big data analytics

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Published By: Teradata     Published Date: Jun 12, 2013
This paper takes a look at the hard truths and common misconceptions surrounding big data. In particular, it focuses on five common myths about large-scale analytics, athen offers a glimpse at the next steps necessary to make big data work for you.
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big data, big data analytics, data driven marketing, finance
    
Teradata
Published By: Teradata     Published Date: Jun 12, 2013
Download this paper to learn how Unified Data Architecture™ can bridge the gap between the business language of SQL, the extreme processing power of MapReduce, and the big data residing in Hadoop to provide a unified, high-performance big data analytics system for the enterprise.
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data, big data, unified data architecture, finance
    
Teradata
Published By: Teradata     Published Date: Jun 12, 2013
This whitepaper details how BCBSNC leverages its Teradata environment to achieve key strategic goals.
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big data, analytics, healthcare
    
Teradata
Published By: Teradata     Published Date: Jun 12, 2013
Health plans and insurers know that to thrive over the next 3-5 years, they must dramatically improve their ability to engage with individual consumers. The combination of Teradata products; an integrated data warehouse, Aster big data analytics and Aprimo integrated communication management, creates actionable analytic capabilities unparalleled in its ability to help companies achieve these goals. this white paper details how health plans and insurers can use Teradata to succeed in today’s healthcare environment.
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healthcare, data, insights, health plans, integrated data
    
Teradata
Published By: Oracle     Published Date: Sep 21, 2016
This white paper shows how to use your big data analytics and smooth procurement systems as a launchpad to holding your own in the Digital Age.
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Oracle
Published By: RSA Security     Published Date: Oct 24, 2013
Big data security analytics is no longer a visionary idea -- leading enterprises recognize that their immediate security requirements demand this type of solution.
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rsa, emc, enterprise strategy, big data, security, security analytics
    
RSA Security
Published By: RSA Security     Published Date: Oct 24, 2013
Starting with a foundational set of data management and analytic capabilities enables organizations to effectively build and scale security management as the enterprise evolves to meet Big Data challenges.
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rsa, emc, big data, security, security analytics, scale, security management
    
RSA Security
Published By: Oracle EPM     Published Date: May 11, 2015
Which EPM priorities are at the top of the Finance agenda? What are the most compelling developments in big data, analytics, mobile technology, and cloud computing that motivate Finance leaders to undertake new technology initiatives?
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epm, finance, technology, cloud computing, big data
    
Oracle EPM
Published By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Today, businesses pour Big Data into data lakes to help them answer the big questions: Which product to take to market? How to reduce fraud? How to retain more customers? People need to get these answers faster than ever before to reduce “time to answer” from months to minutes. The data is coming in fast and the answers must come just as fast. The answer is self-service data preparation and analytics tools, but with that comes an expectation that the right data is going to be there. Only by using a data catalog can you find the right data quickly to get the expected insight and business value. Download this white paper to learn more!
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Waterline Data & Research Partners
Published By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Business users want the power of analytics—but analytics can only be as good as the data. The biggest challenge nontechnical users are encountering is the same one that has been a steep challenge for data scientists: slow, difficult, and tedious data preparation. The increasing volume, variety, and velocity of data is putting pressure on organizations to rethink traditional methods of preparing data for reporting, analysis, and sharing. Download this white paper to find out how you can improve your data preparation for business analytics.
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Waterline Data & Research Partners
Published By: Teradata     Published Date: Jul 15, 2015
This paper examines the value of big data applications as a means to ensure pervasive availability of big data analytics in the organization.
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analytics, big data, applications, lob
    
Teradata
Published By: IBM     Published Date: Jul 05, 2016
The use of analytics will define the successful midmarket business of the next decade, just as it will define the successful larger organization in this information age. The past decade has seen rapid change in the business climates with an explosion of global competition and economic uncertainty. Despite this, many midmarket companies have thrived by using their size and agility as a competitive advantage. Certainly they have fewer resources than large corporations who are able to invest large sums in IT. However, small yachts can turn and adjust their course much quicker than large cruise ships. The same came be said for midmarket companies. The most successful organizations are ones that can react the quickest to changes in the market place. Midmarket companies can take advantage of their smaller size by being more agile and quicker to change, or even reinvent themselve
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ibm, ibm pure data system, big data, data analytics, analytics architecture, competitive advantage, midmarket organization
    
IBM
Published By: IBM     Published Date: Jan 19, 2017
The outcome of any big data analytics project, however, is only as good as the quality of the data being used. As big data analytics solutions have matured and as organizations have developed greater expertise with big data technologies he quality and trustworthiness of the data sources themselves are emerging as key concerns. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, analytics, ecm, data, big data, information governance
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
Analytics relies on BI, Big Data, and data discovery to provide reporting, trend what-if analysis. Analytics is transforming data into insight.
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ibm, analytics, business intelligence, data
    
IBM
Published By: IBM     Published Date: May 23, 2017
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
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cloud strategy, database projects, disaster recover, geographic reach, large database, ibm, analytics, management optimization
    
IBM
Published By: IBM     Published Date: Nov 08, 2017
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
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ibm, cloud, cloud computing, database, ibm db2
    
IBM
Published By: Privacera     Published Date: Oct 23, 2017
Trends indicate that every company should embrace big data and analytics – there’s clearly incredible opportunity for enterprises to derive value from data. But not all companies are clamoring to jump on board with building teams and defining initiatives. The reality is enterprises are analyzing only 0.5% of their data, according to recent study by MIT Technology Review. What’s holding these companies back? This paper will cover the categories of risk and some of the constraints at play, as well as five recommendations to managing and mitigating that risk.
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Privacera
Published By: Group M_IBM Q1'18     Published Date: Jan 23, 2018
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
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db2. blu accelaration, big data, data analytics, disaster recovery
    
Group M_IBM Q1'18
Published By: IBM     Published Date: Apr 19, 2018
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
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db2, data migration, ibm, oracle
    
IBM
Published By: IBM     Published Date: Jul 02, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does. From an IT perspective, there is a fairly straightforward sequence of applications that businesses can adopt over time that will help put direction into this journey. IDC outlines this sequence to e
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IBM
Published By: IBM     Published Date: Jul 05, 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: IBM     Published Date: Aug 08, 2018
An IBM Cloud configuration completed a big data analytics workload in less time and with greater throughput than an AWS solution
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IBM
Published By: Group M_IBM Q418     Published Date: Dec 18, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does.
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Group M_IBM Q418
Published By: Group M_IBM Q119     Published Date: Dec 18, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does.
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Group M_IBM Q119
Published By: Group M_IBM Q2'19     Published Date: May 28, 2019
However, big data and analytics solutions can have shortcomings. Proprietary and best-of-breed approaches can require valuable time and resources to build, integrate and maintain — while outsourcing data analytics can constrain reporting frequency and timeliness. In a world where operational efficiency and fast, reliable information is paramount, these limitations can put payers at a competitive disadvantage.
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Group M_IBM Q2'19
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