data and analytics

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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 APAC     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 APAC
Published By: TIBCO Software APAC     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 APAC
Published By: TIBCO Software APAC     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 APAC
Published By: TIBCO Software APAC     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 APAC
Published By: Lenovo - APAC     Published Date: Jan 28, 2019
Asian ICT infrastructure investment is exploding as businesses review and modernise their data-centre architectures to keep up with the service demands of a growing and increasingly sophisticated population. Demand for cloud services, particularly to support big-data analytics initiatives, is driving this trend. Frost & Sullivan, for example, believes the Asia-Pacific cloud computing market will grow at 28.4 percent annually through 2022. Despite this growth, many businesses are also rapidly realising that public cloud is not the best solution for every need as they do not always offer the same level of visibility, performance, and control as on-premises infrastructure.This reality is pushing many companies towards the middle ground of hybrid IT, in which applications and infrastructure are distributed across public cloud and self-managed data centre infrastructure. Read about Medical company Mutoh and how it took advantage of the latest technology.
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lenovodcg, nutanix, hyperconvergedinfrastructure, hci
    
Lenovo - APAC
Published By: Attunity     Published Date: Nov 15, 2018
With the opportunity to leverage new analytic systems for Big Data and Cloud, companies are looking for ways to deliver live SAP data to platforms such as Hadoop, Kafka, and the Cloud in real-time. However, making live production SAP data seamlessly available wherever needed across diverse platforms and hybrid environments often proves a challenge. Download this paper to learn how Attunity Replicate’s simple, real-time data replication and ingest solution can empower your team to meet fast-changing business requirements in an agile fashion. Our universal SAP data availability solution for analytics supports decisions to improve operations, optimize customer service, and enable companies to compete more effectively.
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Attunity
Published By: Attunity     Published Date: Nov 15, 2018
IT departments today face serious data integration hurdles when adopting and managing a Hadoop-based data lake. Many lack the ETL and Hadoop coding skills required to replicate data across these large environments. In this whitepaper, learn how you can provide automated Data Lake pipelines that accelerate and streamline your data lake ingestion efforts, enabling IT to deliver more data, ready for agile analytics, to the business.
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Attunity
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