data analyst

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Published By: DataFlux     Published Date: Jan 07, 2011
This white paper addresses data profiling techniques that can help the analyst understand the empirical truth associated with enterprise data.
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dataflux, data profiling, enterprise data, analyst, data rule validation, metadata compliance
    
DataFlux
Published By: Adobe     Published Date: Oct 24, 2018
The report combines data from a February 2018 executive survey of 401 email marketers and documented ESP demos related to three key themes. We also utilized vendor questionnaires and our near two-decades of knowledge of the providers in this sector. One-on-one phone interviews with several of the marketers who use these tools and our executive survey clients provided satisfaction data. The methodology details our entire recipe, but readers can feel confident in knowing that our vendor evaluation process is objective and does not stem from one analyst’s singular point of view. This guide also includes our analysis and perspective on vendors that did not for a variety of reasons participate in this research.
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Adobe
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
Data Analytics has become critical for many business decision makers. However, many of these managers and data analysts still rely on spreadsheets and other legacy-era tools that fall far short of current needs. As a result, they also rely heavily on a virtual army of data specialists and scientists, working under the auspices of a centralized analytics group, to prepare, blend, analyze, and even report on the critical data they need for decision making. Download this new paper to get the details behind self-service data analytics, and how it lets business analysts: Take charge of the entire analytical process, instead of relying on other departments Overcome limitations of legacy tools to save time and prevent errors Make more comprehensive and insightful business decisions at speed
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Alteryx, Inc.
Published By: Amazon     Published Date: Nov 07, 2013
Until recently, it has been far cheaper and easier to produce and store data than to process it. Companies have the option to buy large, multi-million dollar hardware devices to process their big data, but with budgets under pressure and no clear way to calculate returns on investment, the business case is difficult to make… And when analysts explain to the CTO that they only need the hardware for six months, for one day a week, or for one hour a day, the investment becomes impossible to justify. In this whitepaper, you’ll learn how by eliminating the traditionally high ‘cost of entry’ for big data analysis, Amazon Web Services is enabling customers to convert more raw data into more valuable business insight.
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amazon web services, aws, aws cloud, cloud services, cloud computing, big data, data management, data analysis, insights, customer sentiment, big data analysis
    
Amazon
Published By: Splunk     Published Date: Aug 21, 2018
Alice Bluebird, a quirky security analyst for hire, is hunting down a nation state of hackers thirsty for the recipes of Frothly, a cutting-edge craft brewery. Follow Alice as she works to solve the mystery of the breach. Did she catch the incident before the hackers managed to steal Frothly’s super secret formulas? Did the hackers act alone or — scarier yet In this light hearted graphic novel “Through the Looking Glass Table”, discover how machine data, as well as an analytics-driven platform, log management, SIEM, UEBA and SOAR solutions, can help anyone — IT managers and sophisticated SOC analysts — better understand and respond to incidents, breaches, phishing attempts, insider threats and more.— did they have help from the inside?
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Splunk
Published By: Select Hub     Published Date: Nov 07, 2017
Interactive analyst report gives you comparison ratings, reviews and pricing from actual software selection projects. Unlike some ratings, SelectHub product scores are taken from multiple sources including top analysts and actual buyers of the software—ideal for your shortlist. Find the right BI analytics tools: • Actionable insights from experts: In plain language, find out how each product supports the functions that matter most to your company. • Key requirements criteria: Get a comprehensive list of the key requirements for use in your software evaluation and vendor selection. • Easy pricing: Get recommendations and pricing for solutions matching your business needs. • Includes practical guide: How to Buy Business Intelligence Software Over 80 business analytics and BI tools evaluated. The SelectHub platform contains expert software analysis across key criteria and vendor data. These built-in analyst ratings are combined with subjective user ratings to create SelectHub ratings r
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Select Hub
Published By: IBM     Published Date: Jan 27, 2017
In today’s highly distributed, multi-platform world, the data needed to solve any particular decision making need is increasingly likely to be found across a wide variety of sources. As a result, traditional manual approaches requiring prior collection, storage and integration of extensive sets of data in the analyst’s preferred exploration environment are becoming less useful. Data virtualization, which offers transparent access to distributed, diverse data sources, offers a valuable alternative approach in these circumstances.
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IBM
Published By: TIBCO Software     Published Date: Aug 13, 2018
Whilst businesses of all kinds are utilizing data analytics, many are still only using it to make simple changes that lead to a set of rigid processes. Whereas the more customer-focused organizations are realizing that to deliver exceptional experiences, they need to be able to react to customer data in real-time and predict what might happen next. And that means going beyond simple analytics. Read our whitepaper to discover what analyst firm Forrester has identified as the Enterprise Insight Platform, technology designed to enable companies to transform into truly data-driven businesses.
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TIBCO Software
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: IBM     Published Date: Nov 30, 2017
Analyst firm, Enterprise Strategy Group, examines how companies can leverage cloud-based data lakes and self-service analytics for timely business insights that weren’t possible until now. And learn how IBM Cloud Object Storage, as a persistent storage layer, powers analytics and business intelligence solutions on the IBM Cloud. Complete the form to download the analyst paper.
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analytics, technology, digital transformation, data lake, always-on data lake, ibm, cloud-based analytics
    
IBM
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: Arcserve     Published Date: May 29, 2015
Find out what you need to know about data protection appliances in this video brief by the Enterprise Strategy Group’s Sr. Data Protection Analyst, Jason Buffington. In this short video he’ll analyze: -Various types of data protection appliances -Market trends regarding appliance adoption -What data protection specialists expect from appliances -How Arcserve has evolved to solve the issues of today’s complex organizations Watch this video brief today!
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data protection appliances, appliance adoption, arcserve, security
    
Arcserve
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: 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: 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: 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: IBM     Published Date: Nov 30, 2017
Analyst firm, Enterprise Strategy Group (ESG), makes the case for storing backup, archive and content repository data in the cloud. Learn how IBM Cloud Object Storage addresses these use cases and helps companies lower costs, provide higher availability and protect against unauthorized access to their data. Complete the form to download the analyst paper
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ibm cloud, archival solutions, ibm, it services, storage, production storage, data management
    
IBM
Published By: Sage Software     Published Date: Jun 20, 2018
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, less than half of an organization’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.
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sage enterprise management, bms, erp, bom, enterprise accounting, enterprise intelligence, drp, enterprise, mrp
    
Sage Software
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: 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: SnowFlake     Published Date: Jul 08, 2016
Today’s data, and how that data is used, have changed dramatically in the past few years. Data now comes from everywhere—not just enterprise applications, but also websites, log files, social media, sensors, web services, and more. Organizations want to make that data available to all of their analysts as quickly as possible, not limit access to only a few highly-skilled data scientists. However, these efforts are quickly frustrated by the limitations of current data warehouse technologies. These systems simply were not built to handle the diversity of today’s data and analytics. They are based on decades-old architectures designed for a different world, a world where data was limited, users of data were few, and all processing was done in on-premises data centers.
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snowflake, data, technology, enterprise, application, best practices, social media
    
SnowFlake
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