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analytics insights

Results 126 - 150 of 282Sort Results By: Published Date | Title | Company Name
By: Alteryx, Inc.     Published Date: Sep 06, 2017
Read this whitepaper and see why the shift toward self-service data analytics is empowering leading analysts and analytic teams to improve processes, eliminate repetitive tasks, build better relationships with IT, and deliver deeper insights faster.
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Alteryx, Inc.
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.
By: IBM Watson Health     Published Date: Sep 29, 2017
In the world of value-based healthcare, your data is the key to extracting the most actionable insights that provide real value to your organization. But getting to those insights can prove difficult, especially if you have to connect disparate data sources. You need transparency into key insights that can help your team make more informed decisions for the success of your organization. In this listicle, we explore five ways an analytics solution can help you transform your organization through the power of insight. From risk modeling to predictive analytics, utilizing the right mix of analytics can improve patient outcomes and ultimately move your organization closer to your ideal value-based care model
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value-based care, analytics, insights, data, business intelligence, ehr, fee-for-service, cognitive, predictive, outcomes, infrastructure
    
IBM Watson Health
By: TIBCO Software     Published Date: Sep 12, 2018
The Internet of Things (IoT) didn’t just connect everything everywhere; It laid the groundwork for the next industrial revolution. Connected devices sending data was only one achievement of the IoT—but one that helped solve the problem of data spread across countless silos that was not collected because it was too voluminous and/or too expensive to analyze. Now, with advances in cloud computing and analytics, cheaper and more scalable factory solutions are available. This, in combination with the cost and size of sensors continuously being reduced, supplies the other achievement: the possibility for every organization to digitally transform. Using a Smart Factory system, all relevant data is aggregated, analyzed, and acted upon. Sensors, devices, people, and processes are part of a connected ecosystem providing: • Reduced downtime • Minimized surplus and defects • Deep insights • End-to-end real-time visibility
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internet of things, connected ecosystem, big data, operations monitoring, process control, analytical techniques
    
TIBCO Software
By: TIBCO Software     Published Date: May 16, 2019
Banks globally are betting big on artificial intelligence and machine learning to give them the technological edge they need for more real-time, personalized and predictive banking services. A framework will help both differentiate early winners and provide them with sustained advantages in intelligence. Download this IDC Analyst Infobrief to learn about how the world’s best banks are becoming more personal, more predictive, and more real-time than ever. What you will learn: 8 trends that reflect bank’s readiness for connected intelligence 9 pitfalls to avoid & 9 ways to bridge the gaps The personal, real-time and predictive building blocks of AI & ML for banks Notable leaders based on IDC Financial Insights’ research and their respective use cases Essential guidance from IDC to leading banks
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data, analytics, customer, banks, intelligence, capabilities, customers, insights, banking
    
TIBCO Software
By: Oracle     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle
By: Adobe     Published Date: Oct 14, 2019
Companies that put data at the centre of their business gain better insights and deliver more effective marketing. Data centricity at an organisational level is the priority for larger companies, mindful of the opportunities afforded by more scientific commercial decision-making and data-driven marketing. A focus on data alone in the context of customer analytics is not enough, however. Companies require insights from their data to deliver first-class customer experiences that give them a competitive advantage. Our global survey of more than 1,000 business respondents shows that companies are rightly focused on activities powered by actionable insights as opposed to focusing on data for its own sake. More effective segmentation and targeting (65%), and better marketing attribution (52%), are the top data-related priorities for marketers, while ‘technologists’ (including analysts, ecommerce, and IT professionals) are primarily focused on making their organisations more data-centric (50%
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Adobe
By: Workday     Published Date: Jun 14, 2019
Putting people analytics into practice can be difficult, but this eBook outlines six key steps that can guide you through the journey. Learn how to demystify the tools and processes that help you derive insights from your people data. Read now.
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workday, workforce technology, digital strategy
    
Workday
By: Workday     Published Date: Jul 05, 2019
"Putting people analytics into practice can be difficult, but this eBook outlines six key steps that can guide you through the journey. Learn how to demystify the tools and processes that help you derive insights from your people data. Read now."
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workday, workforce technology, digital strategy
    
Workday
By: Workday     Published Date: Jul 05, 2019
"Putting people analytics into practice can be difficult, but this eBook outlines six key steps that can guide you through the journey. Learn how to demystify the tools and processes that help you derive insights from your people data. Read now."
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workday, workforce technology, digital strategy
    
Workday
By: IBM     Published Date: Aug 31, 2012
As those hosting transactional data on System z today already realize, it is one of the most secure, highly available and reliable platforms on the market - now see how organizations are bringing their analytics to IBM System z to better harness their data and gain greater business insights while containing cost and reducing complexity.
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IBM
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
By: Adobe     Published Date: Oct 24, 2018
Adobe automates the process of turning insights into action by connecting Adobe Analytics to other solutions in Adobe Experience Cloud, including Adobe Target and Adobe Audience Manager. Four features make this possible: • Anomaly detection. The technology automatically analyzes trends and determines if they are statistically significant — in milliseconds. • Analyze play button. With analytics, you can take insights and connect them to your email, DMP, and personalization platform in seconds. • Intelligent alert. A built-in alerting system sends an SMS text or email when it detects an anomaly. There are also predictive algorithms that help you forecast how often the alert is likely to trigger. You can set these to only notify you of the most important changes. • Intelligent recommendations. It’s simply impossible to manually create every alert you might need, so Adobe is building machine learning directly into analytics to analyze users’ behaviors. Like a virtual data assistant, it co
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Adobe
By: Adobe     Published Date: Oct 24, 2018
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.
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Adobe
By: AWS     Published Date: Aug 20, 2018
A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated querying: ability to run a query across heterogeneous sources of data • Data consumption: support numerous types of analysis - ad-hoc exploration, predefined reporting/dashboards, predictive and advanced analytics
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AWS
By: AWS     Published Date: Nov 15, 2018
It isn’t always easy to keep pace with today’s high volume of data, especially when it’s coming at you from a diverse number of sources. Tracking these analytics can place a strain on IT, who must provide the requested information to C-suite and analysts. Unless this process can happen quickly, the insights grow stale. Download your complimentary ebook now to see how Matillion ETL for Amazon Redshift makes it easy for technical and business users alike to participate and own the entire data and analysis process. With Matillion ETL for Amazon Redshift, everyone from CTOs to marketing analysts can generate valuable business intelligence by automating data and analytics orchestrations.
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AWS
By: AWS     Published Date: Nov 15, 2018
"Getting the right analytics, quickly and easily, is important to help grow your organization. But analytics isn’t just about collecting and exploring data. The truly important step resides in converting this data into actionable insights. Acquiring these insights requires some planning ahead. While ease of deployment, time-to-insight, and cost are all important, there are several more assessments you need to take before choosing the right solution. Learn the 8 must-have features to look for in data visualization. Download this white paper to learn how TIBCO® Spotfire® in AWS Marketplace assist in providing you advanced, cost-effective analytics."
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AWS
By: AWS     Published Date: Jan 03, 2019
Managing your data can be a challenge, but establishing an analytics solution that every user can navigate, regardless of skillset, is where organizations often need help. TIBCO® Spotfire® features AI-driven data visualizations and dashboards, which helps enables each organizational role to discover and deliver valuable insights with ease. Riteway Sales and Marketing, which helps many Southeastern supermarkets execute strategies, leveraged the power of TIBCO Spotfire to better understand individual product performance throughout their stores, achieving exponentially faster time to insight than their previous solution allowed. Watch this on-demand webinar to learn how TIBCO Spotfire, when leveraged on Amazon Web Services cloud, can help you generate deep insights in minutes. You’ll learn: • How to generate relevant, actionable insights from any data, anywhere • Some of the best practices for leveraging AI-driven visual and predictive analytics solutions in the cloud • How to
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AWS
By: Artemis Health     Published Date: Feb 05, 2019
Self-insured employers are mining their health and benefits data to save costs and provide quality care for employees. Data is driving business decisions, but how do you get from millions of rows of data to a consumable graph to taking action? In this white paper, we’ll delve into data analytics best practices that help self-insured employers find actionable insights in their benefits data. • Which data sources will help you ensure you’re measuring the right thing at the right time • How to ensure data variety and choose key metrics • An example of a successful predictive analysis using benefits data
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Artemis Health
By: AWS     Published Date: Jun 20, 2018
Data and analytics have become an indispensable part of gaining and keeping a competitive edge. But many legacy data warehouses introduce a new challenge for organizations trying to manage large data sets: only a fraction of their data is ever made available for analysis. We call this the “dark data” problem: companies know there is value in the data they collected, but their existing data warehouse is too complex, too slow, and just too expensive to use. A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated q
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AWS
By: FICO     Published Date: Mar 02, 2018
The role of analytics in managing, improving and ultimately transforming supply chains cannot be understated. But what about the analytics themselves? FICO’s Zahir Balaporia and renowned author Tom Davenport use the term “The Analytics Supply Chain” to reflect that the actual analytics themselves parallel supply chains, with inherent challenges and problems if things “get stuck.” Rethinking analytics in these terms can not only improve supply chain performance, but also any other business problems you seek to solve. This article targets: · Steps in the analytics supply chain and the vital role of data and analytic models · How your predictions, recommendations and insights need to rely on similar attributes to finished manufactured products; · Key questions to ask yourself in determining where you need to fix your analytics supply chain.
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supply, chain, analytics, employee, optimization, organisations, productivity
    
FICO
By: Kronos     Published Date: Jul 26, 2017
Learn about HCM strategies such as using mobile technology to optimize communication; offering flexible working hours for work-life balance; managing employee absences for stronger compliance, cost control, and employee well-being; and using analytics for workforce insights.
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mobile technology, work life balance, cost control, employee satisfaction, workforce insights
    
Kronos
By: Tableau     Published Date: Apr 13, 2018
In this whitepaper, discover the benefits of expanding your analytics toolkit. Combine Excel’s data collection and management capabilities with Tableau’s intuitive, analytical power to transform your raw data into actionable insights. Focus on the questions that take your data beyond the spreadsheet. Read more at about this partnership.
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Tableau
By: FICO EMEA     Published Date: Jan 25, 2019
Communications service providers (CSPs) have long recognized the potential of data analytics. Yet their early efforts to pull actionable intelligence from the oceans of data they have access to were largely unsuccessful. Many tried a 'big bang' approach to building a central repository without knowing what they wanted to do with the data in it. The arrival of artificial intelligence (AI) – its machine learning subset in particular – has changed their thinking and approach. For this Quick Insights report, we surveyed 64 professionals from CSPs around the world who are applying, leveraging and/ or planning to deploy advanced analytics in some capacity at various points across the customer lifecycle.
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analytics, artificial intelligence, customer lifecycle, insights, telecom credit lifecycle, customer acquisition, optimisation
    
FICO EMEA
By: FICO EMEA     Published Date: Jan 25, 2019
A leading communication services company serving more than 50 million individual, business and government subscribers across the United States.
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analytics, artificial intelligence, customer lifecycle, insights, telecom credit lifecycle, customer acquisition, optimisation
    
FICO EMEA
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