databases

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By: Impetus     Published Date: Mar 15, 2016
Streaming analytics platforms provide businesses a method for extracting strategic value from data-in-motion in a manner similar to how traditional analytics tools operate on data-at rest. Instead of historical analysis, the goal with streaming analytics is to enable near real-time decision making by letting companies inspect, correlate and analyze data even as it flows into applications and databases from numerous different sources. Streaming analytics allows companies to do event processing against massive volumes of data streaming into the enterprise at high velocity.
Tags : impetus, guide to stream analytics, real time streaming analytics, streaming analytics, real time analytics, big data analytics
     Impetus
By: Dell and Intel®     Published Date: Aug 24, 2015
New technologies help decision makers gain insights from all types of data - from traditional databases to high-visibility social media sources. Big data initiatives must ensure data is cost-effectively managed, shared by systems across the enterprise, and quickly and securely made available for analysis and action by line-of-business teams. In this article, learn how Dell working with Intel® helps IT leaders overcome the challenges of IT and business alignment, resource constraints and siloed environments through a comprehensive big data portfolio based on choice and flexibility, redefined economics and connected intelligence.
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     Dell and Intel®
By: Datastax     Published Date: May 14, 2018
"What’s In The Report? The Forrester Graph Database Vendor Landscape discusses the expanding graph uses cases, new and emerging graph solutions, the two approaches to graph, how graph databases are able to provide penetrating insights using deep data relationships, and the top 10 graph vendors in the market today Download The Report If You: -Want to know how graph databases work to provide quick, deep, actionable insights that help with everything from fraud to personalization to go-to-market acceleration, without having to write code or spend operating budget on data scientists. -Learn the new graph uses cases, including 360-degree views, fraud detection, recommendation engines, and social networking. -Learn about the top 10 graph databases and why DSE Graph continues to gain momentum with customers who like its ability to scale out in multi-data-center, multi-cloud, and hybrid environments, as well as visual operations, search, and advanced security."
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     Datastax
By: Datastax     Published Date: May 14, 2018
Distributed cloud databases are transforming the way organizations do business. Read this new, informative guide to learn what distributed cloud databases are and why they’re what’s required to power Right-Now Economy applications. You'll also get straightforward yet detailed information on the database requirements for today’s applications, the limitations of relational databases, and the importance of data autonomy in database selection. With Designing a Distributed Cloud Database for Dummies, you'll learn how enterprises can meet and exceed customer expectations by way of modern applications and distributed cloud databases.
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     Datastax
By: Workday UK     Published Date: Mar 15, 2018
As May 25th, 2018 approaches, many of the organisations that I speak to are choosing to modernise their HR systems to help with their compliance efforts. In particular, where organisations have a complicated mix of different HR systems and spreadsheets, with employee data spread across different databases managed by multiple security models, GDPR compliance will be more difficult. Contrast such a complicated mix of HR systems with Workday’s unified, single system approach to HR, with a single source of HR data and a single security model, and you can see why organisations are choosing to move to Workday as they work to both modernise their HR systems and move towards GDPR compliance. We hope you find this research an i
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     Workday UK
By: CA Technologies EMEA     Published Date: May 23, 2018
To move your business from its current state to the connected enterprise, you have to define a common API to your database and other systems, while providing the infrastructure to support the new model. The new systems must incorporate the security safeguards while ensuring the infrastructure can support the new growing, but variable, load. With the rapid adoption of mobile and web-based services across the industry, the REST architecture has emerged as the de facto standard for API integration across systems. This white paper addresses the concepts of REST, creating REST APIs for your databases and integrating with other systems: • What is REST? • Why use REST for database access? • Building REST infrastructure for database access • The REST enabled database • Integrating REST with other services • Criteria for selecting REST services platform
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     CA Technologies EMEA
By: AWS - ROI DNA     Published Date: Jun 12, 2018
Traditional databases and data warehouses are evolving to capture new data types and spread their capabilities in a hybrid cloud architecture, allowing business users to get the same results regardless of where the data resides. The details of the underlying infrastructure become invisible. Self-managing data lakes automate the provisioning, reliability, performance and cost, enabling data access and experimentation.
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     AWS - ROI DNA
By: ASG Software Solutions     Published Date: Jun 09, 2009
Improved business productivity often requires more efficient IT and more efficient IT cannot be achieved without a better understanding of the way business services are run and delivered. Configuration Management Databases (CMDBs) have emerged as a central component for Information Technology Infrastructure Library (ITIL) and business service management (BSM).
Tags : asg, cmdb, bsm, itil, bsm, metacmdb, configuration management, metadata, metacmdb, lob, sdm, service dependency mapping, ecommerce, bpm, workflow, itsm, critical application, cms, itsm
     ASG Software Solutions
By: IBM     Published Date: Apr 13, 2018
Database security protects databases against compromises of their integrity, confidentiality and availability.
Tags : gdpr, compliance, data protection, personal data
     IBM
By: PCRecruiter     Published Date: Oct 28, 2010
Only a decade or so ago, those human resources professionals who hadn't yet found their way onto the Internet were finding themselves increasingly left out in the cold.As we slip swiftly into the second decade of the 21st century, it's those who haven't yet begun to participate in 'social media and networking' that are starting to feel the chill.
Tags : pcrecruiter, recruiting, social networking, network, facebook, twitter, email program, networking, databases
     PCRecruiter
By: PCRecruiter     Published Date: Oct 28, 2010
Only a decade or so ago, those human resources professionals who hadn't yet found their way onto the Internet were finding themselves increasingly left out in the cold. As we slip swiftly into the second decade of the 21st century, it's those whohaven't yet begun to participate in 'social media and networking' that are starting to feel the chill.
Tags : pcrecruiter, recruiting, social networking, network, facebook, twitter, email program, networking, databases
     PCRecruiter
By: SAP     Published Date: Mar 09, 2017
There’s strong evidence organizations are challenged by the opportunities presented by external information sources such as social media, government trend data, and sensor data from the Internet of Things (IoT). No longer content to use internal databases alone, they see big data resources augmented with external information resources as what they need in order to bring about meaningful change. According to a September 2015 global survey of 251 respondents conducted by Harvard Business Review Analytic Services, 78 percent of organizations agree or strongly agree that within two years the use of externally generated big data will be “transformational.” But there’s work to be done, since only 21 percent of respondents strongly agree that external data has already had a transformational effect on their firms.
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     SAP
By: HPE & Intel®     Published Date: Oct 10, 2016
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?
Tags : database, hpe, intel, data, oracle database, database management
     HPE & Intel®
By: SAP     Published Date: May 18, 2014
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
Tags : 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
By: SAP     Published Date: May 18, 2014
This white paper discusses the issues involved in the traditional practice of deploying transactional and analytic applications on separate platforms using separate databases. It analyzes the results from a user survey, conducted on SAP's behalf by IDC, that explores these issues.
Tags : 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
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.
Tags : database usage, database management, server usage, data protection
     Hewlett Packard Enterprise
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.
Tags : cost reduction, oracle database, it operation, online transaction, online analytics
     Hewlett Packard Enterprise
By: Hewlett Packard Enterprise     Published Date: Mar 26, 2018
Today’s data centers are expected to deploy, manage, and report on different tiers of business applications, databases, virtual workloads, home directories, and file sharing simultaneously. They also need to co-locate multiple systems while sharing power and energy. This is true for large as well as small environments. The trend in modern IT is to consolidate as much as possible to minimize cost and maximize efficiency of data centers and branch offices. HPE 3PAR StoreServ is highly efficient, flash-optimized storage engineered for the true convergence of block, file, and object access to help consolidate diverse workloads efficiently. HPE 3PAR OS and converged controllers incorporate multiprotocol support into the heart of the system architecture
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     Hewlett Packard Enterprise
By: Hewlett Packard Enterprise     Published Date: Mar 26, 2018
Modern storage arrays can’t compete on price without a range of data reduction technologies that help reduce the overall total cost of ownership of external storage. Unfortunately, there is no one single data reduction technology that fits all data types and we see savings being made with both data deduplication and compression, depending on the workload. Typically, OLTP-type data (databases) work well with compression and can achieve between 2:1 and 3:1 reduction, depending on the data itself. Deduplication works well with large volumes of repeated data like virtual machines or virtual desktops, where many instances or images are based off a similar “gold” master.
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     Hewlett Packard Enterprise
By: Dell     Published Date: May 04, 2018
Handle more orders with faster response times, today and tomorrow. Databases are often the driving force behind a company’s mission-critical work. They power online stores, confidential records, and customer management systems, so a solution that sustains high levels of database work can be a big advantage as your company grows. Download this summary from Dell EMC and Intel® to learn more. • Please add this tagline below the abstract in the same font size and above the trademark line: Intel Inside®. New Possibilities Outside. • Please use this trademark line at the bottom of the landing page: Intel and the Intel logo are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries.
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     Dell
By: Oracle CX     Published Date: Oct 19, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better
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     Oracle CX
By: Oracle CX     Published Date: Oct 19, 2017
The Software in Silicon design of the SPARC M7 processor, and the recently announced SPARC S7 processor, implement memory access validation directly into the processor so that you can protect application data that resides in memory. It also includes on-chip Data Analytics Accelerator (DAX) engines that are specifically designed to accelerate analytic functions. The DAX engines make in-memory databases and applications run much faster, plus they significantly increase usable memory capacity by allowing compressed databases to be stored in memory without a performance penalty. The following Software in Silicon technologies are implemented in the SPARC S7 and M7 processors: Note: Security in Silicon encompasses both Silicon Secured Memory and cryptographic instruction acceleration, whereas SQL in Silicon includes In-Memory Query Acceleration and In-Line Decompression. Silicon Secured Memory is the first-ever end-to-end implementation of memory-access validation done in hardware. It
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     Oracle CX
By: Oracle CX     Published Date: Oct 19, 2017
Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better
Tags : 
     Oracle CX
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
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
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