data and analytics

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Published By: Aberdeen Group     Published Date: Nov 13, 2015
Aberdeen’s Content Marketing survey revealed that while 95% of marketers are using or considering using a content marketing strategy, there are some distinct differences between those using content well and those just using content. The Best-in-Class are not only creating content at volume, they are taking a much more data-driven approach to their content marketing strategy — and it’s paying off. Find out how.
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customer acquisition, marketing leads, marketing challenges, marketing messages, contact management, data science, demand generation, email marketing, inbound marketing, lead generation, lead intelligence, market research, integrated marketing, lead nurturing, marketing analytics
    
Aberdeen Group
Published By: Aberdeen Group     Published Date: Nov 13, 2015
Aberdeen’s research shows that 90% of Best-in-Class marketers report fueling lead generation efforts with content marketing. What do you need to know to follow this best practice of the Best-in-Class? That’s exactly what this Knowledge Brief is intended to uncover.
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customer acquisition, marketing leads, marketing challenges, marketing messages, contact management, data science, demand generation, email marketing, inbound marketing, lead generation, lead intelligence, market research, integrated marketing, lead nurturing, marketing analytics
    
Aberdeen Group
Published By: Aberdeen Group     Published Date: Nov 13, 2015
This report examines the pressing need to break down data silos due to the damage they cause to analytical initiatives and user engagement. Read this report to find out more.
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customer acquisition, marketing leads, marketing challenges, marketing messages, contact management, data science, demand generation, email marketing, inbound marketing, lead generation, lead intelligence, market research, integrated marketing, lead nurturing, marketing analytics
    
Aberdeen Group
Published By: Aberdeen Group     Published Date: Nov 23, 2015
This report examines the pressing need to break down data silos due to the damage they cause to analytical initiatives and user engagement. Read this report to find out more.
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customer acquisition, marketing leads, marketing challenges, marketing messages, contact management, data science, demand generation, email marketing, inbound marketing, lead generation, lead intelligence, market research, integrated marketing, lead nurturing, marketing analytics
    
Aberdeen Group
Published By: Adobe     Published Date: Jun 29, 2012
The volume of customer data that marketing departments possess continues to grow at explosive rates. But new research from the Aberdeen Group finds that less than 40% of marketers use this information to optimize and target their campaigns. This "data rich, insight poor" phenomenon is examined in their new white paper, which identifies common analytics challenges-and shows how you can rise above them.
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adobe, cmo, analytics, marketing, aberdeen, optimize, campaign, optimization
    
Adobe
Published By: Adobe     Published Date: Aug 22, 2013
Some people want more "likes" because their goal is increased awareness. Others may struggle with losing customers and want improved customer service to reduce churn rates. Whichever challenge your strategy is trying to solve, you will find only a short-term solution if you deal with each challenge in isolation. What you need is an integrated approach that puts social media at the heart of your business as a solid foundation for long-term growth.
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customer experience management, social media data, web trends and analytics
    
Adobe
Published By: Adobe     Published Date: Apr 17, 2014
Discover new opportunities for maturing your data practices—and building your business results. You’ll learn how to move beyond mere web analytics to build a more comprehensive marketing analytics approach that includes mobile, social, and offline channels. And you’ll see how your current analytics capabilities compare to those of similar organizations and where you have opportunities for improvement.
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adobe, analytics, marketing, data collection, data automation, marketing automation, web analytics, marketing analytics, data exploration, automation technology, data practices, marketing solutions
    
Adobe
Published By: Adobe     Published Date: Aug 02, 2017
With the advanced analytics capabilities in Adobe Analytics and the testing and targeting capacity of Adobe Target, it’s easier than ever to realise the potential of data-driven marketing. From creating a complete view of each customer across touchpoints and along their journey, to using predictive analytics, advanced anomaly detection and machine learning to understand behaviours and needs, you can use data to plan, create and optimise the experiences that matter to you and your customers.
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data management, data system, business development, software integration, resource planning, enterprise management, data collection
    
Adobe
Published By: Adobe     Published Date: Apr 03, 2015
A lack of executive support and poor data quality are just some reasons why analytics programs fail. The guide by Adam Greco, Reenergize Your Web Analytics, identifies the key reasons for program failures and provides ten ways to make your analytics program successful. Read the guide to discover key ways to improve your analytics program, including: • How to deal with your stakeholders • How to set your analytics priorities • How to reap the rewards of change
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analytics program, stakeholders, adobe, marketing, personalization
    
Adobe
Published By: Adobe     Published Date: May 15, 2018
Adobe is the only Leader in Digital Intelligence Platforms. Digital intelligence with scope and depth. Your customers come to you from different places, so your data insights should do the same thing. Adobe Experience Cloud’s digital marking and analytics solutions help you combine insights from existing, new, and emerging channels. Read the Forrester Wave™: Digital Intelligence Platforms, Q2 2017 to find out why we stand alone among DI platform vendors.
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Adobe
Published By: Adobe     Published Date: Oct 11, 2018
Adobe offers powerful personalization tools that help you give your customers custom experiences every time they interact with you. With Adobe, you can take control of your data, use AI to achieve scale, and see incredible results. Adobe Target helps marketers deliver relevant, personalized experiences to highly targeted audiences based on behavioral analytics and audience data. Powered by AI and machine learning, users can deliver individualized customer experiences at massive scale.
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Adobe
Published By: Adobe     Published Date: Nov 09, 2017
Marketing leaders are asking their analytics teams to provide better insights into customers, prospects and journeys, and a more accurate assessment of the impact of marketing tactics. Use this research to find a digital marketing analytics tool to support your needs. This Magic Quadrant is intended for chief marketing of?cers (CMOs), marketing analytics and data science practitioners, and other digital marketing leaders involved in the selection of systems to support marketing analytics requirements.
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Adobe
Published By: Adobe     Published Date: May 04, 2018
Adobe is the only Leader in Digital Intelligence Platforms. Digital intelligence with scope and depth. Your customers come to you from different places, so your data insights should do the same thing. Adobe Experience Cloud’s digital marking and analytics solutions help you combine insights from existing, new, and emerging channels. Read the Forrester Wave™: Digital Intelligence Platforms, Q2 2017 to find out why we stand alone among DI platform vendors.
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Adobe
Published By: ADP     Published Date: Nov 16, 2017
Many businesses invest in analytics technology thinking it’s a silver bullet. But data doesn’t always tell the whole story. You get percentages but not insights. Trends but not necessarily relationships or patterns. Truly impactful workforce analytics has to do more. You have to turn data into insight, and then put it into action. This workbook is designed to help you progress through the workforce analytics maturity model. The first step in the process is to identify where you stand today.
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ADP
Published By: ADP     Published Date: Nov 16, 2017
People are the most important part of your organization. Understanding what they do, how they do it, and even why they do it, provides invaluable insights for optimizing your processes, department, or entire organization. And as a business leader, in many ways you’ve never had it so good. There’s more people data available than ever before, and you’ve got the opportunity to put it to work through data-driven initiatives like changes to workforce demographics, employee retention, or benefits allocations. And most important, you have a chance to fuel business decision-making with smart workforce insights. Once you’ve learned how to turn your people data into real business value, you’ll create more visibility within your business, and everyone will see that the rewards of HR analytics are worth the effort. It’s time to take the opportunity to prove the value of data-driven HR. No more darkness. Otherwise, the only journey ahead is into some challenging pitfalls. We’ve identified five of t
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ADP
Published By: Advizex     Published Date: Sep 25, 2013
The challenge of Big Data is more than a question of size; it’s about time to insight and action. With the exponential growth of unstructured data such as social media, video and the raw data generated by smartphones and other “intelligent” machines, businesses are buried under an avalanche of data that renders even best-effort analytics slow and sometimes unreliable. As many businesses are learning in this age of Big Data, it’s not just what you know, but when you know it and how much you trust it. Download this white paper and learn that with SAP HANA, companies can react intelligently at the speed of thought to capture new opportunities.
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sap hana, sap, real time analytics, raw data, generation, analytics, big data, business intelligence, trusting big data, insight, action, knowledge management, enterprise applications, data management
    
Advizex
Published By: Akamai     Published Date: Jun 04, 2010
Predictive analytics have been used by different industries for years to solve difficult problems that range from detecting credit card fraud to determining patient risk levels for medical conditions. It combines data mining and machine-learning technologies to create statistical models based on historical data. It then uses these models to predict future events. Extracting the power from the data requires powerful algorithms behind predictive analytics.
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akamai, predictive, online advertising, tracking pixels, online shopping, in-market, site visitors, performance marketing
    
Akamai
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
As a financial services provider, you have probably invested hundreds of thousands, if not millions of dollars, in building an analytic infrastructure. But, do your line-of-business analysts and managers have access to the data and insights they need, when they need them? Three ways Alteryx can help you improve customer experience, manage risk and increase operational efficiency Case studies on how your peer financial services companies are using self-service data analytics for a competitive edge
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Alteryx, Inc.
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
The traditional multiple-step, multi-tool legacy approach is a slow, time-consuming, and in most cases, a costly process that prevents organizations from making faster decisions with confidence. Data analysts today need an agile solution that empowers them to take charge of the entire analytics process. Download The Definitive Guide to Self-Service Data Analytics to: Understand why traditional analytic tools designed for data scientists are not ideal for data analysts like you Learn how self-service data analytics delivers the ease of use, speed, flexibility, and scalability you require See how Alteryx stacks up against traditional data prep and analytics tools
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Alteryx, Inc.
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: Alteryx, Inc.     Published Date: Sep 06, 2017
In order to improve competitive advantage, decision making, and operational efficiencies, many of today’s leading organizations are creating an Office of the Chief Data Officer. According to Gartner, “90 percent of large companies will have a CDO role by the end of 2019”.
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Alteryx, Inc.
Published By: Alteryx, Inc.     Published Date: Sep 06, 2017
According to Forrester, the level of analytic satisfaction within organizations is on the decline.* The traditional multiple-step, multi-tool legacy approach is a slow, time-consuming, and in most cases, a costly process that prevents organizations from making faster decisions with confidence. Data analysts today need an agile solution that empowers them to take charge of the entire analytics process. Download The Definitive Guide to Self-Service Data Analytics to: Understand why traditional analytic tools designed for data scientists are not ideal for data analysts like you Learn how self-service data analytics delivers the ease of use, speed, flexibility, and scalability you require See how Alteryx stacks up against traditional data prep and analytics tools Find out how self-service data analytics bridges the gap across skills, speed, and depth of analysis to empower you to achieve ever-greater insights without coding or depending on other departments.
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Alteryx, Inc.
Published By: Alteryx, Inc.     Published Date: Sep 07, 2017
Download now and learn how Alteryx and Microsoft Power BI help accelerate data blending and advanced analytics consumption for everyone in your organization.
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Alteryx, Inc.
Published By: Amazon Web Services     Published Date: Oct 09, 2017
As easy as it is to get swept up by the hype surrounding big data, its just as easy for organisations to become discouraged by the challenges they encounter while implementing a big data initiative. Concerns regarding big data skill sets (and the lack thereof), security, the unpredictability of data, unsustainable costs, and the need to make a business case can bring a big data initiative to a screeching halt. However, given big data's power to transform business, it's critical that organisations overcome these challenges and realise the value of big data. The cloud can help organisations to do so. Drawing from IDG's 2015 Big Data and Analytics Survey, this white paper analyses the top five challenges companies face when undergoing a big data initiative and explains how they can effectively overcome them.
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amazon, web services, intel, migration, data warehousing, organization optimization, security, software
    
Amazon Web Services
Published By: Amazon Web Services     Published Date: Oct 09, 2017
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyse data that addresses many of these challenges. Data Lakes allow an organization to store all of their data, structured and unstructured, in one, centralized repository.
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cost effective, data storage, data collection, security, compliance, platform, big data, it resources
    
Amazon Web Services
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