data analytics

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By: Google     Published Date: Jan 08, 2018
Today’s smart computers can beat board game champions, master video games, and learn to recognize cats. No wonder artificial intelligence has captured the imaginations of business and IT leaders. And indeed, AI is starting to transform processes in established industries, from retail to financial services to manufacturing. Read this guide from Google Cloud and learn how you can unlock the transformational power of information and get useful insights from a vast and complex landscape of data.
Tags : data analytics, machine learning, big data, artificial intelligence
     Google
By: Group M_IBM Q1'18     Published Date: Jan 08, 2018
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements. To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
Tags : cloud, database, hybrid cloud, database platform
     Group M_IBM Q1'18
By: Tricentis     Published Date: Jan 08, 2018
Data. It seems to be everywhere today and yet we can never get enough of it. But as it turns out, a lack of data isn’t our problem -- our problem is the difficulty piecing together, understanding and finding the story in all the data that’s in front of us. In software testing in particular, the need for consolidated, meaningful test metrics has never been higher. As both the pace of development and the cost of delivering poor quality software increase, we need these metrics to help us test smarter, better and faster. Fortunately, business intelligence now exists to make this goal a reality. The analytics these tools provide can help drive efficient and effective testing by providing teams with insight on everything from testing quality and coverage to velocity and more. And this knowledge can position the QA team as trusted experts to advise the entire software development team on steps that can ensure a better quality end result.
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     Tricentis
By: Cardinal Health     Published Date: Dec 28, 2017
Data driven tools and analytics can uncover a wealth of new savings opportunities for surgery centers and surgical hospitals. And you usually don’t have to search far to uncover the savings. You can immediately tap into one source of data to find these opportunities. Every Electronic Health Record (EHR) and Practice Management System offers a set of standard reports. Stored inside are at least five ways to save. Download this whitepaper to learn about these five opportunities
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     Cardinal Health
By: MoreVisibility     Published Date: Dec 19, 2017
As the approach to strategic business decision making becomes more and more data driven, a method for consolidating our various data sets, which are often spread across multiple systems becomes exceedingly important. Two of the biggest players in data driven decision making are website analytics platforms and customer relationship management systems. The former includes accumulating data on top of the funnel behavior such as site traffic origins, lead generation, content consumption tracking, device usage, and overall site behavior. While the latter has a focus more on bottom of the funnel activity such as lead nurturing, customer status, lifetime value, etc. Lastly, without communication between these two essential platforms, a complete understanding of your customers, from lead to longtime client, may never be possible. A web analytics (Google Analytics) and CRM integration provides you with a 360 degree view of your customer base, so that you can understand not just what PPC efforts
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     MoreVisibility
By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
As organizations develop next-generation applications for the digital era, many are using cognitive computing ushered in by IBM Watson® technology. Cognitive applications can learn and react to customer preferences, and then use that information to support capabilities such as confidence-weighted outcomes with data transparency, systematic learning and natural language processing. To make the most of these next-generation applications, you need a next-generation database. It must handle a massive volume of data while delivering high performance to support real-time analytics. At the same time, it must provide data availability for demanding applications, scalability for growth and flexibility for responding to changes.
Tags : database, applications, data availability, cognitive applications
     Group M_IBM Q1'18
By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements. To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
Tags : cloud, database, hybrid cloud, database platform
     Group M_IBM Q1'18
By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
There can be no doubt that the architecture for analytics has evolved over its 25-30 year history. Many recent innovations have had significant impacts on this architecture since the simple concept of a single repository of data called a data warehouse.
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     Group M_IBM Q1'18
By: AWS     Published Date: Dec 15, 2017
Healthcare and Life Sciences organizations are using data to generate knowledge that helps them provide better patient care, enhances biopharma research and development, and streamlines operations across the product innovation and care delivery continuum. Next-Gen business intelligence (BI) solutions can help organizations reduce time-to-insight by aggregating and analyzing structured and unstructured data sets in real or near-real time. AWS and AWS Partner Network (APN) Partners offer technology solutions to help you gain data-driven insights to improve care, fuel innovation, and enhance business performance. In this webinar, you’ll hear from APN Partners Deloitte and hc1.com about their solutions, built on AWS, that enable Next-Gen BI in Healthcare and Life Sciences. Join this webinar to learn: How Healthcare and Life Sciences organizations are using cloud-based analytics to fuel innovation in patient care and biopharmaceutical product development. How AWS supports BI solutions f
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     AWS
By: FICO     Published Date: Dec 04, 2017
Whether you’re onboarding new customers, cross- or up-selling, getting your supply chain or logistics right, or even collecting unpaid debt, making the best choice of decisions means weighing not just what’s right for your department – but what is best for the business overall. Not to mention what is optimal for your customers and partners. And let’s face it, even with the availability of business intelligence and other analytic tools, it’s hard to know what constitutes the right actions to take in an era where Big Data consistently throws you curveballs. Prescriptive Analytics can help – but for most organizations, there are more questions and concerns than answers about how to implement it successfully. Read our white paper on how Prescriptive Analytics can transform your business decisions and actions – leveraging your existing analytics investment and organizational DNA while helping you drive transparency, customer experience, and profits
Tags : business, results, optimal, customer, experience, tools, analytics, big data
     FICO
By: Sage People     Published Date: Dec 04, 2017
The more you know about your people, the more you can enable them to do their best work. And in turn, the greater the chance of business success. Yet, a rapidly changing world of work makes it difficult for companies to achieve this. There is a growing global skills crisis, and it’s getting worse. A shortage of skilled people makes it tough to find and attract the people you need — and it’s even tougher to get them through the door once you find them. To win the war for talent, you need to understand and engage with your candidates better than ever before.
Tags : data, reporting, analytics, insights, science, sage, solutions
     Sage People
By: MarkLogic     Published Date: Nov 30, 2017
The OPDBMS market in 2017 brings cloud and fully managed options center stage for execution. Market-defining vision includes features for machine learning, serverless scenarios and streaming integration. Data and analytics leaders must balance current and future needs against this market landscape.
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     MarkLogic
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.
Tags : analytics, technology, digital transformation, data lake, always-on data lake, ibm, cloud-based analytics
     IBM
By: Anaplan     Published Date: Nov 27, 2017
"The pressure on sales to meet and exceed ever-increasing revenue targets is higher than ever before. At the heart of this challenge lies a complex analytical and modeling problem that involves data spread across many rigid–and usually disconnected–systems, teams, and geographies. Leading companies handle this problem by focusing first on creating a sales performance plan that is data-driven and tied to business objectives. The research report conducted by Harvard Business Review provides you with how today's sales executives: • Overcome technology weaknesses to uncover sophisticated analytics • Change ingrained, cultural tendances of sales organizations • Adopt dynamic practices to respond to change quicker"
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     Anaplan
By: IBM APAC     Published Date: Nov 22, 2017
A user initiates the call and selects the source language, such as Spanish. (In this example, assume that the target language is set to English.) As the user is talking to the support representative, the audio is converted to text using the Speech to Text service. Then using Language Translator, the text is translated to English. English language text is then sent to the Text to Speech service as input. The output audio message is what the support representative hears. All of this happens in near real time. The text from Speech to Text and the Language Translator service also can be stored in a database for analytics. The same process is repeated in reverse for the audio message sent by support personnel.
Tags : source, language, english, spanish, speech to text, database, analytics, audio message, support
     IBM APAC
By: IBM APAC     Published Date: Nov 22, 2017
Using IBM Watson’s cognitive capabilities, companies can quickly differentiate their customer service quality by being more pro active and responsive to customer needs. Simply put, chatbots and virtual agents are the future of customer interactions. Building apps from scratch that incorporate natural language processing, speech to text recognition, visual recognition, analytics, and artificial intelligence requires broad expertise in these disciplines, large staffs, and a huge financial commitment. Making use of IBM Watson cognitive services brings these capabilities in-house quickly and without the capital investment that would be needed to develop the technologies within an organization.
Tags : decision making, deeper data, insights, cognitive, analytics, ibm, watson, virtual agents
     IBM APAC
By: Intel Corp.     Published Date: Nov 21, 2017
This whitepaper will provide an overview on how powerful computing and software technologies enable real time fraud detection to cut losses and reduce risks.
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     Intel Corp.
By: Intel Corp.     Published Date: Nov 21, 2017
A Pathfinder paper navigates decision-makers through the issues surrounding a specific technology or business case, explores the business value of adoption, and recommends the range of considerations and concrete next steps in the decision-making process.
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     Intel Corp.
By: Intel Corp.     Published Date: Nov 21, 2017
This whitepaper will power your anti-money laundering compliance programs with technology that keeps up with evolving threats and regulatory mandates.
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     Intel Corp.
By: IBM Watson Health     Published Date: Nov 21, 2017
The shift to value-based care means that healthcare organizations should expand their concept of return on investment (ROI) to include the ability of solutions to increase efficiency and contain healthcare costs. Data analytics and automation capabilities have become important tools for providers aiming to maximize value-based payments. Learn from this whitepaper about the best ways for healthcare organizations to measure health IT ROI in the value-based environment, including specific examples of how certain providers are approaching this challenge.
Tags : value-based care, healthcare costs, health outcomes, health it, health information technology, hospital performance, operational performance, hospital performance improvement, operational performance, operational benchmarks, comparative analysis, post-acute network alignment, provider alignment, hospital spending, hospital financial benchmarks, hospital operational benchmarks
     IBM Watson Health
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
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
By: MemSQL     Published Date: Nov 15, 2017
FREE O'REILLY EBOOK: BUILDING REAL-TIME DATA PIPELINES Unifying Applications and Analytics with In-Memory Architectures You'll Learn: - How to use Apache Kafka and Spark to build real-time data pipelines - How to use in-memory database management systems for real-time analytics - Top architectures for transitioning from data silos to real-time processing - Steps for getting to real-time operational systems - Considerations for choosing the best deployment option
Tags : hardware trends, data pipelines, database management, architectures, technology
     MemSQL
By: MemSQL     Published Date: Nov 15, 2017
The Path to Predictive Analytics and Machine Learning This Ebook will be your guide to building and deploying scalable, production-ready machine-learning applications. Inside, you will find several machine learning use cases, code samples to help you get started, and recommended data processing architectures.
Tags : data pipelines, analytics, database, machine learning
     MemSQL
By: MemSQL     Published Date: Nov 15, 2017
Pairing Apache Kafka with a Real-Time Database Learn how to: ? Scope data pipelines all the way from ingest to applications and analytics ? Build data pipelines using a new SQL command: CREATE PIPELINE ? Achieve exactly-once semantics with native pipelines ? Overcome top challenges of real-time data management
Tags : digital transformation, applications, data, pipelines, management
     MemSQL
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