transaction data

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Published By: Oracle     Published Date: Mar 22, 2018
s your information technology (IT) organization pressured to get more work done with fewer people or on a constricted budget? Do you need to make IT a competitive asset rather than a cost center? Does your business struggle with slow software applications or data that's too often unavailable? If you answered "yes" to any of these questions, it's time to take a close look at Oracle Exadata, the world's fastest database machine exclusively designed to run Oracle Database. It is the first database machine optimized for data warehousing, online transaction processing (OLTP), and database consolidation workloads as well as in-memory databases and database as a service (DBaaS).
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Oracle
Published By: IBM     Published Date: Aug 06, 2014
Customer Profitability Analytics enables banks to analyze customer, account, product, and transaction data and apply costing models to determine a bank-wide view of profitability. Applying predictive analytics, they can model future behavior and derive a lifetime value for each customer.
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ibm, banking, customer, profit, analytics, costing models
    
IBM
Published By: IBM     Published Date: Jul 22, 2016
You’ll learn: - About the mandates that will significantly increase transaction complexity and transaction volumes for payers and providers - How to reduce costs and improve processing efficiencies while also decreasing the risk associated with data movement - Ways to improve customer service and ensure compliance with evolving regulations while reducing IT operating expenses
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ibm, healthcare, affordable care act, b2b, hipaa, edi regulations, knowledge management, enterprise applications, business technology
    
IBM
Published By: IBM     Published Date: Mar 30, 2017
To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize its value, and integrate it at a more granular level than ever before—focusing on the individual transaction level, rather than on general summary data. As data volumes continue to explode, clients must take advantage of a fully scalable information integration architecture that supports any type of data integration technique such as extract, transfer and load (ETL), data replication or data virtualization.
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data integration, data security, data optimization, data virtualization, database security
    
IBM
Published By: Datastax     Published Date: Aug 27, 2018
" For any business that wants to successfully compete in today’s digital economy, it is not a question of if but rather how much of their business will be done with cloud applications. A cloud application is one with many endpoints including browsers, mobile devices, and/or machines that are geographically distributed. The application is intensely transactional (high velocity reads and/or writes), always available, and instantaneously responsive no matter the number of users or machines using the application. Download this free white paper and explore how DataStax customers are delivering real-time value at epic scale with their cloud applications. Explore the core database requirements that make businesses successful with cloud applications, which include continuous availability, linear scale, and geographic distribution."
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Datastax
Published By: Q2 eBanking     Published Date: Jul 30, 2017
Many financial institutions see their customer data as one of their most valuable assets. Unlocking insights from that data helps FIs understand, anticipate and offer account holders the products and services they truly need. A major trend to unlocking customer insights is using machine learning to surface the behavioral intelligence buried in the large amount of account holder transactional data captured each and every day. In this paper, learn how a group of talented, enthusiastic analysts with an open approach to data can yield some very interesting and extremely valuable and actionable results. This approach, championed by Q2 Executive Vice President and CTO Adam Anderson, has led to a new platform, Q2 SMART, which provides powerful behavioral analytics for financial institutions, enabling growth while providing account holders with real value.
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Q2 eBanking
Published By: Fiserv     Published Date: Jul 09, 2018
Even with the rise of digital payments, cash is still a popular form of payment. According to the Federal Reserve, consumers use cash to pay for nearly one-third of all retail transactions. For many retailers, a completely "cashless society" is nowhere in sight. Cash management remains one of the most important aspects of managing a retail operation, particularly at quick service restaurants (QSRs) and convenience stores, where transactions are smaller and cash is a preferred method of payment. This white paper, Boost Profitability by Automating Cash, sponsored by Fiserv and Fast Casual, details the steps to manage cash properly and boost profit for your business. Uncover the top reasons and flexible options to automate your cash management. • Time savings • Theft deterrence • Higher accuracy • Better customer service • Real-time data
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cash automation, smart safe, cash loss, cash handling, automated cash handling, cash management, cash reconciliation, manual cash reconciliation, automated cash reconciliation, automated vault, cash counting, cash automation system, cash deposits, cash recycler, cash dispensers, cash drawer, point of sale
    
Fiserv
Published By: Oracle     Published Date: Jan 09, 2019
The Accenture Oracle data team has more than 20,000 professionals, who aid in delivering 50 billion transactions a day across more than three exabytes of data for clients globally. Accenture Oracle data specialists recently put the Oracle Autonomous Data Warehouse to a rigorous performance test to provide a real-life application usage experience. The data was then extrapolated and expanded to nine years’ worth of data to test the performance. Learn directly from Accenture experts about testing methodology and results that enable them to deliver more data intelligence faster to the enterprise and transform the way people live and work.
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Oracle
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
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