Published By: Cloudian
Published Date: Jun 08, 2015
For companies looking to build their own cloud storage infrastructure, including enterprise IT organizations and cloud service providers or cloud hosting providers, the decision to use cloud and cloud storage for the delivery of IT services is best made by starting with the knowledge and experience gained from previous work. This white paper gathers into one place the essentials of a scale-out storage reference architecture coupled with a real world example from the Cloudian support organization that is using the Cloudian HyperStore appliances and the Hortwonworks Hadoop Data Platform to analyze Big Data logs and troubleshoot customer issues.
This paper discusses the role of the QlikView Business Discovery platform as the foremost user-friendly analytics platform accompanying a Big Data solution. It is written for IT professionals and business leaders who are trying to understand how to gain the most leverage from a Big Data implementation by providing an analytics layer that can both access the data and make it relevant and accessible to the business users in an organization.
Data centers face financial pressure as server-side compute cycles grow while space, power, and funds continue to be limited. Increased demand for compute capacity comes from growth in mobile devices, big data and analytics, cloud computing, media consumption, hosted desktops, and more. Data center managers find themselves maxed out on storage, power, cooling, space, storage, and compute capacity. Even with virtualization, there is a capacity limit to existing resources. Building more facilities is an option, but the emerging technology of ultra-dense computing offers a more compelling financial alternative for many common workloads.
Customer demands have led to recent changes in the data warehouse market. As a result, companies and departments of all types and sizes can leverage advanced data warehouse solutions to facilitate effective use of innovative business analytics and support of various mission-critical business intelligence initiatives.
Without access to a mix of capabilities such as business intelligence, performance management, data quality, extensibility, analytics, location intelligence, and SaaS, organizations will be hard-pressed to optimize efficiency, performance, and the bottom line. The right partnership will drive new revenue and solutions for organizations of all sizes.
Published By: AccelOps
Published Date: Jun 27, 2013
Companies rely on the data center and IT to provide mission-critical services, like email, Web, and voice. However, assuring service delivery and reliability becomes increasingly difficult as growth in data center virtualization, remote access, cloud-based
applications, and outsourced service technologies fuel operational complexity. To improve service reliability, organizations must be able to see and manage all aspects of
performance, availability, and security related to that service.
Find out how the combination of discovery, data aggregation, correlation, out-of-the-box analytics, data management, and reporting can yield a single pane of glass into data center and IT operations and services.
Published By: Aberdeen
Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
What’s the best analytic approach for your business?
As technology has evolved, so has our ability to process data at an incredible rate, making it possible to perform what has become known as Anticipatory Analytics. While still a relatively new concept, anticipatory analytics is gaining prevalence as a methodology.
If you’re seeking to understand the future needs of your business before they show obvious signs, anticipatory analytics can’t be ignored.
In this document, you’ll learn:
• The advantages of anticipatory analytics
• The key enablers of anticipatory analytics
• How anticipatory can be leveraged for your business
• Why anticipatory can give you first-mover advantage
• When to use anticipatory or predictive analytics, based on your goals
Creating predictive analytics from alternative data has become the current focus of the biggest quant trading firms in the industry
The democratization of financial services data and technology, together with more intense competition, makes the needs of today’s market participants vastly different from those of previous generations. Firms must locate untapped sources of data for both public and non-public companies. This alternative data, such as payment data and other non-public information, from sources beyond the common channels, can be a predictive indicator of market performance; a difference maker in assisting firms as they develop models to evaluate their investments.
By combining our unique data sets with advanced analytics, traders, analysts and managers can seek predictive signals and actionable information utilizing their own models.
View our research report to learn how alternative data, our 'Information Alpha,' can help you earn differentiated investment returns.
Stories and statistics behind successful analytics projects
The adoption of analytics across the enterprise is accelerating, and with good reason. Analytics can offer a competitive advantage by helping to identify growth opportunities, circumnavigate risk and improve customer relationships. These insights are becoming crucial parts of the business strategy for executives representing a wide array of industries.
Check out our latest eBook to see how some of the world’s leading companies are using analytics to meet their needs. You’ll receive diverse examples of how organizations applied the latest statistical methodologies, such as: scorecard build, regression, decision trees, machine learning and material change to uncover meaning in data.
The examples represent global brands across critical industries – Financial Services, Insurance, High-Tech, Aerospace, Manufacturing and others – where analytics helped answer their most challenging questions.
Published By: Microsoft
Published Date: Feb 02, 2017
Download the Keystone Research whitepaper to see how top performing enterprises use their IT investments to store, process, and use data to make more effective, real-time decisions.
Keystone Research, a global economics and data-driven strategy consulting firm, interviewed senior IT and business decision makers at over three hundred businesses to uncover the relationship between Data & Analytics technologies and business performance. This research shows that companies who have developed the most sophisticated Data & Analytics platforms and apply these capabilities as a regular part of their business enjoy operating margins that are eight percentage points higher than lagging organizations. This translates to $100 million in operating profits on average for the more advanced companies in the sample controlling for factors such as company size and industry vertical.
High-priority big data and analytics projects often target customer-centric outcomes such as improving customer loyalty or improving up-selling. In fact, an IBM Institute for Business Value study found that nearly half of all organizations with active big data pilots or implementations identified customer-c entric outcomes as a top objective (see Figure 1).1 However, big data and analytics can also help companies understand how changes to products or services will impact customers, as well as address aspects of security and intelligence, risk and financial management, and operational optimization.
It's all well enough for an organization to collect every slice of data it can reach, but having more data doesn't mean you'll automatically get better insights. First, you have to figure out what you want from your data you have to find its value.
The outcome of any big data analytics project, however, is only as good as the quality of the data being used. As big data analytics solutions have matured and as organizations have developed greater expertise with big data technologies he quality and trustworthiness of the data sources themselves are emerging as key concerns. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Analytics has permeated, virtually, every department within an organization. It’s no longer a ‘nice to have’. It’s an organizational imperative. HR, specifically, collects a wealth of data; from recruiting applications, employee surveys, performance management data and it sits in systems that remain largely untapped. This data can help drive strategic decisions about your workforce. Analytic tools have, historically, been difficult to use and required heavy IT lifting in order to get the most out of them. What if an analytics system learned and continue to learn as it experienced new information, new scenarios, and new responses. This is referred to as Cognitive Computing and is key to providing an analytics system that is easy to use but extremely powerful.
In this Executive Brief, we share best practices in how to evaluate and deploy layered controls that will help you develop a holistic approach to controls, investigate and control where risk is introduced, assess your risk appetite and benchmark your cybersecurity posture against others in your industry.
This research report examines the key issues, and provides recommendations for leveraging data and analytics to help procurement drive greater enterprise value. Based on in-depth interviews with two dozen leading Chief Procurement Officers (CPOs), the report outlines pragmatic steps that every procurement organization can take to leverage analytics and improve engagement with suppliers and key business stakeholders across the enterprise.
Published By: Mindfire
Published Date: May 07, 2010
In this report, results from well over 650 real-life cross-media marketing campaigns across 27 vertical markets are analyzed and compared to industry benchmarks for response rates of static direct mail campaigns, to provide a solid base of actual performance data and information.
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.