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Published By: TIBCO Software APAC     Published Date: Aug 13, 2018
Big data has raised the bar for data virtualization products. To keep pace, TIBCO® Data Virtualization added a massively parallel processing engine that supports big-data scale workloads. Read this whitepaper to learn how it works.
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TIBCO Software APAC
Published By: Workday     Published Date: Oct 11, 2018
Before Workday, Panera Bread’s payroll processes were manual, inefficient, and error-prone, and payroll nightmares and compliance risks were a regular occurrence. Complex systems and costly integrations made it impossible for the company to keep up with its rapid growth or gain valuable insights into global labor expenses. See the infographic to learn why unifying HR, payroll, time tracking, and absence management in a single system allows Panera to use one consistent, flexible, and scalable system across the U.S. and Canada.
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Workday
Published By: NEC     Published Date: Sep 29, 2009
Written by: IDC Abner Germanow, Jonathan Edwards, Lee Doyle IDC believes the convergence of communications and mainstream IT architectures will drive significant innovation in business processes over the next decade.
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it architecture, idc, automation, automated order processing, soa, service oriented architecture, soap, http, xml, wsdl, uddi, esbs, jee, .net, crm, san
    
NEC
Published By: Amazon Web Services     Published Date: Oct 12, 2018
Safeguarding your data is more important than ever. In today’s data-driven business landscape, companies are using their data to innovate, inform product improvements, and personalize services for their customers. The sheer volume of data collected for these purposes keeps growing, but the solutions available to organizations for processing and analyzing it become more efficient and intuitive every day. Reaching the right customers at the right time with the right offers has never been easier. With this newfound agility, however, comes new opportunities for vulnerability. With so much riding on the integrity of your data and the services that make it secure and available, it’s crucial to have a plan in place for unexpected events that can wipe out your physical IT environment or otherwise compromise data access. The potential for natural disasters, malicious software attacks, and other unforeseen events necessitates that companies implement a robust disaster recovery (DR) strategy to
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Amazon Web Services
Published By: Vision Solutions     Published Date: Feb 18, 2008
Continuous member service is an important deliverable for credit unions, and. the continued growth in assets and members means that the impact of downtime is affecting a larger base and is therefore potentially much more costly. Learn how new data protection and recovery technologies are making a huge impact on downtime for credit unions that depend on AIX-hosted applications.
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vision, high availability, ibm, aix, cdp, core union
    
Vision Solutions
Published By: SAS     Published Date: Aug 28, 2018
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
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SAS
Published By: SAP     Published Date: Feb 03, 2017
The SAP HANA platform provides a powerful unified foundation for storing, processing, and analyzing structured and unstructured data. It funs on a single, in-memory database, eliminating data redundancy and speeding up the time for information research and analysis.
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SAP
Published By: SAP     Published Date: Feb 03, 2017
The spatial analytics features of the SAP HANA platform can help you supercharge your business with location-specific data. By analyzing geospatial information, much of which is already present in your enterprise data, SAP HANA helps you pinpoint events, resolve boundaries locate customers and visualize routing. Spatial processing functionality is standard with your full-use SAP HANA licenses.
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SAP
Published By: Ricoh     Published Date: Oct 02, 2018
Your business is changing. As a finance leader, you know that accounting is a labour-intensive, costly process where systems often don’t allow for expedient exception handling and many days are fraught with difficulty in matching invoices to other databases for reconciliation. Like most companies, you know where you want to go but may not have infrastructure or internal expertise to handle electronic fund transfers, credit card payments or cheque processing— all the pieces required to make your vision for an efficient, integrated operation a reality.
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Ricoh
Published By: Cisco EMEA Tier 3 ABM     Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
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big data, analytics, virtualization, cloudera, ibm, sas, sap, splunk
    
Cisco EMEA Tier 3 ABM
Published By: SAP     Published Date: May 18, 2014
In-memory technology—in which entire datasets are pre-loaded into a computer’s random access memory, alleviating the need for shuttling data between memory and disk storage every time a query is initiated—has actually been around for a number of years. However, with the onset of big data, as well as an insatiable thirst for analytics, the industry is taking a second look at this promising approach to speeding up data processing.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
    
SAP
Published By: Hewlett Packard Enterprise     Published Date: Aug 02, 2017
In midsize and large organizations, critical business processing continues to depend on relational databases including Microsoft® SQL Server. While new tools like Hadoop help businesses analyze oceans of Big Data, conventional relational-database management systems (RDBMS) remain the backbone for online transaction processing (OLTP), online analytic processing (OLAP), and mixed OLTP/OLAP workloads.
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database usage, database management, server usage, data protection
    
Hewlett Packard Enterprise
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: Cisco     Published Date: Jun 21, 2016
The Cisco® Hyperlocation Solution is the industry’s first Wi-Fi network-based location system that can help businesses and users pinpoint a user’s location to within one to three meters, depending on the deployment. Combining innovative RF antenna and module design, faster and more frequent data processing, and a powerful platform for customer engagement, it can help businesses create more personalized and profitable customer experiences.
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Cisco
Published By: Pentaho     Published Date: Feb 26, 2015
This eBook from O’Reilly Media will help you navigate the diverse and fast-changing landscape of technologies for processing and storing data (NoSQL, big data, MapReduce, etc).
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data systems, data-intensive applications, scalability, maintainability, data storage, application development
    
Pentaho
Published By: OpenText     Published Date: Mar 02, 2017
Watch the video to learn how Procure-to-Pay (P2P) solutions automate B2B processes to help you gain better visibility into transaction lifecycles, improve efficiency, and increase the speed and accuracy of order, shipping, and invoice processing.
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supply chain, b2b, procure-to-pay, shipping, invoicing
    
OpenText
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Big data alone does not guarantee better business decisions. Often that data needs to be moved and transformed so Insight Platforms can discern useful business intelligence. To deliver those results faster than traditional Extract, Transform, and Load (ETL) technologies, use Matillion ETL for Amazon Redshift. This cloud- native ETL/ELT offering, built specifically for Amazon Redshift, simplifies the process of loading and transforming data and can help reduce your development time. This white paper will focus on approaches that can help you maximize your investment in Amazon Redshift. Learn how the scalable, cloud- native architecture and fast, secure integrations can benefit your organization, and discover ways this cost- effective solution is designed with cloud computing in mind. In addition, we will explore how Matillion ETL and Amazon Redshift make it possible for you to automate data transformation directly in the data warehouse to deliver analytics and business intelligence (BI
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Amazon Redshift Spectrum—a single service that can be used in conjunction with other Amazon services and products, as well as external tools—is revolutionizing the way data is stored and queried, allowing for more complex analyses and better decision making. Spectrum allows users to query very large datasets on S3 without having to load them into Amazon Redshift. This helps address the Scalability Dilemma—with Spectrum, data storage can keep growing on S3 and still be processed. By utilizing its own compute power and memory, Spectrum handles the hard work that would normally be done by Amazon Redshift. With this service, users can now scale to accommodate larger amounts of data than the cluster would have been capable of processing with its own resources.
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Amazon Web Services
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: Infosys     Published Date: May 30, 2018
Customers today are far more concerned about the contents and origin of a product than ever before. in such a scenario, granting them easy access to product information, via digital initiatives such as SmartLabel™, goes a long way in strengthening customer trust in a brand. But it also means expending several man-hours of effort processing unstructured data, with the possibility of human error. Intelligent automation can help save effort and time, with virtually error-free results. A consumer products conglomerate wanted a smart solution to implement SmartLabel™ compliance. See how Infosys helped and the five key takeaways from the project.
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automation, brand, information, digital, customer
    
Infosys
Published By: IBM APAC     Published Date: Apr 27, 2018
While relying on x86 servers and Oracle databases to support their stock trading systems, processing rapidly increasing number of transactions fast became a huge challenge for Wanlian Securities. They shifted to IBM FlashSystem that helped them cut average response time for their Oracle Databases from 10 to less than 0.4 milliseconds and improved CPU usage by 15%. Download this case study now.
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IBM APAC
Published By: Dome9     Published Date: Apr 25, 2018
As of May 2017, according to a report from The Depository Trust & Clearing Corporation (DTCC), which provides financial transaction and data processing services for the global financial industry, cloud computing has reached a tipping point1. Today, financial services companies can benefit from the capabilities and cost efficiencies of the cloud. In October of 2016, the Federal Deposit Insurance Corporation (FDIC), the Office of the Comptroller of Currency (OCC) and the Federal Reserve Board (FRB) jointly announced enhanced cyber risk management standards for financial institutions in an Advanced Notice of Proposed Rulemaking (ANPR)2. These proposed standards for enhanced cybersecurity are aimed at protecting the entire financial system, not just the institution. To meet these new standards, financial institutions will require the right cloud-based network security platform for comprehensive security management, verifiable compliance and governance and active protection of customer data
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Dome9
Published By: Oracle     Published Date: Aug 09, 2018
The purpose of IT backup and recovery systems is to avoid data loss and recover quickly, thereby minimizing downtime costs. Traditional storage-centric data protection architectures such as Purpose Built Backup Appliances (PBBAs), and the conventional backup and restore processing supporting them, are prone to failure on recovery. This is because the processes, both automated and manual, are too numerous, too complex, and too difficult to test adequately. In turn this leads to unacceptable levels of failure for today’s mission critical applications, and a poor foundation for digital transformation initiatives. Governments are taking notice. Heightened regulatory compliance requirements have implications for data recovery processes and are an unwelcome but timely catalyst for companies to get their recovery houses in order. Onerous malware, such as ransomware and other cyber attacks increase the imperative for organizations to have highly granular recovery mechanisms in place that allow
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Oracle
Published By: IBM APAC     Published Date: Nov 22, 2017
Using IBM Watson’s cognitive capabilities, companies can quickly differentiate their customer service quality by being more pro active and responsive to customer needs. Simply put, chatbots and virtual agents are the future of customer interactions. Building apps from scratch that incorporate natural language processing, speech to text recognition, visual recognition, analytics, and artificial intelligence requires broad expertise in these disciplines, large staffs, and a huge financial commitment. Making use of IBM Watson cognitive services brings these capabilities in-house quickly and without the capital investment that would be needed to develop the technologies within an organization.
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decision making, deeper data, insights, cognitive, analytics, ibm, watson, virtual agents
    
IBM APAC
Published By: IBM APAC     Published Date: Nov 22, 2017
AlchemyAPI’s approach to natural language processing incorporates both linguistic and statistical analysis techniques into a single unified system. This hybrid approach provides an industry-leading advantage since both techniques have benefits and drawbacks depending on the content and specific usecases. Linguistic analysis takes a basic grammatical approach to understand how words combine into phrases, and how those phrases combine into sentences. While this approach works well with editorialized text (e.g., news articles and press releases), it does not perform as well when it comes to usergenerated content, often filled with slang, misspellings and idioms. Statistical analysis, however, understands language from a mathematical standpoint and works well on “noisy” content (e.g., tweets, blog posts, and Facebook status updates). The combination of these two approaches allows for increased accuracy on a variety of content.
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industry, advantage, linguistic, grammatical, statistical analysis, content
    
IBM APAC
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