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Data Management

Data Management comprises all the disciplines related to managing data as a valuable resource. Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise.
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By: Oracle Hardware     Published Date: Apr 29, 2016
When meeting the needs of a growing infrastructure, do you build or buy? This video illustrates how using the Oracle Database Appliance, which contains the server, software, networking and storage, is easy to deploy and maintain compared to a traditional build scenario, while also being an affordable high availability database solution.
Tags : data management, business practices, databade management, data appliance
     Oracle Hardware
By: Pentaho     Published Date: Apr 28, 2016
Today, the need for self-service data discovery is making data governance a charged topic. As business-driven data discovery emerges as a fundamental need, the ability to ensure that data and analytics are trustworthy and protected becomes both more difficult and more imperative. This research explains how to manage the barriers and risks of self-service and enable agile data discovery across the organization by extending existing data governance framework concepts to the data-driven and discovery-oriented business. You’ll learn: - The implications of the "freedom vs. control" paradox - How to design for iterative, "frictionless" discovery - Critical checkpoints in data discovery process where governance should be in place
Tags : pentaho, governed data, data and analytics, governance framework, freedom vs control
     Pentaho
By: Pentaho     Published Date: Apr 28, 2016
As data warehouses (DWs) and requirements for them continue to evolve, having a strategy to catch up and continuously modernize DWs is vital. DWs continue to be relevant, since as they support operationalized analytics, and enable business value from machine data and other new forms of big data. This TDWI Best Practices report covers how to modernize a DW environment, to keep it competitive and aligned with business goals, in the new age of big data analytics. This report covers: • The many options – both old and new – for modernizing a data warehouse • New technologies, products, and practices to real-world use cases • How to extend the lifespan, range of uses, and value of existing data warehouses
Tags : pentaho, data warehouse, modernization, big data, bug data analytics
     Pentaho
By: Pentaho     Published Date: Apr 28, 2016
Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.
Tags : pentaho, best practices, hadoop, next generation analytics, platforms
     Pentaho
By: Rsam     Published Date: Apr 28, 2016
The University of Rochester Medical Center (URMC) is of the nation’s top academic medical centers. Their InfoSec team wanted to implement a program that could withstand constant shifts in regulatory requirements while protecting the sanctity of patient health information. Learn why the selected Rsam and the results of their successful implementation.
Tags : rsam, university of rochester, security incident response, successful implementation, data management
     Rsam
By: Rsam     Published Date: Apr 28, 2016
Healthcare enterprises are under more scrutiny than ever to demonstrate compliance. With more than 5,000 suppliers, this FORTUNE 50 company needed to automate and streamline their vendor risk management program. Learn why they selected Rsam and the results of their successful implementation.
Tags : rsam, fortune 500, vendor risk management, healthcare enterprise, compliance
     Rsam
By: Pluralsight     Published Date: Apr 27, 2016
The rise of the web drove the need for applications in the browser. JSON is natively supported and easy to understand, with facile methods to learn our technical details. JSON sums new web technologies with client side practices to achieve an interactive web application.
Tags : network management, best practices, network optimization, network applications, application management
     Pluralsight
By: IBM     Published Date: Apr 22, 2016
The upside of disruption: Reinventing business processes, organizations and industries in the wake of the digital revolution
Tags : ibm, ibm big data and analytics, ibm big data, trusted data, big data
     IBM
By: IBM     Published Date: Apr 22, 2016
This white paper explains the value of putting data and insight to work to accelerate an organization’s journey to becoming a Cognitive Business, by enhancing their investments in data and analytics and realizing new opportunities from cognitive systems that understand, reason and learn.
Tags : ibm, ibm analytics, cognitive business, watson, think data
     IBM
By: IBM     Published Date: Apr 22, 2016
Developing a data integration and lifecycle management strategy for a hybrid environment This e-book focuses on building and executing a data integration and lifecycle management strategy.
Tags : ibm, think data, integration, lifecycle strategy, ibm analytics
     IBM
By: Mimecast     Published Date: Apr 20, 2016
Mimecast conducted a whaling attack survey with 500 organizations around the globe and the results were alarming.
Tags : mimecast, data breach, personalized emails, network defenses, cyber threats
     Mimecast
By: IBM     Published Date: Apr 19, 2016
This white paper describes how IBM’s Pure Data System for Analytics delivers speed and simplicity to help organizations become more responsive and agile in today’s increasingly mobile and data-driven market.
Tags : ibm, ibm pure data system, big data, data analytics, analytics architecture
     IBM
By: IBM     Published Date: Apr 19, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
Tags : ibm, ibm pure data system, big data, data analytics, analytics architecture
     IBM
By: IBM     Published Date: Apr 19, 2016
The use of analytics will define the successful midmarket business of the next decade, just as it will define the successful larger organization in this information age. The past decade has seen rapid change in the business climates with an explosion of global competition and economic uncertainty. Despite this, many midmarket companies have thrived by using their size and agility as a competitive advantage. Certainly they have fewer resources than large corporations who are able to invest large sums in IT. However, small yachts can turn and adjust their course much quicker than large cruise ships. The same came be said for midmarket companies. The most successful organizations are ones that can react the quickest to changes in the market place. Midmarket companies can take advantage of their smaller size by being more agile and quicker to change, or even reinvent themselves, to respond to the market.
Tags : ibm, ibm pure data system, big data, data analytics, analytics architecture
     IBM
By: IBM     Published Date: Apr 18, 2016
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business. Combining the power of IBM® InfoSphere® Master Data Management (MDM) with the IBM big data portfolio creates a valuable connection: big data technology can supply insights to MDM, and MDM can supply master data definitions to big data.
Tags : ibm, mdm, big data, ibm infosphere, data management
     IBM
By: IBM     Published Date: Apr 18, 2016
"Five high-value uses for big data: IBM has conducted surveys, studied analysts’ findings, talked with more than 300 customers and prospects and implemented hundreds of big data solutions. As a result, it has identified five high-value use cases that enable organizations to gain new value from big data."
Tags : ibm, mdm, big data, trusted data, data solutions
     IBM
By: IBM     Published Date: Apr 18, 2016
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
Tags : ibm, mdm, big data, data management, data matching
     IBM
By: IBM     Published Date: Apr 18, 2016
Today data volumes are exploding in every facet of our lives. Business leaders are eager to harness the power of big data but before setting out into the big data world it is important to understand that as opportunities increase ensuring that source information is trustworthy and protected becomes exponentially more difficult. This paper provides a detailed review of the best practices clients should consider before embarking on their big data integration projects.
Tags : ibm, big data, trusted data, data management, data solutions
     IBM
By: IBM     Published Date: Apr 18, 2016
"Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need."
Tags : ibm, big data, ibm infosphere, ibm biginsights, ibm bigintegrate
     IBM
By: IBM     Published Date: Apr 18, 2016
By using InfoSphere Information Server “flexible integration” capabilities, the information that drives business and strategic initiatives—from big data and point-of-impact analytics to master data management and data warehousing—is trusted, consistent and governed in real time.
Tags : ibm, big data, ibm infosphere, information empowerment, data integration
     IBM
By: IBM     Published Date: Apr 18, 2016
IBM commissioned Forrester Consulting to conduct a Total Economic Impact (TEI) study and examine the potential return on investment (ROI) enterprises may realize by leveraging IBM InfoSphere Information Integration and Governance (IIG) solutions.
Tags : ibm, total economic impact, tei study, roi, return on investment
     IBM
By: IBM     Published Date: Apr 18, 2016
While the term 'big data' has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades. IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.
Tags : ibm, ibm infosphere, big data, data optim, data management
     IBM
By: IBM     Published Date: Apr 18, 2016
This e-book describes how a data refinery can make trusted data available quickly and easily to people and systems across your organization. It includes simple steps you can take to start exploring - and implementing - this strategy for handling the challenges of hybrid data environments.
Tags : ibm, trusted data, data optim, big data, hybrid data environments
     IBM
By: F5 Networks Inc     Published Date: Apr 15, 2016
As enterprises evolve to the 3rd Platform of IT, they will reap many benefits and face many challenges. Meeting the rapid pace of business and taking control of the customer experience must be balanced with keeping assets secure as the enterprise perimeter expands or dissolves altogether.
Tags : application, transformation, cloud, enterprise, mobile
     F5 Networks Inc
By: RolePoint     Published Date: Apr 12, 2016
Over the last three years, social networks have experienced exponential growth. Employee networks have grown accordingly, offering access to structured career data through sites like LinkedIn in particular, and unstructured data through networks like Facebook. Employees are continually adding new contacts and growing personal networks. Job posting tools that share jobs into social networks are often described as social referral tools, though this is an inaccurate and misleading description. The more sophisticated of these tools create unique links for sharing that enable employers to identify which of their employees originated the share. This is useful for recognition and reward, whilst the practice of sharing jobs in the wider network is to be encouraged in order to reach job seekers who are browsing or using search engines to identify opportunities. Job seekers are increasingly connecting with their peers in organizations they want to work for. Encouraging employees to share jobs in
Tags : rolepoint, social referral, facebook, linkedin, career data
     RolePoint
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