data and analytics

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Published By: Qlik     Published Date: Oct 13, 2015
Data discovery appeals strongly to business users, but some business intelligence leaders are reluctant to ensure adoption. Data discovery is filling the gap between traditional BI and advanced analytics, and this research explains why and how BI leaders should support its use.
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qlik, data discovery, business intelligence, analytics, user produced content, data management, business technology
    
Qlik
Published By: Microsoft Office 365     Published Date: Nov 15, 2016
Download the free A to Z eBook to learn more about data security, employee productivity, IT Support and cost. Also, see how the competition measures up against Office 365. Here are a few must-knows when it comes to Office 365: Data compliance out of the box. Built-in security and privacy features; meets key industry standards and supports FERPA, HIPPAA and EU. Online or offline across all devices. Whether you are in the office or on the go, Office applications let you create, edit and share from your PC/MAC or your iOS, Android™ or Windows device with anyone in real time. Work off a single platform and eliminate third-party apps. With our suite of apps, such as Enterprise Content Management, Cloud PBX, and Microsoft MyAnalytics, you can trust that a single vendor is providing you the tools you need to get work done.
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Microsoft Office 365
Published By: IBM     Published Date: Jul 20, 2016
Big data. We've heard the phrase for quite some time, but how can human resource leaders get into the action? One way is through the development and implementation of talent analytics strategies. Talent analytics is fundamentally changing the way organizations and practitioners are thinking about the role of HR and organizations uncovering never before seen insights.
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ibm, talent acquisition, talent acquisition technology, human resources, recruiting, human resource technology
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
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. Download this white paper to learn how.
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database, big data, analytics, infrastructure, data management, data center
    
IBM
Published By: AWS     Published Date: May 18, 2018
We’ve become a world of instant information. We carry mobile devices that answer questions in seconds and we track our morning runs from screens on our wrists. News spreads immediately across our social feeds, and traffic alerts direct us away from road closures. As consumers, we have come to expect answers now, in real time. Until recently, businesses that were seeking information about their customers, products, or applications, in real time, were challenged to do so. Streaming data, such as website clickstreams, application logs, and IoT device telemetry, could be ingested but not analyzed in real time for any kind of immediate action. For years, analytics were understood to be a snapshot of the past, but never a window into the present. Reports could show us yesterday’s sales figures, but not what customers are buying right now. Then, along came the cloud. With the emergence of cloud computing, and new technologies leveraging its inherent scalability and agility, streaming data
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AWS
Published By: AWS     Published Date: Sep 04, 2018
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics.
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AWS
Published By: AWS     Published Date: Sep 04, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. It’s designed for speed and ease of use — but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether you’ve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technology
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AWS
Published By: GE Power     Published Date: Oct 05, 2016
With any innovation, early adopters forge the path forward, testing the limits of new technology, proving solutions that deliver value and dispensing those that don’t. Each power organization approaches the use of data and analytics from their own point of reference, technology maturity and propensity for change. In this eBook, learn how 14 global power companies achieved real business results for their business with digital solutions.
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digital power plant, digital power, digital power station, distributor solution, efficiency of power generation, industrial power
    
GE Power
Published By: GE Power     Published Date: Feb 02, 2017
With any innovation, early adopters forge the path forward, testing the limits of new technology, proving solutions that deliver value and dispensing those that don’t. Each power organization approaches the use of data and analytics from their own point of reference, technology maturity and propensity for change. In this eBook, learn how 14 global power companies achieved real business results for their business with digital solutions.
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GE Power
Published By: GE Power     Published Date: Feb 02, 2017
From balancing asset life and performance to managing variations in market conditions and fuel costs, power leaders everywhere are using data and analytics as a strategic asset to drive efficiencies and increase profitability for their business.
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GE Power
Published By: IBM     Published Date: Oct 16, 2017
This white paper examines how some of the ways organizations use big data make their infrastructures vulnerable to attack. It presents recommended best practices organizations can adopt to help make their infrastructures and operations more secure. And it discusses how adding advanced security software solutions from IBM to their big-data environment can fill gaps that big-data platforms by themselves do not address. It describes how IBM® Security Guardium®, an end-to- end solution for regulatory compliance and comprehensive data security, supports entitlement reporting; user-access and activity monitoring; advanced risk analytics and real-time threat detection analytics; alerting, blocking, encryption and other data protection capabilities, as well as automated compliance workflows and reporting capabilities, to stop threats.
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security, big data, ibm, data protection
    
IBM
Published By: CrowdStrike     Published Date: Feb 01, 2017
One of the biggest challenges to effectively stopping breaches lies in sifting through vast amounts of data to find the subtle clues that indicate an attack is imminent or underway. As modern computer systems generate billions of events daily, the amount of data to analyze can reach petabytes. Compounding the problem, the data is often unstructured, discrete and disconnected. As a result, organizations struggle to determine how individual events may be connected to signal an impending attack. Download the white paper to learn: • How to detect known and unknown threats by applying high-volume graph-based technology, similar to the ones developed by Facebook and Google • How CrowdStrike solved this challenge by building its own proprietary graph data model • How CrowdStrike Threat Graph™ collects and analyzes massive volumes of security-related data to stop breaches
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CrowdStrike
Published By: Kronos     Published Date: Sep 20, 2018
If you’ve tried managing your retail operation’s labor performance without reliable, real-time data, you know the costly shortcomings of this approach. Tap into clear, easy-to-access workforce data — a single view of all elements of your workforce that empowers you to make effective decisions and protect your bottom line. Workforce Analytics for Retail transforms labor and sales data into meaningful business intelligence. Learn how managers can make data-driven decisions that optimize workforce utilization, control labor costs, and drive continuous improvement.
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Kronos
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: 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
Published 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.
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cloud, database, hybrid cloud, database platform
    
Group M_IBM Q1'18
Published By: IBM     Published Date: Jul 05, 2018
Scalable data platforms such as Apache Hadoop offer unparalleled cost benefits and analytical opportunities. IBM helps fully leverage the scale and promise of Hadoop, enabling better results for critical projects and key analytics initiatives. The end-to- end information capabilities of IBM® Information Server let you better understand data and cleanse, monitor, transform and deliver it. IBM also helps bridge the gap between business and IT with improved collaboration. By using Information Server “flexible integration” capabilities, the information that drives business and strategic initiatives—from big data and point-of- impact analytics to master data management and data warehousing—is trusted, consistent and governed in real time. Since its inception, Information Server has been a massively parallel processing (MPP) platform able to support everything from small to very large data volumes to meet your requirements, regardless of complexity. Information Server can uniquely support th
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IBM
Published By: IBM     Published Date: Jul 09, 2018
Data is the lifeblood of business. And in the era of digital business, the organizations that utilize data most effectively are also the most successful. Whether structured, unstructured or semi-structured, rapidly increasing data quantities must be brought into organizations, stored and put to work to enable business strategies. Data integration tools play a critical role in extracting data from a variety of sources and making it available for enterprise applications, business intelligence (BI), machine learning (ML) and other purposes. Many organization seek to enhance the value of data for line-of-business managers by enabling self-service access. This is increasingly important as large volumes of unstructured data from Internet-of-Things (IOT) devices are presenting organizations with opportunities for game-changing insights from big data analytics. A new survey of 369 IT professionals, from managers to directors and VPs of IT, by BizTechInsights on behalf of IBM reveals the challe
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IBM
Published 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
Published By: Hitachi Vantara     Published Date: Aug 02, 2018
In this inforgraphic, we are going to show you the possibilities with modernised, optimized data infrastructure. In doing so, we aim to bring you ideas about how you can bring your own data-driven business vision to life, focusing on the outcomes that matter most to you. In essence, we will be discussing five main industries and the possibilities for modernized data infrastructure. We will be displaying how Banking and Financial Services, Telecommunications, manufacturing, healthcare and retail can use data, analytics and automation to optimize their business, therefore bringing about a competitive edge which previous appeared unimaginable. Using data correctly, most importantly building proper data infrastructures, can be the driving force behind obtaining a competitive edge. Data is your story. And it’s our story, too.
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digital transformation, data infrastructure, data optimisation
    
Hitachi Vantara
Published By: Hitachi Vantara     Published Date: Aug 13, 2018
In this inforgraphic, we are going to show you the possibilities with modernised, optimized data infrastructure. In doing so, we aim to bring you ideas about how you can bring your own data-driven business vision to life, focusing on the outcomes that matter most to you. In essence, we will be discussing five main industries and the possibilities for modernized data infrastructure. We will be displaying how Banking and Financial Services, Telecommunications, manufacturing, healthcare and retail can use data, analytics and automation to optimize their business, therefore bringing about a competitive edge which previous appeared unimaginable. Using data correctly, most importantly building proper data infrastructures, can be the driving force behind obtaining a competitive edge. Data is your story. And it’s our story, too.
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Hitachi Vantara
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
Published By: TIBCO Software     Published Date: Feb 14, 2019
With the new TIBCO Spotfire® A(X) Experience, we are revolutionizing analytics and business intelligence. This new platform accelerates the personal and enterprise analytics experience so you can get from data to insights in the fastest possible way. With the fusion of technology enablers like machine learning, artificial intelligence, and natural language search, the Spotfire® X platform redefines what’s possible for analytics and business intelligence, simplifying for everyone how data and insights are generated, consumed, and acted on. Download this whitepaper to learn more, then check out the new Spotfire analytics. It’s unlike anything you have ever seen. Simple, yet powerful, it changes everything.
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TIBCO Software
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