations have been slow to recognize and act on these new opportunities. This report from the International Institute for Analytics explores the many business opportunities IoT presents, details its associated implementation challenges and describes how organizations can accelerate their progress so they don’t fall behind.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Want to get even more value from your Hadoop implementation? Hadoop is an open-source software framework for running applications on large clusters of commodity hardware. As a result, it delivers fast processing and the ability to handle virtually limitless concurrent tasks and jobs, making it a remarkably low-cost complement to a traditional enterprise data infrastructure. This white paper presents the SAS portfolio of solutions that enable you to bring the full power of business analytics to Hadoop. These solutions span the entire analytic life cycle – from data management to data exploration, model development and deployment.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
This Harvard Business Review Insight Center report is a compilation of 26 short stories -- only a page each -- from industry experts and thought leaders versed on the promises and challenges of big data.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Organizations need to accelerate the pace with which they realize business value from data. The focus is on improving “time to value,” which is the length of time it takes from the beginning of a project to the delivery of anticipated business value. This TDWI Best Practices Report focuses on realizing value from BI and analytics and how organizations can accelerate the path to higher value. The report looks at multiple factors impacting the ability of organizations to quickly derive greater value from data and analytics, including the organizational issues, practices, and development methods that are often just as important as keeping pace with technological innovation.
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SAS
Published By: Oracle     Published Date: Nov 05, 2013
Sales people spend more time out of the office than in. When they are out of the office, they need information at their fingertips. And in today’s more mobile, more collaborative, and more data-rich business world, the needs of corporate sales forces are radically changing. In particular, sales people have always needed access to information about their customer before a meeting and an easy way to update customer information after a meeting. Now, to work more efficiently from the road, they could benefit from and in many cases need additional help in the form of relationship management assistance, collaboration tools, and contextual and relevant business analytics.
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mobility, mobile, collaboration, crm, customer service, sales, enterprise communication, mobile crm
    
Oracle
Published By: MapR Technologies     Published Date: Dec 12, 2013
Evaluator Group looks at what will make Hadoop an enterprise data center-grade analytics platform.
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big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
    
MapR Technologies
Published By: MapR Technologies     Published Date: Dec 12, 2013
When used effectively, Hadoop can deliver unparalleled value in revealing new analytics-driven revenue streams, improving customer acquisition and retention, as well as increasing operational efficiencies. The Hadoop Buyer's Guide is an invaluable resource for those investigating or evaluating Hadoop---from understanding how Hadoop can solve your data challenges, to what to look for when selecting a solution, to comparing vendors, and preparing for implementation and future success. Download the guide, and get everything you need to know about choosing the right Hadoop distribution for your business success.
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big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
    
MapR Technologies
Published By: MapR Technologies     Published Date: Dec 12, 2013
This independent whitepaper from the Kusnetzky Group Analyst describes the promise and challenges surrounding Big Data. It also validates the M7 solution from MapR, which simplifies big data management by consolidating disparate solutions into a single, enterprise-ready platform.
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big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
    
MapR Technologies
Published By: MapR Technologies     Published Date: Jan 08, 2014
Forrester Research shares seven architectural qualities for evaluating Big Data production platforms. In this webinar guest speaker Mike Gualtieri, Principal Analyst at Forrester, along with experts from MapR and Cisco, will present the following: • The 7 architectural qualities for productionizing Hadoop successfully • Architectural best practices for Big Data applications • The benefits of planning for scale • How Cisco IT is using best practices for their Big Data applications Speakers • Mike Gualtieri, Principal Analyst at Forrester Research • Jack Norris, Chief Marketing Officer at MapR Technologies • Andrew Blaisdell, Product Marketing Manager at Cisco • Sudharshan Seerapu, IT Engineer at Cisco
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big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
    
MapR Technologies
Published By: MapR Technologies     Published Date: Jan 03, 2014
As the demand for Big Data analytics mushrooms, IT decision-makers must prepare for the widespread deployment of Hadoop. This Technical Insight Paper from the Evaluator Group outlines the key requirements that must be met to make Hadoop enterprise data center ready.
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big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
    
MapR Technologies
Published By: Riverbed     Published Date: Jul 15, 2014
Your business is complex. Big data promises to manage this complexity to make better decisions. But the technology services that run your business are also complex. Many are too complex to manage easily, fueling more complexity, delays, and downtime. Forrester predicts this will inevitably get worse. To combat this onslaught, you can no longer just accelerate current practices or rely on human intelligence. You need machines to analyze conditions to invoke the appropriate actions. These actions themselves can be automated. To perform adaptive, full-service automation, you need IT analytics, a disruption to your existing monitoring and management strategy.
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big data analysis, it analytics, manage, complex, automation, monitoring, management strategy, networking, it management
    
Riverbed
Published By: Yottaa, Inc.     Published Date: May 09, 2014
Increasing user engagement is a primary goal for any website, but measuring it isn’t easy. "User engagement" means different things to different businesses. This free guide defines 10 critical user engagement metrics every business can use, along with web benchmarks and tips. Find out what each of these metrics indicates about your site’s user experience, and where your site stands among the wider web. All of these metrics can be found within free testing tools you likely use already, like Google Analytics and Websitetest.com. Start measuring your website engagement today - download guide here!
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user engagement, conversion optimization, cro, conversion rate, bounce rate, cart abandonment, traffic, web performance, performance monitoring, benchmarking, ecommerce, m-commerce, mobile commerce, mobile optimization, google analytics, a/b testing
    
Yottaa, Inc.
Published By: Sirius Computer Solutions, Inc.     Published Date: Jul 08, 2014
In today’s data-driven culture, tools for business analysis are quickly evolving. Clients need a solution to accelerate their business analytics and reporting capabilities while lowering OP-Ecosts associated with systems management and cost of ownership. Download to learn more!
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sirius computer solutions, ibm, systems solution, sap business suite, sap hana, data, system management, it management, enterprise applications
    
Sirius Computer Solutions, Inc.
Published By: Tableau Software     Published Date: Dec 12, 2014
A new generation of business intelligence emerges as the expectation for user-friendly analytics and the expertise to ask and answer questions with data continues to grow. The wave of innovation is far from over. This paper highlights the top trends in business intelligence for 2015.
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tableau, business intelligence, business management, data management, analytics, top trends, data governance, data journalism, the cloud, cloud data
    
Tableau Software
Published By: Tableau Software     Published Date: Dec 12, 2014
Get started by creating the best type of chart for your data and questions. From there, you’ll quickly find you’re not only answering your initial questions, but telling amazing stories with your data.
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tableau, charts, business charts, data management, data charts, graphs, data analytics, data
    
Tableau Software
Published By: Gleanster Research     Published Date: Oct 11, 2012
Authored by two luminary Business Intelligence (BI) industry analysts. This 9 page report exposes best practices on Self-Service BI. The findings come from a Q3'12 survey on BI, which captured the experiences of 327 organizations.
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business intelligence, cio, self-service, business analytics, data warehouse, data, analysis, business technology
    
Gleanster Research
Published By: IBM     Published Date: Feb 10, 2014
The closer your organization gets to your customers, the more successful it will be. Learn how to take customer relationships to a new level of intimacy using a combination of business intelligence and predictive analytics software.
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ibm, king fish media, business analytics, insights, business intelligence software, analytics quotient, roi, predictive analytics, customer behavior, customer intimacy, data warehousing, it management, business technology
    
IBM
Published By: IBM     Published Date: Feb 10, 2014
Customer Intimacy has become an essential driver for company success.In this white paper, you’ll learn how customer intimacy can be implemented at your organization in five practical steps.
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ibm, business analytics, customer analytics, crm, customer service, customer intimacy, cem, enterprise feedback management, data warehousing, insights, predictive analytics, performance management, it management, business technology
    
IBM
Published By: IBM     Published Date: Feb 10, 2014
Working with BrightStar Partners, an Avnet Services company, and IBM, the PDZA team has developed a new analytics solution that combines real-time weather data with ticket sales and attendance information to help forecast visitor numbers much more accurately than ever before.
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ibm, brightstar, business analytics, software, ibm cognos business intelligence, data management, data warehousing, operational efficiency, customer service, insights, data delivery, marketing, customer analytics, mobile solutions, email, social media, software development, it management, business technology
    
IBM
Published By: IBM     Published Date: Feb 10, 2014
Manage physical and virtual assets, maintain your infrastructure and capital equipment and maximize the efficiency of your people, processes and assets with predictive analytics.
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ibm, ibm business analytics, operational analytics, predictive maintenance, insights, data analysis, roi, operational value cycle, ibm spss, asset management, infrastructure management, it management, knowledge management
    
IBM
Published By: IBM     Published Date: Feb 10, 2014
Predictive maintenance taps into the sets of structured and unstructured data that organizations already have available.
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ibm, business analytics, operational analytics, predictive maintenance, predictive analytics, data analysis, efficiency, roi, infrastructure mangamenet, knowledge management, business technology
    
IBM
Published By: IBM     Published Date: Feb 10, 2014
A car company thought they had a problem with their brake lights. Predictive analytics helped reveal the true culprit.
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ibm, ibm business analytics, operational analytics, predictive maintenance, insights, data analysis, roi, asset management, detection, maintenance, operations, it management, business technology
    
IBM
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