data analyst

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Published By: ETQ     Published Date: Jul 10, 2019
According to Gartner, "supply chain leaders responsible for quality management are shifting to software solutions that standardize processes, optimize data and ensure compliance. This research provides guidance for structuring a process for QMS software selection." Download this Gartner Analyst Guide to learn: Key challenges in the QMS software selection processes What to expect from different QMS solutions across the market Analysis of the current state of quality management to help define software requirements Self assessment questions and commonly sought QMS system functionalities to use in your decision making process
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ETQ
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: Flexential     Published Date: Jul 17, 2019
By 2020, there will be 50 billion devices producing 600Zb of data, driving enterprises to assess their IT infrastructures to keep pace with unprecedented data processing demands. Is your business ready to handle this data explosion? In this on-demand webinar, you’ll hear Tim Parker, Vice President of Network Services at Flexential, and Craig Matsumoto, Senior Analyst of Data Center Services at 451 Research, discuss the evolution of data – and how enterprises are processing and creating it. Download now to hear Parker and Matsumoto examine how edge computing solutions are meeting the latency demands of an increasingly digitized world.
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Flexential
Published By: Dell EMC     Published Date: Aug 01, 2019
Software might run the world, but software still runs on hardware. It’s a misperception that hardware has little value anymore. Every application, every workload, every data set runs on physical servers. Read “Hardware Does Matter: Global Server Brands are Perceived as Superior for Driving Digital Business,” a Frost & Sullivan report of 500 IT decision makers, on the value of global server brands vs. commodity servers. Look beyond commodity status to discover: • Key server purchase criteria • How top brands directly compare • How to choose based on workload Server brands very significantly, and a commodity brand may not provide the outcomes you need, especially for new and next-generation applications. Download this analyst report from Dell EMC and Intel® to learn more.
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Dell EMC
Published By: SAS     Published Date: Sep 05, 2019
Envision this situation at a growing bank. Its competitive landscape demands an agile response to evolving customer needs. Fortunately, analytically minded professionals in different divisions are seeing results that positively affect the bottom line. • A data scientist in the business development team analyzes data to create customized • experiences for premium customers. • A digital marketer tracks and influences the customer journey for prospective • mortgage customers. • A risk analyst builds risk models for the bank’s loan portfolios. • A data analyst examines data about local customers. • A technical architect defines a new system to protect bank data from internal and • external cyberthreats. • An application developer builds a new mobile app for online customer portfolio • management. Between them, these employees might be using more than a dozen packages for analytics and data management.
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SAS
Published By: MicroStrategy     Published Date: Aug 28, 2019
Why HyperIntelligence? Today, despite massive investments in data, IT infrastructure, and analytics software, the adoption of analytics continues to lag behind. In fact, according to Gartner, most organizations fail to hit the 30% mark. That means that more than 70% of people at most organizations are going without access to the critical information they need to perform to the best of their abilities. What’s stopping organizations from breaking through the 30% barrier and driving the pervasive adoption of intelligence? Simple. The majority of existing tools only cater to users who are naturally analytically inclined—the analysts, data scientists, and architects of the world. The other 70%—the people making the operational decisions daily within a business—simply lack the time, skill, or desire to seek out data and intelligence on their own. HyperIntelligence helps organizations operationalize their existing investments and arm everyone across the organization with intelligence. Whether
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MicroStrategy
Published By: Iovation     Published Date: Aug 02, 2019
Account takeover. Synthetic identities. The security risks that financial services and online merchants face are endless, and the fraud landscape is changing dramatically. You not only need to be aware of how it’s evolving, but how to address these threats, protect your customers and your brand. iovation has analyzed data from our consortium made up of six billion devices seen, 55 million fraud reports, and thousands of fraud analysts to determine the most significant fraud trends and what you can do to combat them.
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Iovation
Published By: Simba by Magnitude     Published Date: Jul 12, 2019
Today’s C-level executives expect data and analytics to provide them with speed and agility to deliver competitive advantage and to disrupt new markets. But, in today’s complex data environment exists a near paradox between these expectations, that companies will be able to rapidly deliver value using data and analytics--and the complexities of the data landscape, making it more difficult to find, govern, connect to and access the data needed to deliver that value. Once thing is clear: if management expectation is to be met, simplifying connectivity is a must.In this white paper, veteran analyst Mike Ferguson, Managing Director of Intelligent Business Strategies explores how simplifying data access –connectivity –aligns expectations with data realities thus decreasing time to value.
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Simba by Magnitude
Published By: SAP     Published Date: May 18, 2014
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: SAP     Published Date: May 18, 2014
The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: Hewlett Packard Enterprise     Published Date: Feb 08, 2017
Explore four ways you can empower your data to help you meet your business goals in this analyst white paper from ESG. Download now.
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Hewlett Packard Enterprise
Published By: Carbonite     Published Date: Jul 18, 2018
© 2018 Carbonite, Inc. All rights reserved. Case study Diamond Foods’ Diamond of California® nuts are household staples for shoppers across the U.S. But constantly filling grocery store shelves with snacks requires intricate supply chain management that relies on critical business data, including complex spreadsheets and enterprise resource planning files, to keep production and deliveries on schedule. “If our critical servers go down or we lose important data on employee laptops, it has a direct impact on our bottom line,” says Kentrell Davis, Senior Client Support Services Analyst at Diamond Foods.
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Carbonite
Published By: Adobe     Published Date: Sep 12, 2017
"Read the guide to learn five ways to overcome challenges to programmatic ads, including how to: · Bring marketers, creatives, IT, and data analysts together to ensure success · Save money and time while improving engagement and conversion · Customize multiple versions of one campaign and serve ads with strong creative in real time"
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Adobe
Published By: Gigamon     Published Date: Oct 25, 2017
Read the Joint Solution Brief Accelerate Threat Detection and Response to learn how Gigamon helps Splunk Enterprise users effectively analyze and remediate network security threats. Benefits include enhanced visibility and deeper, faster security analytics from precise, targeted network metadata generated from the traffic flowing in your network. Also learn how automation of common security tasks, across the Gigamon platform and third-party security tools, from within the Splunk platform helps increase analyst efficiency and reduce errors.
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Gigamon
Published By: SAS     Published Date: Nov 04, 2015
If you are working with massive amounts of data, one challenge is how to display results of data exploration and analysis in a way that is not overwhelming. You may need a new way to look at the data – one that collapses and condenses the results in an intuitive fashion but still displays graphs and charts that decision makers are accustomed to seeing. And, in today’s on-the-go society, you may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time. SAS® Visual Analytics is a data visualization and business intelligence solution that uses intelligent autocharting to help business analysts and nontechnical users visualize data. It creates the best possible visual based on the data that is selected. The visualizations make it easy to see patterns and trends and identify opportunities for further analysis.
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data visualization, sas, big data, visual analytics, data exploration, analysis, networking, knowledge management
    
SAS
Published By: Dun & Bradstreet     Published Date: Mar 03, 2017
Creating predictive analytics from alternative data has become the current focus of the biggest quant trading firms in the industry The democratization of financial services data and technology, together with more intense competition, makes the needs of today’s market participants vastly different from those of previous generations. Firms must locate untapped sources of data for both public and non-public companies. This alternative data, such as payment data and other non-public information, from sources beyond the common channels, can be a predictive indicator of market performance; a difference maker in assisting firms as they develop models to evaluate their investments. By combining our unique data sets with advanced analytics, traders, analysts and managers can seek predictive signals and actionable information utilizing their own models. View our research report to learn how alternative data, our 'Information Alpha,' can help you earn differentiated investment returns.
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Dun & Bradstreet
Published By: Sage EMEA     Published Date: Jan 29, 2019
Transform your finance operations into a strategic, data-driven engine Data inundation and information overload have burdened practically every largescale enterprise today, providing great amounts of detail but often very little context on which executives can act. According to the Harvard Business Review,1 less than half of an organisation’s structured data is actively used in making decisions. The burden is felt profoundly among finance executives, who increasingly require fast and easy access to real-time data in order to make smart, timely, strategic decisions. In fact, 80% of analysts’ time is spent simply discovering and preparing data, and the average CFO receives information too late to make decisions 24% of the time.2
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Sage EMEA
Published By: MarkLogic     Published Date: Jun 09, 2017
Your high-stakes data projects don’t have to end – as analysts predict – in failure. Don’t just rely on legacy technology and outdated thinking - the key is to start your next data project armed with the right technology and mindset to succeed. This paper will give you insights and guidelines to help you learn how to leverage all of your data to reach your data integration objectives with less time and expense than you might imagine. Change is good, and in this paper we’ll give you real-world examples of organizations that embraced change and found success.
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MarkLogic
Published By: IBM APAC     Published Date: Aug 22, 2017
For any sized organization, securing data and networks today is a daunting task. New vulnerabilities are discovered almost daily; new malware strains are developed as soon as a detection script is written for the old ones; and cybercriminals can buy prepackaged exploit kits on the Darknet backed by professional support teams. As a security analyst, you need more than a few point solutions designed to defend the network’s edge. You need visibility, perspective and an innate sense of when things just don’t seem right.
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ibm, qradar, cloud, analytics, flexibility, scalability, organization
    
IBM APAC
Published By: Cognizant     Published Date: Oct 23, 2018
The implications of AI’s unique approach are profound: AI can learn by example rather than through brute-force programming; can understand human intention and emotions and act accordingly; and can handle extraordinarily complex relationships of data that are beyond the capability of human analysts working alone. AI can multiply what we currently do and take us to experiences we’ve never had before, at a speed and scale that will change entire industries. In these case studies, we’re pleased to present a range of real-world examples to guide your imagination. Here, you’ll find situations where companies like yours found AI to be part of the solution. These examples show how AI can enhance an existing application, workflow or process and reduce friction. This e-book presents how 10 organizations are using artificial intelligence to accelerate decision making, improve business processes, enhance user engagement, reduce costs and drive remarkable growth and profitability.
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cognizant, artificial intelligence
    
Cognizant
Published By: Oracle Analytics     Published Date: Oct 10, 2017
How are organizations balancing self-service analytics and data governance today? What are the trends for tomorrow? Many organizations are on their way to achieving self-service analytics maturity through the use of intuitive data visualization technologies aimed at non-technical users; as well as various tactics that reduce reliance on IT. But handing the analytics reins entirely to business users can make governance nearly impossible. As a result, organizations are increasing investments in modern analytics platforms that enable a balance between IT governing and curating data, empowering business users to derive insights from data mostly on their own and without delay. Join guest speaker, Forrester Research VP and Principal Analyst, Boris Evelson and Oracle Analytics Senior Group Director, Jose Villacis as they discuss insights from an Oracle-commissioned study of North American enterprise analytics leaders.
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Oracle Analytics
Published By: IBM     Published Date: Oct 14, 2016
This ebook presents six reasons why you should consider a database change, including opinions from industry analysts and real-world customer experiences. Read on to learn more.
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ibm, database, database change, analytics, networking, knowledge management, business technology, data center
    
IBM
Published By: Akamai Technologies     Published Date: Oct 02, 2018
The Summer 2018 security report is about change: what’s new and unusual in DDoS attacks, where are the surprising data patterns, and how should enterprises and security professionals prepare for the unexpected. Looking back at November 2017 to April 2018, as well as year-over-year changes, Akamai analysts identified data trends that spotlight the new and unfamiliar. The Summer 2018 State of the Internet / Security: Web Attacks report covers atypical attack methods, credential abuse attacks and law enforcement prosecution of DDoS-for-hire platforms. Guest writer Rik Ferguson also explores future threat scenarios. Finally, the Integrate SID for your records (and in case you need it) for this program is: 0E9175. Anything else you need to hit the ground running with this program?
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internet, web, attacks, technology, ddos
    
Akamai Technologies
Published By: Liaison Technologies     Published Date: Nov 21, 2011
In this whitepaper, we describe how executive and IT management can get and maintain control of their company's data architecture to help meet business objectives. We describe the relationship between data integration projects and data architecture concepts and practices. We describe how the business planning and IT development processes that direct and leverage data integration projects depend on tooling. We describe breakthrough ways in which data architects, business analysts, programmers, and business users can collaborate to address their organization's pressing business challenges.
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enterprise, soa, technology, liaison, business, data integration, data architecture, it management
    
Liaison Technologies
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