data matching

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Published By: IBM     Published Date: Jul 26, 2017
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base. 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-centric 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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customer analytics, data matching, big data, competitive advantage, customer loyalty
    
IBM
Published By: IBM     Published Date: Jul 06, 2016
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
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ibm, mdm, big data, data management, data matching, customer analytics
    
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: Trintech EMEA ABM Pilot     Published Date: Nov 03, 2017
In terms of reconciliations, we tend to spend most of our time simply gathering data before we can even begin to think about reconciling it. Once the data is finally in the right format, the majority of our time is then spent manually going through the matching process, rather than spending that time focused on the areas that are most critical to us, as can be seen in the diagram on the right.
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account reconciliation, accounting automation, finance shared services, finance transformation program, finance transformation strategy, financial close, financial close process, reconciliation software, adjusting journal entries, recuing journal entries
    
Trintech EMEA ABM Pilot
Published By: Epicor     Published Date: Jan 16, 2018
Brookside Lumber—a Pennsylvania-based lumber and building materials (LBM) dealer—needed a new business software system that was flexible, open, user-friendly, and easily enhanced. They wanted a solution that could get them the data they needed to accomplish their goals in a timely manner. That’s where Epicor BisTrack came in. BisTrack helps LBM dealers achieve operational efficiencies by: • Matching workflow needs of LBM contractor yards • Automatically notifying users of necessary information • Delivering seamless, hands-on implementation • Quickly getting information out of the solution for special request • Providing optional add-on applications for business growth • Adapting to the way you do business • Servicing customers faster Read this case study to learn more about how Epicor BisTrack was able to help Brookside Lumber, and discover how it can also help your LBM business. Download the case study now.
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lumber, building materials, lbm, erp, bistrack, lumber distributors, lumber manufacturers
    
Epicor
Published By: EverString     Published Date: Jul 27, 2018
You have lots of leads, but finding the right match is getting harder and harder. You know the good leads are out there. They might even be looking for you. The trouble is, those good leads are hidden among so many bad ones. Your sales and marketing teams know this. They’re facing a deluge of data, not all of it reliable, and they’re trying to decode that data using outdated point solutions and imperfect criteria. Which means a lot of time spent running campaigns, initiating conversations and booking meetings that go nowhere. If this were the dating world, we’d be talking about a calendar full of bad first dates. Everyone’s “swiping right,” but no one’s truly matching. No one’s getting a second date. No one’s committing. Something just isn’t working. We can’t help you if you’re dating. But if you’re trying to sell your company’s products and services—well, the game is about to change. Instead of moving through a volume of potential customers as quickly as possible to build pipeline, th
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EverString
Published By: SRC,LLC     Published Date: Jun 01, 2009
Today, organizations are collecting data at every level of their business and in volumes that in the past were unimaginable. Data sets are stored in different database systems or in files with distinctive formats, all reflecting business process, application, program software, or information type dependencies. Adding to this complexity is the distribution of these data sets across the enterprise in silos requiring a varied set of tools and/or specialized business rules for data transformation, classification, matching, and integration. Because of the massive amounts of data stored in a variety of representation formats, decision makers strain to derive insights and create business solutions that adequately span and integrate information from these disparate technology islands. Learn more today!
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src, data transformation, classification, business value, geographic business intelligence, geo-bi, etl, extract, transform, load, spatial analysis, operational data stores, ods, spatial data, etl, cdi, point of sale, retail floor space management, rfsm, alteryx
    
SRC,LLC
Published By: DataFlux     Published Date: Jan 07, 2011
This white paper describes a general approach for planning your organization's efforts to improve data quality, providing a data-example-driven perspective of some of the unique challenges of product data quality, as well as discuss and demonstrate three critical steps to improving product data quality.
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dataflux, product data quality, standardization, matching
    
DataFlux
Published By: Trend Micro, Inc.     Published Date: Apr 29, 2009
The greatest threat to enterprise data security comes from inside threats. Securing the enterprise requires an understanding of the data leak points, environment, people, and processes for managing sensitive information. This white paper explains how network-based and endpoint-based solutions can work together to provide the broadest protection available while ensuring scalability and manageability, and that employee productivity is not impacted.
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trend micro, datadna, data leak, threat, leak, network boundaries, vulnerability threats, data leak, laptop, environment, data loss, data protection, data management, data leak prevention, dlp, agent-based technology, remote computing, leakproof, monitoring, enforcement
    
Trend Micro, Inc.
Published By: SAP     Published Date: Mar 24, 2011
In spite of the growth of virtual business activities performed via the World Wide Web, every business transaction or operation is performed at a physical place. And as handheld GPS devices drive a growing awareness of the concept of "location," people are increasingly looking for operational efficiencies, revenue growth, or more effective management as a result of geographic data services and location-based intelligence. In this white paper, David Loshin, president of Knowledge Integrity, Inc., introduces geographic data services (such as geocoding and proximity matching) and discusses how they are employed in both operational and analytical business applications. The paper also reviews analytical techniques applied across many types of organizations and examines a number of industry-specific usage scenarios.
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location-based bi, business value, geographic enhancement
    
SAP
Published By: LeanData     Published Date: Oct 29, 2015
Leads mean everything to running a successful business. Managing those precious leads, though, also can be challenging. But LeanData has created a solution where leads always will get to the correct salespeople by automatically matching them to accounts with a speed and accuracy that’s impossible to duplicate manually at scale. This eBook explores the different ways that smart companies are using LeanData’s Router and Converter functions to get their leads to the right home so they can generate more pipeline and closed deals. The journey begins here.
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LeanData
Published By: IBM     Published Date: Nov 06, 2014
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
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big data, data integration, analytics, customer matching, ibm
    
IBM
Published By: IBM     Published Date: Jan 09, 2015
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
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ibm, big data, insights, infosphere, data management, dashboards, value, data matching, analytics, challenges, hadoop
    
IBM
Published By: IBM     Published Date: Jan 09, 2015
Early adopters of an extended 360° view will get competitive advantages over their rivals and this will force laggards to adopt a similar approach or lose business.
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ibm, big data, insights, mdm, infosphere, data management, dashboards, value, data matching, analytics, challenges, competitive advantage, loyalty, implementation, 360, degree, customers
    
IBM
Published By: IBM     Published Date: Apr 18, 2016
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
Tags : 
ibm, mdm, big data, data management, data matching, customer analytics
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
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customer analytics, data analysis, competitive advantage, understanding your customer base
    
IBM
Published By: HP     Published Date: Jul 08, 2009
Data is the backbone of every organization. No matter the business, industry, or size, reliable data access is essential to operations. Should a "worst-case scenario" occur, being prepared with an appropriate disaster recovery strategy is essential. Given the potential high cost associated with data loss, reliable data protection is no longer an option; rather, it is an obligation. This white paper discusses a data protection strategy that takes into consideration the business environment, offering sophisticated features while maintaining simplicity, affordability, and reliability.
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storage, data protection, reliability, reliable, disaster recovery, business protection, business continuity, storageworks, rto, rpo, recovery time objective, recovery point objective, tape, lan, san, das, direct attached storage, rdx, d2d, disk to disk
    
HP
Published By: IBM     Published Date: Dec 12, 2006
This paper gives the reader an overview of the functionality of IBM's WebSphere Customer Center, and explains why IBM is the strategic partner that more Fortune 500 companies select as their strategic platform for Customer Data Integration.
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cdi, customer data integration, data management, data integration, customer service, customer interaction service, websphere, name matching, ibm
    
IBM
Published By: SAP     Published Date: Jul 17, 2012
In spite of the growth of virtual business activities performed via the World Wide Web, every business transaction or operation is performed at a physical place. And as handheld GPS devices drive a growing awareness of the concept of "location," people are increasingly looking for operational efficiencies, revenue growth, or more effective management as a result of geographic data services and location-based intelligence. In this white paper, David Loshin, president of Knowledge Integrity, Inc., introduces geographic data services (such as geocoding and proximity matching) and discusses how they are employed in both operational and analytical business applications. The paper also reviews analytical techniques applied across many types of organizations and examines a number of industry-specific usage scenarios.
Tags : 
business, sap, white paper, technology, location, intelligence, business value, data services
    
SAP
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