analytics organizations

Results 201 - 225 of 227Sort Results By: Published Date | Title | Company Name
By: SAS     Published Date: Mar 31, 2016
Digitization creates major opportunities for financial services – automating operations, expanding channels, delivering engaging customer experiences.
Tags : analytics, financial services, operations, digital management, data, best practices
     SAS
By: SAS     Published Date: May 17, 2016
This report provides a guide to some of the opportunities that are available for using machine learning in business, and how to overcome some of the key challenges of incorporating machine learning into an analytics strategy. We will discuss the momentum of machine learning in the current analytics landscape, the growing number of modern applications for machine learning, as well as the organizational and technological challenges businesses face when adopting machine learning. We will also look at how two specific organizations are exploiting the opportunities and overcoming the challenges of machine learning as they’ve embarked on their own analytic evolution.
Tags : oreilly, evolution of analytics, sas, machine learning, analytics landscape, networking, it management, data management
     SAS
By: SAS     Published Date: Apr 25, 2017
Organizations in pursuit of data-driven goals are seeking to extend and expand business intelligence (BI) and analytics to more users and functions. Users want to tap new data sources, including Hadoop files. However, organizations are feeling pain because as the data becomes more challenging, data preparation processes are getting longer, more complex, and more inefficient. They also demand too much IT involvement. New technology solutions and practices are providing alternatives that increase self-service data preparation, address inefficiencies, and make it easier to work with Hadoop data lakes. This report will examine organizations’ challenges with data preparation and discuss technologies and best practices for making improvements.
Tags : 
     SAS
By: SAS     Published Date: Apr 25, 2017
This Checklist explores how AI can be used to enhance marketing analytics and to help companies both better understand their customers and deliver a great customer experience. It also provides practical advice on how organizations can use what they may already be doing to become more effective in marketing.
Tags : 
     SAS
By: SAS     Published Date: Jun 05, 2017
One of the biggest inhibitors of analytics success is the delay between developing and implementing models. This paper reviews how an analytics factory, a rapid scoring and model development environment, can help organizations turn models into insight faster than before.
Tags : 
     SAS
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.
Tags : 
     SAS
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.
Tags : 
     SAS
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.
Tags : 
     SAS
By: SAS     Published Date: Oct 18, 2017
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
Tags : 
     SAS
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.
Tags : 
     SAS
By: IBM     Published Date: Sep 10, 2013
This white paper will discuss how big data analytics, coupled with the right facilities and asset management software, can provide next-generation opportunities to improve facilities and asset management processes and reutnrs. It will examine how different organizations successfully use big data generated by their facilities and assets to help increase revenue, power operational efficiency, ensure service availability and mitigate risk. Most importantly, this white paper will reveal how your organization can leverage big data analytics to achieve similar benefits and transform the management of your organization's facilities and assets-and ultimately, your business.
Tags : big data, smarter infrastructures, big data, ibm, power operational, leverage big data, analytics, harnessing the power of data, security, enterprise applications, data management
     IBM
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.
Tags : ibm, king fish media, business analytics, insights, business intelligence software, analytics quotient, roi, predictive analytics, customer behavior, customer intimacy, data warehousing, it management
     IBM
By: IBM     Published Date: May 07, 2015
Learn how to build a proactive threat and fraud strategy based on business analytics. You’ll see extensive examples of how organizations worldwide apply IBM Business Analytics solutions to minimize the negative impact of risk and maximize positive results.
Tags : business analytics, risk management, threat management, fraud, proactive threat, analytics solutions, reduce exposure, reduce threats
     IBM
By: IBM Software     Published Date: Oct 26, 2010
Analytics are changing how organizations today operate. Being able to quickly and effortlessly interact with business information is now considered essential to making the best business decisions.
Tags : analytics, business decision making, analytics system
     IBM Software
By: IBM Software     Published Date: Feb 11, 2011
This white paper explores how predictive analytics helps marketing organizations increase ROI by executing highly targeted campaigns focused on high revenue-generating customers and prospects.
Tags : ibm cognos, predictive analytics, marketing campaign management system, roi, customer behaviour
     IBM Software
By: SAS     Published Date: Aug 03, 2016
New analytics tools and services are helping organizations extract exceptional business value from the massive volumes of available data provided by various internal and external sources. Many companies are harnessing these insights to improve operational and business processes, troubleshoot problems, identify business opportunities, and generally compete and innovate better. Now the benefits of analytics in those areas are prompting companies to look to analytics to improve information security. Enterprise security organizations are under tremendous pressure to change. Traditional perimeter-focused security controls and strategies have proved inadequate against modern, highly targeted attack campaigns.
Tags : best practices, technology, security, enterprise, analytics
     SAS
By: SAS     Published Date: Aug 03, 2016
As the pace of business continues to accelerate, forward-looking organizations are beginning to realize that it is not enough to analyze their data; they must also take action on it. To do this, more businesses are beginning to systematically operationalize their analytics as part of a business process. Operationalizing and embedding analytics is about integrating actionable insights into systems and business processes used to make decisions. These systems might be automated or provide manual, actionable insights. Analytics are currently being embedded into dashboards, applications, devices, systems, and databases. Examples run from simple to complex and organizations are at different stages of operational deployment.
Tags : best practices, embedding analytics, technology, data, operational analytics
     SAS
By: SAS     Published Date: Jun 27, 2019
In the quest to understand how a therapeutic intervention performs in actual use – in real medical practice outside the controlled environment of clinical trials – many life sciences organizations are stymied. They rely on one-off processes, disconnected tools, costly and redundant data stores, and ad hoc discovery methods. It’s time to standardize real-world data and analytics platforms – to establish much-needed consistency, governance, repeatability, sharing and reuse. The organizations that achieve these goals will formalize their knowledge base and make it scalable, while significantly reducing turnaround times, resources and cost. Learn the seven key components for putting that structure to real-world evidence – and four ways to take it to the next level.
Tags : 
     SAS
By: MicroStrategy     Published Date: Aug 21, 2019
To survive and thrive in an era of accelerating digital disruption, organizations require accessible data, actionable insights, continuous innovation, and disruptive business models. It’s no longer enough to prioritize and implement analytics – leaders are being challenged to stop doing analytics just for analytics’ sake and focus on defined business outcomes. In addition, these leaders are being challenged to bring predictive capabilities and even prescriptive recommended actions into production at scale. As AI and accelerated growth and transformation become top of mind, many enterprises are realizing that their current segmented analytics approach isn’t built to last, and that real transformation will require proper endto- end data management, data security, and a data processing platform company-wide. The year 2019 will be a turning point for many organizations that realize being data-driven doesn’t guarantee future success.
Tags : 
     MicroStrategy
By: IBM Business Analytics     Published Date: Jun 23, 2011
David Axson, author of The Management Mythbuster, explains how insightful analytics and a systematic approach to risk management can drive dramatic improvements in the quality and value that finance organizations deliver.
Tags : ibm business analytics, david axson, enterprise risk management, erp, enterprise resource planning, insightful analytics, finance function
     IBM Business Analytics
By: IBM Software     Published Date: Jun 08, 2011
This white paper explores how predictive analytics helps marketing organizations increase ROI by executing highly targeted campaigns focused on high revenue-generating customers and prospects.
Tags : ibm cognos, predictive analytics, marketing campaign management system, roi, customer behaviour
     IBM Software
By: Dell Software     Published Date: Apr 17, 2013
The paper showcases how IT can proactively address problems before they result in service degradation. Foglight provides the visibility organizations need into the why of customer behavior. Line-of-business owners can identify sources of customer frustration and work with IT to eliminate issues.
Tags : beyond web analytics, dell, quest software, reduce customer frustration, visible organizations
     Dell Software
By: Cisco     Published Date: Sep 15, 2015
IDC finds that leveraging data analytics in business decisions is becoming a top priority for an increasing number of companies. This in turn is placing new demands on IT organizations; the need is twofold: to manage new streams of unstructured data from sources such as social media and to speed response times to deliver real-time analytics.
Tags : sap, analytics, data, real-time, it management, enterprise applications
     Cisco
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: AWS     Published Date: Sep 04, 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 technology
Tags : 
     AWS
Start   Previous    1 2 3 4 5 6 7 8 9 10    Next    End
Search White Papers      

Add White Papers

Get your white papers featured in the insideHPC White Paper Library contact: Kevin@insideHPC.com