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business analytics

Results 176 - 200 of 903Sort Results By: Published Date | Title | Company Name
Published By: FICO     Published Date: Jun 07, 2016
With the increasing mainstream adoption of big data infrastructure — highly distributed file storage and query tools — more businesses are taking a new look at what business intelligence and analytics can do to grow revenue, increase profits and ultimately develop strategic relationships with customers.
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FICO
Published By: Anaplan     Published Date: Apr 06, 2016
A Harvard Business Review Analytics Services White Paper Finance is constantly tested to keep pace in today’s business environment. To keep up, planning needs to become a continuous process that spans departmental boundaries and enables managers to collectively realign resources to respond to market changes. Organizations must streamline disparate sales and operational planning with traditional financial planning and analysis by using technology to connect people, data, and processes across the organization. Download this white paper to discover the three steps to moving towards finance-led integrated business planning recommended by the Harvard Business Review.
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analytics, planning, cfo, operations, business practices, revenue, growth, enterprise business, finance trends, business analytics, business process, harvard business review, hbr, financial planning, corporate finance, fp&a, budgeting, integrated business planning, ibp, finance
    
Anaplan
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: Google Analytics 360 Suite     Published Date: Sep 05, 2017
Today’s meandering customer journeys take place over multiple channels and devices. Each interaction creates a stream of digital information, leaving marketers with a growing pile of data. But, with data seemingly everywhere, why are so many marketers still feeling like there’s not a drop to drink? Leaders Have a Data Strategy and Enable More Teams with Data In this research report from June 2017, Econsultancy surveyed more than 700 marketing and analytics executives at consumer brands to better understand how data factors into marketing strategy — and daily decision making. Two-thirds of leading marketers — those who outperformed their top business goal — say they currently have a documented data and analytics strategy. In this report, you’ll also learn how leaders have built data-driven cultures and why they are more likely to use: digital analytics to optimize user experience in real time audience-level data to personalize customer experience customer-level data to segment and r
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Google Analytics 360 Suite
Published By: Groove     Published Date: May 16, 2018
HotSchedules is a technology company that streamlines several aspects of running a business in the service industry. The sales team at HotSchedules had been using Salesforce for several years, but they were spending a lot of time on data entry and other manual tasks. They needed a way to simplify recordkeeping so they could spend more time talking to prospects. The HotSchedules sales team is taking advantage of the full suite of features in Groove to enhance their sales operations at every turn — from Salesforce integration to multi-step campaigns to analytics. Let’s take a look.
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Groove
Published By: Splunk     Published Date: Nov 29, 2018
From protecting customer experience to preserving lines of revenue, IT operations teams face increasingly complex responsibilities and are responsible for preventing outages that could harm the organization. As a Splunk customer, your machine data platform empowers you to utilize machine learning to reduce MTTR. Discover how six companies utilize machine learning and AI to predict outages, protect business revenue and deliver exceptional customer experiences. Download the e-book to learn how: Micron Technology reduced number of IT incidents by more than 50% Econocom provides better customer service by centralizing once-siloed analytics, improving SLA performance and significantly reducing the number of events TransUnion combines machine data from multiple applications to create an end-to-end transaction flow
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predictive it, predictive it tools, predictive analytics for it, big data and predictive analytics
    
Splunk
Published By: Splunk     Published Date: Dec 11, 2018
Predictive IT is a powerful new approach that uses machine learning and artificial intelligence (AI) to predict incidents before they impact customers and end users. By using AI and predictive analytics, IT organizations are able to deliver seamless customer experiences that meet changing customer behavior and business demands. Discover the critical steps required to build your IT strategy, and learn how to harness predictive analytics to reduce operational inefficiencies and improve digital experiences. Download this executive brief from CIO to learn: 5 steps to an effective predictive IT strategy Where AI can help, and where it can’t How to drive revenue and exceptional customer experiences with predictive analytics
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predictive it, predictive it tools, predictive analytics for it, big data and predictive analytics
    
Splunk
Published By: Location3     Published Date: Aug 31, 2018
When we released our first white paper in February 2015 discussing the ways multi-location businesses were using online media to drive in-store visits, most of the strategic opportunities being leveraged by marketers revolved around using things like promotional coupons, beacons and other tactics. While those methods certainly provided incremental lift in in-store traffic and revenue, there existed a number of gaps in connecting online data associated with promotional efforts, to data that indicated a customer actually converted offline at a business location. At press time for our original “online-to-offline” white paper, digital industry giants were still very much in the early stages of evaluating data points that signified offline customer conversions. Many of these “conversions” were somewhat implied (i.e. Clicks on “Get Directions” link), while others were a bit more reliable in signifying in-store visits and purchases made by consumers (i.e. downloadable coupon redeemed in-store
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marketing, local marketing, franchise, franchisor, digital marketing, online to offline, multi-location businesses, store visits, cross channel analytics
    
Location3
Published By: Workday APAC     Published Date: May 08, 2019
As your organization’s finance leader, the opportunity to better understand the landscape and your business has never been greater. Advances in analytics—powered by digital technologies, such as automation and machine learning—give finance teams deeper business insights. Read the story.
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Workday APAC
Published By: Workday APAC     Published Date: May 08, 2019
Finance can now move beyond the back office to lead business strategy with new technology and analytics. Want to learn how that’s done? Come see how finance can help your organization become more agile and competitive in today’s digitized business environment.
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Workday APAC
Published By: IBM APAC     Published Date: May 14, 2019
Clients can realize the full potential of artificial intelligence (AI) and analytics with IBM’s deep industry expertise, technology solutions and capabilities and start to infuse intelligence into virtually every business decision and process. IBM’s AI & Analytics Services organization is helping enterprises get their data ready for AI and ultimately achieve stronger data-driven decisions; access deeper insights to provide improved customer care; and develop trust and confidence with AI-powered technologies focused on security, risk and compliance. Artificial intelligence (AI) is moving beyond the hype cycle, as more and more organizations seek to adopt AI-related technologies. These organizations are focusing on prioritizing functional areas and use cases, placing a stronger emphasis on topline growth, taking up a renewed interest in their data infrastructure and articulating greater unease about the skills of their knowledge workers. This report explores how they are approaching str
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IBM APAC
Published By: Amazon Web Services     Published Date: Oct 09, 2017
As easy as it is to get swept up by the hype surrounding big data, its just as easy for organisations to become discouraged by the challenges they encounter while implementing a big data initiative. Concerns regarding big data skill sets (and the lack thereof), security, the unpredictability of data, unsustainable costs, and the need to make a business case can bring a big data initiative to a screeching halt. However, given big data's power to transform business, it's critical that organisations overcome these challenges and realise the value of big data. The cloud can help organisations to do so. Drawing from IDG's 2015 Big Data and Analytics Survey, this white paper analyses the top five challenges companies face when undergoing a big data initiative and explains how they can effectively overcome them.
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amazon, web services, intel, migration, data warehousing, organization optimization, security, software
    
Amazon Web Services
Published By: Teradata     Published Date: Jan 20, 2015
This Neil Raden and Teradata webinar explores: The business values gained from an integrated view of SAP® and non-SAP® data; Existing solutions and challenges; Requirements for the optimal BI and analytics platform, and; A new solution that simplifies and enhances BI analytics for SAP® ERP data.
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data warehouse, teradata, business value, analytics platform, erp data, data management
    
Teradata
Published By: Teradata     Published Date: Jan 16, 2015
Companies that use SAP® need to have a method to access all valuable information that is recorded in order to make the best business decisions and establish a sustainable competitive advantage. With Teradata Analytics for SAP®, Lamb Weston, a global frozen potato product producer, has been able to generate their business intelligence reports quickly and effortlessly. BI that lets you focus on running the business…Download now!
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teradata, sap, product producer, sap success, data management
    
Teradata
Published By: Teradata     Published Date: Jan 16, 2015
Teradata® Analytics for SAP® Solutions performs high-value business analytics on integrated data.
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data analytics, high-value, integrated data, intelligence, data management
    
Teradata
Published By: Dassault Systèmes     Published Date: Jul 21, 2017
Obtaining a first-mover competitive advantage or faster time-to-market requires a new wave in analytics. Dassault Systèmes remains a leading innovator in Product Lifecycle Management (PLM) and has invested heavily in analytical technologies to further drive business benefits for its customers in the related areas of planning, simulation, insight and optimization. This white paper examines the challenges peculiar to PLM and why Dassault Systèmes’ EXALEAD offers the most appropriate solution. It also clearly positions EXALEAD PLM Analytics alongside related technologies like BI, data-warehousing and Big Data solutions. Understand and implement PLM Analytics to access actionable information, support accurate decision-making, and drive performance.
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product solutions, lifecycle management, tech products, data management tools, pdm, plm, process automation, product development speed, manufactures
    
Dassault Systèmes
Published By: Teradata     Published Date: May 02, 2017
To understand the challenges and opportunities with the Internet of Things, MIT Sloan Management Review’s 2016 Global Executive Study conducted a comprehensive study with business executives, managers, and IT professionals globally. Through the survey results and interviews with subject matter and industry experts, MIT Sloan Management Review was able to reveal the business value and competitive issues from the Internet of Things (IoT). This comprehensive report dives into data sharing with competitors, analytic talent management, and the intersection with governing the data. Analytics is unsurprisingly is shown as the key to IoT success.
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data, sharing, analytics, iot, mit
    
Teradata
Published By: IBM     Published Date: Feb 02, 2016
In this white paper, IDC Energy Insights discusses the current and future challenges that utilities face in meeting their business objectives and the role analytics will play.
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analytics, energy, utilities, ibm, big data, productivity
    
IBM
Published By: IBM     Published Date: Apr 01, 2016
Traditional business intelligence (BI) looks backward at what has happened. In today’s marketplace, enterprises need to look ahead. In this eGuide from TDWI, you'll discover how advances in predictive analytics are enabling organizations to use insights about the past and present to make accurate predictions about the future.
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ibm, business intelligence, ibm connect, predictive analytics, enterprise applications, business technology
    
IBM
Published By: IBM     Published Date: Apr 11, 2016
This paper explores why your business needs the latest operational decision management (ODM) solutions to help turn data insights into action. Discover how IBM Operational Decision Manager software and the IBM Business Process Manager platform work together to: *Recognize patterns that suggest opportunity or risk *Create and shape business events by automating decisions *Bring more dimension and precision to decision making by applying analytics to big data *Help you implement the right business processes by understanding data in context.
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ibm, smarter process, operational decision management, odm, knowledge management, enterprise applications, business technology
    
IBM
Published By: IBM     Published Date: Apr 22, 2016
This white paper explains the value of putting data and insight to work to accelerate an organization’s journey to becoming a Cognitive Business, by enhancing their investments in data and analytics and realizing new opportunities from cognitive systems that understand, reason and learn.
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ibm, ibm analytics, cognitive business, watson, think data, knowledge management, enterprise applications, data management, business technology
    
IBM
Published By: IBM     Published Date: Jul 08, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. 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.
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ibm, idc, big data, data, analytics, information governance, knowledge management, data management, data center
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
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.
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IBM
Published By: IBM     Published Date: Jan 27, 2017
While any number of reasons can prompt a change in data warehouse solutions, there are four key facts you need to know to help you make the right choice: 1. Complexity stifles business 2. Speed is business-friendly 3. Cost reduction is crucial 4. Analytics: The key to current and future success This e-book will explore those facts and explain why they are essential when evaluating your data warehouse options.
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IBM
Published By: Group M_IBM Q2'19     Published Date: Apr 03, 2019
Data is the lifeblood of business. And in the era of digital business, the organizations that utilize data most effectively are also the most successful. Whether structured, unstructured or semi-structured, rapidly increasing data quantities must be brought into organizations, stored and put to work to enable business strategies. Data integration tools play a critical role in extracting data from a variety of sources and making it available for enterprise applications, business intelligence (BI), machine learning (ML) and other purposes. Many organization seek to enhance the value of data for line-of-business managers by enabling self-service access. This is increasingly important as large volumes of unstructured data from Internet-of-Things (IOT) devices are presenting organizations with opportunities for game-changing insights from big data analytics. A new survey of 369 IT professionals, from managers to directors and VPs of IT, by BizTechInsights on behalf of IBM reveals the challe
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Group M_IBM Q2'19
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