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Published By: Delphix     Published Date: May 28, 2015
In a world of privacy regulation, intellectual property theft, and cybercrime, only a masking solution can secure vital data and enable outsourcing, third party analysis, and cloud deployments. Delphix delivers rapid deployment of masked data in minutes, service-based masking of production systems, and the ability to ship masked data across sites, to third parties, and into the cloud, with minimal network footprint.
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Delphix
Published By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Business users want the power of analytics—but analytics can only be as good as the data. The biggest challenge nontechnical users are encountering is the same one that has been a steep challenge for data scientists: slow, difficult, and tedious data preparation. The increasing volume, variety, and velocity of data is putting pressure on organizations to rethink traditional methods of preparing data for reporting, analysis, and sharing. Download this white paper to find out how you can improve your data preparation for business analytics.
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Waterline Data & Research Partners
Published By: Datawatch     Published Date: Dec 16, 2015
In this paper, the Top 10 Ways to Supercharge Analyst Productivity with Data Preparation, learn how a self-service data preparation solution saves analysts’ time by allowing them to manipulate, filter, enrich, blend and combine disparate data sets in a matter of minutes.
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data preparation, data wrangling, analyst productivity, data analysis, cleaning data, data blending
    
Datawatch
Published By: Datawatch     Published Date: Feb 03, 2016
Some companies estimate that up to 80 percent of their analysts’ time is spent on data preparation. Thorough, automated data preparation, however, can quickly transform raw information into reliable, consistent data sets ready for analysis. This report from Gartner details why information management and business analytics leaders must introduce data preparation into their big data initiatives in order to improve both the understanding of the data, and the productivity of analysts. Read the report now to learn more.
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datawatch, data preparation, data analytics, data analysis, analyst productivity, information management, business analytics, big data
    
Datawatch
Published By: IBM     Published Date: Jul 27, 2016
IBM i2 Enterprise Insight Analysis helps analysts and investigators turn large data sets into comprehensive intelligence, in near real-time. With the help of advanced analytics and visual analysis capabilities, analysts can uncover hidden connections, patterns and trends buried in disparate data. Equip analysts and those on the front line with the tools they need to generate actionable intelligence, with mission critical speed.
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ibm, cyber threat analysis, ibm i2 enterprise insight analysis, cyber security, business intelligence
    
IBM
Published By: IBM     Published Date: Oct 27, 2016
IBM Analytics for Apache Spark for Bluemix is an open-source cluster computing framework with in-memory processing to speed analytic applications up to 100 times faster compared to other technologies on the market today. Optimized for extremely fast and large scale data processing-you can easily perform big data analysis from one application.
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ibm, apache spark, bluemix, analytics
    
IBM
Published By: Veritas     Published Date: May 12, 2016
The Data Genomics Index is a first-of-its-kind benchmark analysis of data stored within a typical enterprise environment. This report reveals insights into data growth, data age, and data type thereby providing organizations with the comparison standard for beginning to take action on their data. In addition to the Index, Veritas has founded the Data Genomics Project. This community of likeminded data scientists, industry experts and thought leaders will come together to surface the true nature of enterprise environments, build the data-genome that matters for information management, and share the discussion with a world struggling to solve tremendous data growth challenges.
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Veritas
Published By: IBM     Published Date: Jan 18, 2017
In the domain of data science, solving problems and answering questions through data analysis is standard practice. Data scientists experiment continuously by constructing models to predict outcomes or discover underlying patterns, with the goal of gaining new insights. But data scientists can only go so far without support.
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ibm, analytics, aps data, open data science, data science, data engineers
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
Analytics relies on BI, Big Data, and data discovery to provide reporting, trend what-if analysis. Analytics is transforming data into insight.
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ibm, analytics, business intelligence, data
    
IBM
Published By: IBM     Published Date: Nov 03, 2017
Ironically, the most important business decisions are too often based not on the best available data and analysis, but on the judgment calls of HIPPOs — the highest-paid people in the organization. In large part, these individuals became HIPPOs in the first place because, over the course of their professional careers, their intuition and gut feel has tended to be more right than wrong. This approach may have sufficed in simpler, slower-moving times. But modern enterprises are too connected and too fast-paced for important business decisions to be made strictly on individual intuition and gut feel. For better-informed decision-making, your organization’s decision-makers need timely access to information they can rely on.
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hippo, ibm, decision-makers, modern enterprise
    
IBM
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
Analysts struggle to incorporate new sources of data into their analysis because they rely on Microsoft Excel or other tools that were not designed for data blending. Deleting columns, parsing data, and writing complicated formulas to clean and combine data every time it changes is not an efficient way for today’s analysts to spend their time. Download The Definitive Guide to Data Blending and: Understand how analysts are empowered through data blending Learn how to automate time-consuming, manual data preparation tasks Gain deeper business insights in hours, not the weeks typical of traditional approaches
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Alteryx, Inc.
Published By: Reputation.com     Published Date: Oct 02, 2017
1.Meet the new consumer The migration to mobile and social media will challenge — and change — everything we know about consumer marketing. 2. Who owns your brand? Brand equity can no longer be bought. Online reviews now generate total market transparency for location-based businesses. Reviews tilt the balance of branding power away from companies and into the hands of customers. 3. The battle for brick-and-mortar customers is won or lost on the social web. To win, marketers must actively enlist customers as online advocates. Those who scale online review volume and quality will be rewarded with higher search visibility and more business at street level. 4. “Dark data” provides priceless operational insights Vast amounts of unstructured, unmined sentiment data on social media provides feedback about the customer experience that you can filter using thematic analysis and use to improve operations at the national or location level. 5. Business implications Online reputation stands betwee
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Reputation.com
Published By: IBM     Published Date: Jun 04, 2018
"The appearance of your reports and dashboards – the actual visual appearance of your data analysis -- is important. An ugly or confusing report may be dismissed, even though it contains valuable insights about your data. Cognos Analytics has a long track record of high quality analytic insight, and now, we added a lot of new capabilities designed to help even novice users quickly and easily produce great-looking and consumable reports you can trust. Watch this webinar to learn: • How you can more effectively communicate with data. • What constitutes an intuitive and highly navigable report • How take advantage of some of the new capabilities in Cognos Analytics to create reports that are more compelling and understandable in less time. • Some of the new and exciting capabilities coming to Cognos Analytics in 2018 (hint: more intelligent capabilities with enhancements to Natural Language Processing, data discovery and Machine Learning)."
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data analysis, data analytics, dashboards
    
IBM
Published By: IBM     Published Date: Jun 04, 2018
"What would you do if you didn’t have to rely on disparate analytics solutions to meet the needs of business users while following the rules of IT? View this 'Charting Your Analytical Future' webinar to learn about a world of innovation and independence for users that does not limit the confidence and controls of IT. With the cognitive-guided self-service features available in IBM business analytics solutions, more users than ever before can get the answers they need. Next-generation business analytics capabilities make it possible to access relevant data, prepare it for analysis and understand performance. But it doesn’t stop there. Users can package the results in a visually-appealing format and share them throughout the organization. Don’t miss this opportunity to hear how you can: * Benefit from advanced analytics without the complexity * Operationalize insights and dashboards from a collection of trusted data sources * Tell your story with rich visualizations and geospati
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business analytics, analytics solutions
    
IBM
Published By: IBM     Published Date: Jul 02, 2018
Cloud has evolved from a technological innovation to an integral part of business. Companies in every industry are investing in Digital Transformation initiatives to evolve and grow; often, cloudbased platforms are foundational elements of these transformations, as businesses increasingly seek the flexibility and agility to roll out new software services in days or weeks, versus months or years. As Digital Transformation initiatives unfold, one key challenge is to modernize the data center to facilitate rapid delivery of new applications and services—while still ensuring that existing missioncritical applications remain high performing, available, and secure. Another challenge relates to new requirements for accelerating the analysis of organizational data to near real time, much faster than previously possible with earlier incarnations of Business Intelligence (BI). Agile businesses are demanding faster access to the information contained within operational and business data stores to
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IBM
Published By: IBM     Published Date: Jul 09, 2018
As the information age matures, data has become the most powerful resource enterprises have at their disposal. Businesses have embraced digital transformation, often staking their reputations on insights extracted from collected data. While decision-makers hone in on hot topics like AI and the potential of data to drive businesses into the future, many underestimate the pitfalls of poor data governance. If business decision-makers can’t trust the data within their organization, how can stakeholders and customers know they are in good hands? Information that is not correctly distributed, or abandoned within an IT silo, can prove harmful to the integrity of business decisions. In search of instant analytical insights, businesses often prioritize data access and analysis over governance and quality. However, without ensuring the data is trustworthy, complete and consistent, leaders cannot be confident their decisions are rooted in facts and reality
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IBM
Published By: OracleSMB     Published Date: Jan 04, 2018
Finance has grown beyond recording and reporting. Leaders in fast-growing companies need not only the raw financial data, but the sophisticated analysis to make sense of it all. In today’s digital world, Finance must move out of the back-office and help drive the direction of the business, as well as improve the bottom line through more efficient processes and increased responsiveness. With the right tools, your finance team can simplify processes and fulfill its goal of adding value.
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OracleSMB
Published By: LogMeIn     Published Date: Feb 27, 2018
Most customer engagement solutions on the market require complex data analysis and months of implementation before you start seeing results. But Bold360 ai uses Natural Language Understanding to start learning your customers’ needs from the very first interaction. Its smart routing capability directs customers to the best resource available, and captures data in an intuitive dashboard. Start seeing results now with Bold360 ai.
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bold360, engagement, customer, market, data, analysis
    
LogMeIn
Published By: Amazon Web Services EMEA     Published Date: Sep 09, 2019
Local and regional governments around the world are using the cloud to transform services, improve their operations, and reach new horizons for citizen services. The Amazon Web Services (AWS) cloud enables data collection, analysis, and decision making for smarter cities. This whitepaper provides strategic considerations for local and regional governments to consider as they identify which IT systems and applications to move to the cloud. Real examples that show how cities can stop wasting money, move faster, and innovate.
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Amazon Web Services EMEA
Published By: Group M_IBM Q119     Published Date: Dec 20, 2018
The security information and event management (SIEM) market is defined by the customer's need to analyze event data in real time for the early detection of targeted attacks and data breaches, and to collect, store, analyze, investigate and report on event data for incident response, forensics and regulatory compliance. The vendors included in our Magic Quadrant analysis have products designed for this purpose, and they actively market and sell these technologies to the security buying center.
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Group M_IBM Q119
Published By: Group M_IBM Q2'19     Published Date: Apr 03, 2019
The growing need for data governance, risk and compliance, data analysis and data value still drives strategic requirements in metadata management and the growth of its solutions. Data and analytics leaders can use this vendor evaluation to find the most appropriate solution for their organization.
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Group M_IBM Q2'19
Published By: Group M_IBM Q3'19     Published Date: Jul 01, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q3'19
Published By: Group M_IBM Q3'19     Published Date: Sep 04, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q3'19
Published By: Acoustic     Published Date: Aug 22, 2019
Companies that can harness the power of data are tomorrow’s winners. At Acoustic, we believe deeply in the importance of putting data into context to help companies quickly determine which marketing messages are resonating and which strategies are outpacing the market. The 2019 Marketing Benchmark Report examines email and mobile marketing messages sent by thousands of brands in 2018 to establish industry standards on customer engagement, delivery and subscriber churn. Our analysis uncovers trends and benchmarks than can help you optimize your audience outreach. Use this valuable information to compare how your campaigns are performing, see where to focus your efforts and build your case for more investment.
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Acoustic
Published By: VMware Dell     Published Date: Jul 02, 2008
In this case study, you'll discover the tangible benefits to IRMC when they used VMware Virtual Desktop Infrastructure to virtualize their call center operations and support multiple call centers from a central data center. Their IT staff achieved increased flexibility, faster provisioning, redeployed IT staff, reduced IT costs, and improved competitiveness. Finally, review a detailed financial analysis to back up IRMC's 73% annual ROI, and see how they saved.
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call center, vmware, virtual, virtualization, virtual machine, callcenter, it savings, cost savings
    
VMware Dell
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