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Published By: Group M_IBM Q1'18     Published Date: Jan 23, 2018
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
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db2. blu accelaration, big data, data analytics, disaster recovery
    
Group M_IBM Q1'18
Published By: SAS     Published Date: Jan 17, 2018
The Connected Customer is an individual who is intimately connected to the data, outcomes, decisions, and staff associated with any relationship to an organization. This intensely personal connection is not just a matter of the most recent transaction, but represents a combination of connected data, connected analytics, and collaborative decisions associated with improving the customer’s relationship with the organization over time. In this report, Blue Hill explores the key traits associated with supporting the Connected Customer through the Internet of Things, and provides guidance on why the Internet of Things will be essential across the general business landscape.
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SAS
Published By: MuleSoft     Published Date: Jan 16, 2018
“Today’s shoppers expect more than a transactional relationship with retailers; they want a seamless and personalized journey that reflects the context of how they shop across devices and channels. The key to success lies in connecting in-store software with online systems so retailers can provide an uninterrupted experience wherever customers shop.” - Ross Mason, Founder of MuleSoft Driving digital transformation in retail requires connectivity across an ever-increasing number of applications, data and devices. Because of this, connectivity has emerged as a bottleneck that slows the development of new applications and the adoption of new technologies to meet customer demands. In response, leading retail and CPG companies have adopted API-led connectivity, which eliminates this connectivity bottleneck and enables a 2-5x faster IT project delivery across the value chain. Download this eBook to learn: How leading retailers like Buffalo Wild Wings, TAL Apparel and PetSmart are leverag
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MuleSoft
Published By: Oracle ZDLRA     Published Date: Jan 10, 2018
Traditional backup systems fail to meet the database protection and recovery requirements of modern organizations. These systems require ever-growing backup windows, negatively impact performance in mission-critical production databases, and deliver recovery time objectives (RTO) and recovery point objectives (RPO) measured in hours or even days, failing to meet the requirements of high-volume, high transactional databases -- potentially costing millions in lost productivity and revenue, regulatory penalties, and reputation damage due to an outage or data loss.
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data protection, backup speed, recovery, overhead, assurance, storage, efficiency, oracle
    
Oracle ZDLRA
Published By: SAP     Published Date: Nov 16, 2017
The SAP HANA platform has successfully become a proven mainstay data management solution, supporting the full range of analytic and transactional software from SAP, both in the data center and in the cloud.
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SAP
Published By: IBM     Published Date: Nov 08, 2017
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
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ibm, cloud, cloud computing, database, ibm db2
    
IBM
Published By: Oracle     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Traditional backup systems fail to meet the needs of modern organizations by focusing on backup, not recovery. They treat databases as generic files to be copied, rather than as transactional workloads with specific data integrity, consistency, performance, and availability requirements. Additionally, highly regulated industries, such as financial services, are subject to ever?increasing regulatory mandates that require stringent protection against data breaches, data loss, malware, ransomware, and other risks. These risks require fiduciary?class data recovery to eliminate data loss exposure and ensure data integrity and compliance
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Oracle
Published By: Oracle CX     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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Oracle CX
Published By: Oracle CX     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle CX
Published By: Datastax     Published Date: Aug 23, 2017
Banks deal with mountains of data and complex transactions that far too often don’t capitalize on the power of an always-on, real-time data management platform to provide both financial insights and peace of mind. Today’s cloud applications require a new, far more holistic approach to data management and data protection. This eBook explains why the scalability, 100% availability, enterprise-grade security, and real-time insights of DataStax Enterprise are essential for banking in the modern world.
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transactions, modernizing, financial insights, data management
    
Datastax
Published By: CA Technologies     Published Date: Aug 22, 2017
Effectively supporting these new business demands has become more complex and challenging. The increased use of mobile devices alone is driving exponential growth in transaction volumes. A customer pushes a button on his or her cell phone, for example, to check a bank balance. That single transaction triggers a cascade of transactions as the request is validated and data is accessed, retrieved and then sent back to the customer.
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storage, systems, network, applications, data, automation, ca technologies
    
CA Technologies
Published By: Hewlett Packard Enterprise     Published Date: Aug 02, 2017
What if you could reduce the cost of running Oracle databases and improve database performance at the same time? What would it mean to your enterprise and your IT operations? Oracle databases play a critical role in many enterprises. They’re the engines that drive critical online transaction (OLTP) and online analytical (OLAP) processing applications, the lifeblood of the business. These databases also create a unique challenge for IT leaders charged with improving productivity and driving new revenue opportunities while simultaneously reducing costs.
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cost reduction, oracle database, it operation, online transaction, online analytics
    
Hewlett Packard Enterprise
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: CA Technologies     Published Date: Jul 20, 2017
Mainframes continue to provide high business value by combining efficient transaction processing with high-volume access to critical enterprise data. Business organizations are linking mobile devices to mainframe processing and data to support digital applications and drive business transformation. In this rapidly growing scenario, the importance of providing excellent end-user experience becomes critical for business success.This analyst announcement note covers how CA Technologies is addressing the need for providing high availability and a fast response time by optimizing mainframe performance with new machine learning and analytics capabilities.
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CA Technologies
Published By: Coupa Software Inc.     Published Date: Jul 10, 2017
Many companies think of their accounts payable (AP) department as a transactional function—it’s essential to your operation, but too often it’s weighed down with people-heavy paper processes. If your AP department is focused on data entry and resolving escalations, you’re missing a valuable business opportunity.
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coupa, accounts payable, capital management, finance, eprocurement, suppliers, business technology
    
Coupa Software Inc.
Published By: IBM     Published Date: Jul 06, 2017
DB2 is a proven database for handling the most demanding transactional workloads. But the trend as of late is to enable relational databases to handle analytic queries more efficiently by adding an inmemory column store alongside to aggregate data and provide faster results. IBM's BLU Acceleration technology does exactly that. While BLU isn't brand new, the ability to spread the column store across a massively parallel processing (MPP) cluster of up to 1,000 nodes is a new addition to the technology. That, along with simpler monthly pricing options and integration with dashDB data warehousing in the cloud, makes DB2 for LUW, a very versatile database.
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memory analytics, database, efficiency, acceleration technology, aggregate data
    
IBM
Published By: Oracle     Published Date: Jul 05, 2017
Your company’s website is up. Servers are churning transactions. The network is pumping data. Life is good. But everything in IT can change quickly. Today’s slightly sluggish network could become tomorrow’s downtime disaster. No matter what challenge may arise, you don’t get extra time, staff, or budget to deal with it. Plus, since the whole company relies on IT, everyone notices when you’re underwater.
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revenue loss, tarnish brand, consumer confidence, dns services, high performing networks, workflow, dns
    
Oracle
Published By: TopQuadrant     Published Date: Jun 01, 2017
This paper presents a practitioner informed roadmap intended to assist enterprises in maturing their Enterprise Information Management (EIM) practices, with a specific focus on improving Reference Data Management (RDM). Reference data is found in every application used by an enterprise including back-end systems, front-end commerce applications, data exchange formats, and in outsourced, hosted systems, big data platforms, and data warehouses. It can easily be 20–50% of the tables in a data store. And the values are used throughout the transactional and mastered data sets to make the system internally consistent.
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TopQuadrant
Published By: IBM     Published Date: May 26, 2017
Business executives and managers at business-to-business (B2B) enterprises care about time, money, competitive advantage, customer loyalty and growth. Few pay much attention to the vital IT infrastructure that supports transactions and collaboration with trading partners—though that B2B backbone directly affects performance and profitability. In fact, just 26 percent of business managers view B2B integration as a competitive differentiator, according to a study for IBM by Vanson Bourne, a research consultancy. As a result, many enterprises continue to utilize manual and error-prone emails, faxes and file transfers for B2B transactions. Reliance on complex, brittle and antiquated systems to exchange critical data impacts time to market, cost-efficiency and satisfaction across suppliers and end-customers. Modernization of B2B integration in recent years has moved forward in fits and starts, often undermined by competing priorities and misalignment between business and IT managers.
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b2b integration, customer loyalty, ibm, customer growth
    
IBM
Published By: IBM     Published Date: May 23, 2017
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
Tags : 
cloud strategy, database projects, disaster recover, geographic reach, large database, ibm, analytics, management optimization
    
IBM
Published By: Oracle     Published Date: May 03, 2017
Traditional backup systems fail to meet the needs of modern organisations by focusing on backup, not recovery. They treat databases as generic files to be copied, rather than as transactional workloads with specific data integrity, consistency, performance, and availability requirements.
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Oracle
Published By: Entrust Datacard     Published Date: Apr 26, 2017
Research in the SSL/TLS security market points to a growing need for securing web applications with high assurance certificates issued by a reputable Certification Authority (CA). The integrity of the CA and the extended services offered through a certificate management platform (CtaaS) can produce a truly secure IT environment for website transactions according to industry analysts, Frost & Sullivan, in their in-depth analysis, SSL/TLS Certificates Market, Finding the Business Model in an All Encrypt World. Organizations want to avoid the negative publicity associated with security breaches and customers want to be assured of data protection when making online transactions. In this condensed report, catch the highlights of current industry trends and the ever important need to secure your server with a reputable CA.
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Entrust Datacard
Published By: Dynatrace     Published Date: Apr 26, 2017
It's impossible to optimize every page and action of every transaction for every device and user location...you need to identify the pages and actions that matter most and build an optimization plan. This report details how T-Mobile did exactly that, and how you can do the same: Base your plan on your own business and visitor data Correlate performance to transaction completion rate Determine where you'll see the most return for your technology and time investment Download the report to read more.
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digital experience, digital experience monitoring
    
Dynatrace
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