data management

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Published By: Hewlett Packard Enterprise     Published Date: Oct 24, 2017
Big Data is not just a big buzzword. Government agencies have been collecting large amounts of data for some time and analyzing the data collected to one degree or another. Big data is a term that describes high volume, variety and velocity of information that inundates an organization on a regular basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and better services.
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cloud optimization, cloud efficiency, cloud management, cloud assurance, cloud visibility, enterprise management, data management
    
Hewlett Packard Enterprise
Published By: IBM     Published Date: Apr 01, 2016
Read the eBook to: 1) Expand what you know about Big Data; 2) Learn about the Big Data Zones Model that brings a new approach to managing data, faster to deploy, faster to insights and with less risk; 3) Gain confidence in your Big Data projects and learn about the importance of governance in a Big Data world
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ibm, ibm connect, big data, big data zones model, data management
    
IBM
Published By: Teradata     Published Date: Feb 26, 2013
This survey and research report discusses shifts in the data management landscape and the movement to align data with operational and analytical workloads creating the best possible unified data architecture platform. Read on to learn more.
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big data, survey report, data management, landscape, movement, align data, operational and analytics workloads, business intelligence, terdata
    
Teradata
Published By: SAP     Published Date: May 18, 2014
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
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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: IBM     Published Date: Jan 14, 2015
Big data has been big news in recent years. Organizations recognize that they must now begin to focus on using big data technologies to solve business problems. The pressure is on for organizations to move past the discussion phase toward well-planned projects.
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big data, data management, data exploration, gain visibility, security extension, business intelligence, explore data, data analytics
    
IBM
Published By: SAP     Published Date: May 18, 2014
Big data and personal data are converging to shape the internet’s most surprising consumer products. they’ll predict your needs and store your memories—if you let them. Download this report to learn more.
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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: CEB     Published Date: Nov 21, 2013
How do you know if your organization has the talent it needs to execute on its strategy? Is your organization’s talent ready to perform in the new work environment? Are your talent development programs focused on the right people?
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ceb, big data, big data intent, global workforce, organisational talent, business objectives, productivity, innovation, talent management, workforce skills, data-based analysis, future leaders, organisational risk, global skills, landscape of diversity, global availability
    
CEB
Published By: TIBCO     Published Date: Apr 08, 2013
As the volume of available data increases, and we have new ways of extracting insights from data, it is valuable to take a step back and examine the impact of these insights on integration and company actions. Join us for this webinar and learn how you can use big data in your organization.
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big data, integration, architecture, database, data warehousing, operations management
    
TIBCO
Published By: TIBCO     Published Date: May 15, 2013
According to Forrester, most organizations today are only using 12% of their available data and only 37% of organizations are planning some type of big data technology project. At a time when companies are seeing volume of information increase quickly, it’s time to take a step back and look at the impact of big data. Join Mike Gualtieri, Principal Analyst at Forrester, for this webcast exploring the importance of integration in your big data initiatives. Discover how your ability to operate, make decisions, reduce risks and serve customers is inextricably linked to how well you’re able to handle your big data. Continue on to gain insight into: •3 key big data management activities you need to consider •Technologies you need to create for your big data ecosystem •A multi-dimensional view of the customer is the holy grail of individualization •Overcoming key integration challenges And more!
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big data, integration, architecture, database, data warehousing, operations management
    
TIBCO
Published By: IBM     Published Date: Aug 20, 2015
Understand the traits of successful performers and potential top talent. Using big data to uncover those traits reveals something surprising.
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big data, talent management, ibm recruitment, behavioral insights, potential top talent, impactful management, unique individual characteristics, human resources
    
IBM
Published By: IBM     Published Date: Jul 08, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, idc, big data, data, analytics, information governance
    
IBM
Published By: IBM     Published Date: Oct 18, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, idc, big data, data, analytics, information governance
    
IBM
Published By: IBM     Published Date: Jul 14, 2015
This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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big data, data warehouse, data center, information governance, analytics, big data analytics, business management
    
IBM
Published By: IBM     Published Date: Apr 06, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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big data, analytics, unstructured content, enterprise information, ibm
    
IBM
Published By: IBM     Published Date: Feb 24, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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big data, ibm, big data outcomes, information governance, big data analytics
    
IBM
Published By: LogLogic     Published Date: Mar 15, 2012
"Big Data" is the latest buzzword, yet over 70% of companies don't know what Big Data means and how to solve the data management challenges, finds LogLogic survey.
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log management, siem, big data, storage, sem, pci compliance, it operations, data storage, data forensics, security intelligence, splunk, rsa envision, logrhythm, arcsight, compliance, hipaa, nitro security, q1 labs, security event management, syslog
    
LogLogic
Published By: SAS     Published Date: Mar 01, 2012
This paper shows the results of the survey, as well as trends and expert opinions focusing on why some top organizations are able to successfully extract insight from "big data."
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics, it management, ondemand solutions, performance management, risk management, sas® 9.3, supply chain intelligence, sustainability management
    
SAS
Published By: Adaptive Computing     Published Date: Feb 06, 2014
A new approach, known as “Big Workflow,” is being created by Adaptive Computing to address the needs of these applications. It is designed to unify public clouds, private clouds, Map Reduce-type clusters, and technical computing clusters. Download now to learn more.
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adaptive, ada[tive computing, big data, data center, workload management, servers, cloud, cloud computing, storage, data storage
    
Adaptive Computing
Published By: Dell EMC     Published Date: Aug 15, 2017
The all-flash, hybrid & archive storage systems allow customers to take on new, demanding unstructured data apps to achieve faster business outcomes.
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nas storage, storage platform, storage system, data storage, data management
    
Dell EMC
Published 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.
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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: HP Data Center     Published Date: Apr 08, 2009
Unified Communications (UC) aims to unite securely and seamlessly all the different business communications channels that exist in a company. That includes voice, video, data, IM, mobility and the Web etc. This report examines in detail the key industry drivers and benefits that are inspiring large scale enterprises to adopt a Unified Communications strategy.
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business communications, voice, video, data, mobility, industry drivers, unified communications strategy, just in time, jit, cross-functional, hp data center, cisco, crm, workflow, workforce management, total cost of ownership, tco, voice response (ivr), automatic call distributor (acd), disaster recovery
    
HP Data Center
Published By: IBM     Published Date: Jan 14, 2015
Bloor Research investigated several key critical success factors for big data analytics. Their findings show that governance, data cleansing, and privacy and security have never been more important. Read this paper to see their conclusions.
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big data, data management, data exploration, gain visibility, security extension, business intelligence, explore data, data analytics
    
IBM
Published By: CA Technologies EMEA     Published Date: Sep 07, 2018
There are five ways to provision test data. You can copy or take a snapshot of your production database or databases. You can provision data manually or via a spreadsheet. You can derive virtual copies of your production database(s). You can generate subsets of your production database(s). And you can generate synthetic data that is representative of your production data but is not actually real. Of course, the first four examples assume that the data you need for testing purposes is available to you from your production databases. If this is not the case, then only manual or synthetic data provision is a viable option. Download this whitepaper to find out more about how CA Technologies can help your business and its Test Data problems.
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CA Technologies EMEA
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