data base manag

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Published By: Datastax     Published Date: Jun 20, 2019
A Gartner survey found that 80% of respondents using public cloud are using more than one cloud service provider. This report assesses the shift to multicloud architecture, challenges being faced by data and analytics leaders, and the growing need for database management technology that enables integration of data across multiple clouds.
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Datastax
Published By: Infosys     Published Date: Jun 14, 2019
The basic promise of blockchain is that it works as a global distributed ledger or database of things we value - everything from money, to creative work and votes - so these can then be managed and transacted in a trusted and secure manner. Yes, blockchain is a young technology, but well past its infancy. Today, the somewhat inflated expectations around the technology have been brought to a more realistic level and we are beginning to see practical applications across the enterprise. Although these are typically in the realm of reducing cost and/or time for transactions, improving product and system security, finding and preventing fraud and counterfeiting and increasing transparency, there are also instances of businesses relying on blockchain to create new revenue streams. Infosys recently commissioned an independent survey of senior executives worldwide. Download the report to read about their findings.
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Infosys
Published By: Oracle     Published Date: Jun 04, 2019
Finance leaders believe data management is a burden on businesses. Yet less than half of organisations have a data management strategy in place. But data management strategies positively impact security across all lines of business. Poor data management practices inevitably lead to poor outcomes, with bad decisions based on bad data. Data must also be protected, with weak practices leading to cyber breaches. And the reputational damage to an organisation’s brand cannot be underestimated. However, when managed well, data offers a competitive advantage. In the past, data was typically informed historical reporting, with internal needs and compliance taking priority. There is a new data paradigm. Data is the new currency in the digital age.
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Oracle
Published By: Oracle     Published Date: May 08, 2019
Oracle DBAs Share Insights about the Future of Cloud, Security, Artificial Intelligence, and Autonomous Computing. This year, in addition to canvasing analysts, pundits, and executives for their strategic insights, Oracle is interested in the tactical views, predictions, and opinions of master DBAs, database product experts, and Oracle ACE Directors. We gathered insights about database management, security, artificial intelligence, autonomous computing, and many other topics and cover how future trends will impact DBA careers during 2019, and beyond. The Intelligent Enterprise Era. Download predictions.
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Oracle
Published By: Oracle     Published Date: May 08, 2019
What if your database could install, manage, secure, and upgrade itself—with little or no manual administration required? Now it’s possible, thanks to machine learning, artificial intelligence and the power of the cloud. Discover how the Oracle Autonomous Database is: • Self-driving: Tell it the service level you want to achieve, and it does the rest. • Self-securing: It installs patches automatically and uses AI to counter threats. • Self-repairing: It patches, scales, and tunes itself while your operations are running, to deliver 99.995% uptime. Discover the power of autonomous data management. Download now.
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Oracle
Published By: Oracle EMEA     Published Date: Apr 15, 2019
Oracle Autonomous Data Warehouse Cloud is more than just a new way to store and analyze data; it’s a whole new approach to getting more value from your data. Market leaders in every industry depend on analytics to reach new customers, streamline business processes, and gain a competitive edge. Data warehouses remain at the heart of these business intelligence (BI) initiatives, but traditional data-warehouse projects are complex undertakings that take months or even years to deliver results. Relying on a cloud provider accelerates the process of provisioning data-warehouse infrastructure, but in most cases database administrators (DBAs) still have to install and manage the database platform, then work with the line-of-business leaders to build the data model and analytics. Once the warehouse is deployed—either on premises or in the cloud—they face an endless cycle of tuning, securing, scaling, and maintaining these analytic assets. Oracle has a better way. Download this whitepaper to f
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Oracle EMEA
Published By: Intel     Published Date: Apr 11, 2019
The Internet of Things (IoT) unleashes valuable business insights through data that’s gathered at every level of a retail organization. With IoT and data analytics, retailers now have the capability to gather insight into customer behavior, offer more personalized experiences, achieve better inventory accuracy, create greater supply chain efficiencies, and so much more. But with data comes great risk. A recent report by security firm Thales and 451 Research found that 43 percent of retailers have experienced a data breach in the past year, with a third reporting more than one breach.1 Intel® technology-based gateways and Asavie, a provider of next-gen enterprise mobility management and IoT connectivity solutions, offer a security connectivity solution that minimizes the effort and cost to businesses to ensure safety from cybersecurity attacks. In addition, the Intel/Asavie IoT solution provides retailers with a solid basis to build their smart, connected projects:
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Intel
Published By: Datastax     Published Date: Apr 08, 2019
For decades, organizations relied on traditional relational database management systems (RDBMS) to organize, store, and analyze their data. But then Facebook came along, and an RDBMS was suddenly not quite enough. The social giant needed a powerful database solution for its Inbox Search feature, and Apache Cassandra—a distributed NoSQL database—was born. Released as an open source project in July 2008, Cassandra—named after the mythological prophet who famously put a curse on an oracle—became an Apache Incubator project in March 2009. It graduated to a top-level project in February 2010
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Datastax
Published By: Apstra     Published Date: Feb 21, 2019
Modern data centers based on hyperscale, leaf-spine switching architectures are growing so large and complex they are outstripping the capacity of operators to engineer, configure and manage these networks using traditional tools and techniques. As a result, data center operators are looking for new ways to automate workflows, maximize uptime and increase operational agility while reducing operating costs
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acg, data center efficiency
    
Apstra
Published By: Larsen & Toubro Infotech(LTI)     Published Date: Feb 18, 2019
The largest national multiline insurance had built a repository of Insurance policies (P&C and Life Insurance) on Microfilm and Microfiche in early 90’s, as a preservation strategy. They were grappling with issues as this technology became outdated over time: • Risk of losing their only source of data for Insurance policies and corresponding communication, need to improve data availability and speed of claims evaluation • Compliance issues, need of a WORM (write once read many) storage compliant with FINRA regulations, where data should be encrypted when at rest • Total cost for digitization compared to 10-12 years of support left to maintain insurance policies was not very encouraging • Required a low cost, cloud-based, FINRA-compliant document management solution which could provide quick access to stored data Download complete case study to know how LTI’s e-Office sDownload full case study to know how LTI’s e-Office solution enabled 50% TCO for Largest national Multiline Insurance.
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Larsen & Toubro Infotech(LTI)
Published By: SAS     Published Date: Jan 30, 2019
Machine learning systems don’t just extract insights from the data they are fed, as traditional analytics do. They actually change the underlying algorithm based on what they learn from the data. So the “garbage in, garbage out” truism that applies to all analytic pursuits is truer than ever. Few companies are already using AI, but 72 percent of business leaders responding to a PWC survey say it will be fundamental in the future. Now is the time for executives, particularly the chief data officer, to decide on data management strategy, technology and best practices that will be essential for continued success.
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SAS
Published By: Oracle     Published Date: Jan 28, 2019
Databases tend to hold an organization’s most important information and power the most crucial applications. It only makes sense, then, to run them on a system that’s engineered specifically to optimize database infrastructure. Yet some companies continue to run their databases on do-it-yourself (DIY) infrastructure, using separate server, software, network, and storage systems. It’s a setup that increases risk, cost, complexity, and time spent deploying and managing the systems, given that it typically involves at least three different IT groups.
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Oracle
Published By: Claravine     Published Date: Jan 03, 2019
Marketers have long struggled with the simple task of knowing which marketing spend is truly effective, and how to optimize that spend. At the heart of the issue lies the challenge of ensuring the data quality and consistency exists to make decisions based on real intelligence. Why is this a problem? First, effective tracking is reliant on the consistent, complete application of campaign tracking codes and associated metadata, which has traditionally been a manual, ungoverned process. Adding to this complexity has been the dramatic expansion of digital marketing point solutions, and the disparate teams expected to execute across each of these channels and geographies. The result is what you would expect—highly inaccurate, incomplete, and inconsistent data that must be manually cleaned before reporting is possible. Fortunately a solution exists. Progressive marketing leaders are implementing Digital Experience Data Management (DXDM), ensuring the rich, consistent insights critical to ma
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Claravine
Published By: Datastax     Published Date: Dec 27, 2018
This paper examines the challenges banks face when creating a 360-degree view of every customer interaction, what database requirements the lines of business (LOBs) should look into, and use cases where retail banking LOBs can benefit from leveraging DataStax Enterprise, the data management platform purpose-built to power cloud applications.
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Datastax
Published By: AWS     Published Date: Nov 28, 2018
Financial institutions run on data: collecting it, analyzing it, delivering meaningful insights, and taking action in real time. As data volumes increase, organizations demand a scalable analytics platform that can meet the needs of data scientists and business users alike. However, managing an on-premises analytics environment for a large and diverse user base can become time-consuming, costly, and unwieldy. Tableau Server on Amazon Web Services (AWS) is helping major Financial Services organizations shift data visualization and analytics workloads to the cloud. The result is fewer hours spent on manual work and more time to ask deeper questions and launch new data analyses, with easily-scalable support for large numbers of users. In this webinar, you’ll hear how one major asset management company made the shift to cloud data visualization with Tableau Server on AWS. Discover lessons learned, best practices tailored to Financial Services organizations, and starting tactics for scalable analytics on the cloud.
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AWS
Published By: AWS     Published Date: Nov 12, 2018
If your organization runs VMware vSphere-based cloud infrastructure in your on-premises data center, but you have been reluctant to migrate applications to the cloud for fear of losing some VMware vSphere-based cloud capabilities, VMware Cloud on AWS solves this problem by seamlessly integrating your familiar VMware virtualization and cloud management tools with Amazon Web Services (AWS). Many organizations believe that moving their applications to the cloud makes it necessary to introduce new tools, skills, and processes. This can present a new set of challenges because learning to use new tools, applying new skills, and adapting to new processes can be costly and time-consuming. In this eBook, we dive deeper into how these challenges can hinder hybrid cloud adoption and cover how VMware Cloud on AWS can help your organization overcome these challenges. Join our webinar to learn The benefits of Disaster Recovery-as-a-Service (DRaaS), delivering on-site protection. How automated or
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AWS
Published By: AWS     Published Date: Nov 12, 2018
If your organization runs VMware vSphere-based cloud infrastructure in your on-premises data center, but you have been reluctant to migrate applications to the cloud for fear of losing some VMware vSphere-based cloud capabilities, VMware Cloud on AWS solves this problem by seamlessly integrating your familiar VMware virtualization and cloud management tools with Amazon Web Services (AWS). Many organizations believe that moving their applications to the cloud makes it necessary to introduce new tools, skills, and processes. This can present a new set of challenges because learning to use new tools, applying new skills, and adapting to new processes can be costly and time-consuming. In this eBook, we dive deeper into how these challenges can hinder hybrid cloud adoption and cover how VMware Cloud on AWS can help your organization overcome these challenges. Join our webinar to learn How to take advantage of flexible consumption models to align hybrid cloud adoption with your business
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AWS
Published By: NetApp     Published Date: Oct 12, 2018
Big data needs both high availability and protection. The amount of data created and replicated globally is predicted to increase ten-fold by 2025, according to IDC research. You may be wondering where to store that big data, as well as how to ensure your data is highly available and protected. In this eBook, explore why cloud-based disaster recovery (DR) improves data availability, eases the processes associated with DR management, and creates a more economically efficient solution for today’s data-driven companies.
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NetApp
Published By: ServiceNow     Published Date: Sep 18, 2018
What is a performance based business? A performance-based business is an organization guided by data-driven decisions. It is proactive, self-aware, and highly competitive. Data isn’t siloed in a business analytics department. Instead, the right people have the right data at the right time and in the right context. The top 5 reasons to become a performance-based business: 1. Get better results. 2. Align your entire business. 3. Make data-driven decisions. 4. Manage change more effectively. 5. Spot trends faster. Discover how ServiceNow Performance Analytics could benefit your business by downloading this eBook.
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performance, business, data, servicenow
    
ServiceNow
Published By: CA Technologies EMEA     Published Date: Sep 11, 2018
The advent of cloud computing and software-defined data center architectures for modern application delivery has made networking more sensitive than ever before. Applications in the digital age require networks that can expand and contract dynamically based on consumer demand. Enterprises are implementing software-defined networking (SDN) to deliver the automation required by these new environments, but the dynamic nature of SDN makes network management and monitoring fundamentally more challenging. Network infrastructure teams need monitoring tools that can provide visibility into these new and constantly changing networks. This white paper explores the importance of SDN monitoring and examines a leading example of a solution, CA Performance Management with CA Virtual Network Assurance integration.
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CA Technologies EMEA
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Amazon Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. Organizations choose Amazon Redshift for its affordability, flexibility, and powerful feature set: • Enterprise-class relational database query and management system • Supports client connections with many types of applications, including business intelligence (BI), reporting, data, and analytics tools • Execute analytic queries in order to retrieve, compare, and evaluate large amounts of data in multiple-stage operations
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Amazon Web Services
Published By: SAS     Published Date: Aug 28, 2018
Machine learning systems don’t just extract insights from the data they are fed, as traditional analytics do. They actually change the underlying algorithm based on what they learn from the data. So the “garbage in, garbage out” truism that applies to all analytic pursuits is truer than ever. Few companies are already using AI, but 72 percent of business leaders responding to a PWC survey say it will be fundamental in the future. Now is the time for executives, particularly the chief data officer, to decide on data management strategy, technology and best practices that will be essential for continued success.
Tags : 
    
SAS
Published By: Datastax     Published Date: Aug 07, 2018
Relational databases had their day and are still viable for certain use cases, but the advent of the cloud and subsequent proliferation of cloud applications is putting an almost unmanageable burden on their capabilities. Read this eBook to learn why your RBMS fails at scale, and why it's no longer a viable option for today's distributed, super fast-paced, cloud-friendly world.
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Datastax
Published By: Microsoft     Published Date: Jul 20, 2018
Microsoft provides a solution to easily run small segments of code in the cloud with Azure Functions. Azure Functions provides solutions for processing data, integrating systems, and building simple APIs and microservices. The book starts with intermediate-level recipes on serverless computing along with some use cases on the benefits and key features of Azure Functions. Then, we'll deep dive into the core aspects of Azure Functions, such as the services it provides, how you can develop and write Azure Functions, and how to monitor and troubleshoot them. Moving on, you'll get practical recipes on integrating DevOps with Azure Functions, and providing continuous deployment with Visual Studio Team Services. The book also provides hands-on steps and tutorials based on real-world serverless use cases to guide you through configuring and setting up your serverless environments with ease. Finally, you'll see how to manage Azure Functions, providing enterprise-level security and compliance to
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Microsoft
Published 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
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