data analyst

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Published By: Xiotech     Published Date: Apr 13, 2007
Organizations face a double whammy when it comes to data archive management. On one hand, the volume of digital and paper archives is growing exponentially. Industry analysts report that digital hard disk storage has grown 85 percent a year over the last eight years and 2.7 billion new sheets of paper are filed into folders every day.
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data archive, data management, storage, data warehousing, archive management, document search, search and retrieval, document management, document archive, xiotech
    
Xiotech
Published By: Adobe     Published Date: May 16, 2017
Programmatic advertising is full of complex patterns. Very similar to patterns in nature. Our guide, Brilliant Advertising, shows how fractals in nature perfectly describe the complexity of programmatic ads and pave the way for how you should approach creative assets. 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: Opalis     Published Date: Nov 06, 2006
Automating repetitive Data Center Operations into best practices makes response times faster, more reliable, and less costly. Learn how to extend your current IT systems to do more of the routine work, freeing up IT staff for higher-value projects.
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process automation, automation, business process automation, bpa, data centers, datacenter, datacenters, response time, cost control, spending, it automation, analyst report, opalis
    
Opalis
Published By: Winshuttle     Published Date: Dec 04, 2006
This paper describes 7 best practices that many companies have adopted in automating the upload of Excel data into SAP. Adopting these best practices will alleviate many of the pains that business users and IT analysts face in uploading Excel data to SAP.
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excel, sap, spreadsheet, spreadsheets, best practice, best practices, sap data, data entry, data management, data upload, winshuttle
    
Winshuttle
Published By: Clarus Systems     Published Date: Mar 18, 2008
Enterprise networks are going through massive change, and the convergence of voice and data including Communication deployments, upgrades, transformations and ongoing management remain a top priority. According industry analysts at Aberdeen Group, 61% are planning for Communications in the next two years. In order to get the most from their Unified Communications investment at the time of deployment and beyond, enterprises must leverage both active testing and configuration analysis techniques to certify and validate that environments are configured as designed.
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itil, clarus systems, ipt, ip telephony, unified communications, cisco, callmanager, best practices, voice engineering, pdioo, strategies, deployment, operations, day 1, day 2, clarusipc, automated testing, business intelligence, performance management, configuration management
    
Clarus Systems
Published By: Network Automation     Published Date: Dec 02, 2008
Every night for several years, the five Latin America offices of Michigan-based medical technology products manufacturer Stryker Corporation were forced to burn the midnight oil to turn their daily financials into a single consolidated report. Each office has its own independent ERP system, so the process required three hours to compile the data for each territory plus another 90 minutes for a financial analyst at division headquarters to merge the five spreadsheets into one document.
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network automation, automate professional, erp
    
Network Automation
Published By: SAS     Published Date: Dec 20, 2018
There’s no shortage of data scientist interview questions available online. You can find lists and lists of questions to ask data scientist recruits in an interview, but most of the questions focus on the technical and quantitative aspects of the job without considering the softer skills. Our list takes a different approach. If you’re hiring a data scientist, we recommend focusing on more than technical skills, and your interview questions should reflect that. Data scientists have a unique blend of skills; not only do they solve problems by squeezing information out of data, they also communicate results and persuade others to apply that information to their decisions. Remember that data scientists aren’t just ninja quantitative analysts, says Wayne Thompson, Chief Data Scientist at SAS. “You’re looking for more than technical skills. Logical reasoning agility, along with storyboarding skills are critical because these scientists must be able to solve problems iteratively in collabo
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SAS
Published By: Sponsored by HP and Intel®     Published Date: Nov 14, 2012
This report defines "tier-1" storage in the modern IT world and in the data centers and services that support it.
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data centers, data storage, tier one, virtualization, storage tiers
    
Sponsored by HP and Intel®
Published By: IBM     Published Date: Sep 06, 2013
In this IBM security report, we will take a look at the data we've gathered through our monitoring operations and the security intelligence generated by our analysts and incident response teams who interpret that data. Our aim is to help you gain important insights into the current threat landscape - with a close look at the volume of attacks, the industries most impacted , the most prevalent types of attacks and attackers, and the key factors enabling them.
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ibm, security services, cyber security intelligence, index, security report, security attacks, security protection, business security, data security, security intelligence index
    
IBM
Published By: Symantec     Published Date: Oct 07, 2014
Last year, Mac malware increased by 66% with a single, high-profile attack infecting over 600,000 machines. Malware authors are targeting unsuspecting Mac users and gaining access to organization's data. Still wondering whether Macs need protection? See what advice a senior strategic analyst at ESG has to share.
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enterprise, mac security, cybercrime, malware, data, high-profile attack, infection
    
Symantec
Published By: IBM     Published Date: Jan 09, 2014
Organizations are looking to eliminate data center complexity, sprawl and underutilization. This requires solutions that can boost efficiency and economics, while delivering high-performance capabilities. Read the white paper and see how users and industry analysts alike trust IBM Power Systems to break free from costly and impractical systems.
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it solutions, smart analytics, analytics systems, testimonials
    
IBM
Published By: ArborNetworks     Published Date: Feb 12, 2016
Ask any cybersecurity professional and she’ll tell you that her job is getting increasingly difficult. Why? Most will point to a combination of the dangerous threat landscape, IT complexity, and their overwhelming workload. These issues are driving a major transition in enterprise security. Large organizations must move beyond a threat prevention mentality to become proactive cyber-¬-attack “hunters” that constantly monitor their networks for signs of trouble. This shift to proactive hunting will require new technologies that collect, process, and analyze massive amounts of security data, offer intelligent security analytics for real-¬-time incident detection, integrate threat intelligence to align suspicious internal activities with external threats, and provide analysts with the right data analytics features to query and manipulate data for historical investigations.
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arbor networks, enterprise, cyber attack, network, data
    
ArborNetworks
Published By: Lookout     Published Date: Mar 28, 2017
The data that you’ll see throughout this book is the result of a survey commissioned by Lookout and conducted by Enterprise Strategy Group, an integrated IT research, analyst, strategy, and validation firm.
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enterprise, mobile, security, survey, commission, lookout
    
Lookout
Published By: Dun & Bradstreet     Published Date: Feb 21, 2017
As the volume of data coming into organizations – from both internal and external sources – continues to grow and makes its way across departmental systems in many different formats, there is a critical need to create a single, holistic view of the key data entities in common use across the enterprise. Master Data Management (MDM) aims to accomplish this goal. Not surprisingly, MDM has become a significant priority for global enterprises, with the market expected to triple from $9.4B to $26.8B by 2020 according to analysts. The reality, though, is that while seemingly everyone is investing heavily in the tools to manage data, few are putting a great enough emphasis on the data itself. And that’s a problem. Poor data quality is said to be costing businesses $3.1 trillion annually – and that’s just in the US alone. The information being put into MDM tools must be mastered first and foremost.
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managing data, data management insight, mdm, master data management
    
Dun & Bradstreet
Published By: Q2 eBanking     Published Date: Jul 30, 2017
Many financial institutions see their customer data as one of their most valuable assets. Unlocking insights from that data helps FIs understand, anticipate and offer account holders the products and services they truly need. A major trend to unlocking customer insights is using machine learning to surface the behavioral intelligence buried in the large amount of account holder transactional data captured each and every day. In this paper, learn how a group of talented, enthusiastic analysts with an open approach to data can yield some very interesting and extremely valuable and actionable results. This approach, championed by Q2 Executive Vice President and CTO Adam Anderson, has led to a new platform, Q2 SMART, which provides powerful behavioral analytics for financial institutions, enabling growth while providing account holders with real value.
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Q2 eBanking
Published By: Group M_IBM Q1'18     Published Date: Jan 08, 2018
Effectively using and managing information has become critical to driving growth in areas such as pursuing new business opportunities, attracting and retaining customers, and streamlining operations. In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before. These needs create a daunting array of workload challenges and place tremendous demands on your underlying IT infrastructure and database systems. This e-book 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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database, streamlining, it infrastructure, database systems
    
Group M_IBM Q1'18
Published By: Group M_IBM Q119     Published Date: Feb 15, 2019
With the increasing complexity and volume of cyberattacks, organizations must have the capacity to adapt quickly and confidently under changing conditions. Accelerating incident response times to safeguard the organization's infrastructure and data is paramount. Achieving this requires a thoughtful plan- one that addresses the security ecosystem, incorporates security orchestration and automation, and provides adaptive workflows to empower the security analysts. In the white paper "Six Steps for Building a Robust Incident Response Function" IBM Resilient provides a framework for security teams to build a strong incident response program and deliver organization-wide coordination and optimizations to accomplish these goals.
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Group M_IBM Q119
Published By: Group M_IBM Q2'19     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 Q2'19
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