data exploration

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Published By: SAS     Published Date: Oct 18, 2017
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Want to get even more value from your Hadoop implementation? Hadoop is an open-source software framework for running applications on large clusters of commodity hardware. As a result, it delivers fast processing and the ability to handle virtually limitless concurrent tasks and jobs, making it a remarkably low-cost complement to a traditional enterprise data infrastructure. This white paper presents the SAS portfolio of solutions that enable you to bring the full power of business analytics to Hadoop. These solutions span the entire analytic life cycle – from data management to data exploration, model development and deployment.
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SAS
Published By: Cisco     Published Date: Jun 22, 2016
With 50 to 100 billion things expected to be connected to the Internet by 2020, we are now experiencing a major paradigm shift that is revolutionizing business. More and more of the objects we use every day—including those in our factories, utilities, and railroads—are used to capture and distribute information that is helping us know more and do more. The TechWiseTV team and guest experts take an in-depth look at how industries like these are utilizing the data they are gathering from the factory floor all the way out to the field. This exploration into how the Internet of Things actually works in the real world and what your organization must do to take full advantage of it is a great opportunity to understand the practical challenges and specific technology involved in bringing all this potential to life.
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Cisco
Published By: SAS     Published Date: Nov 04, 2015
If you are working with massive amounts of data, one challenge is how to display results of data exploration and analysis in a way that is not overwhelming. You may need a new way to look at the data – one that collapses and condenses the results in an intuitive fashion but still displays graphs and charts that decision makers are accustomed to seeing. And, in today’s on-the-go society, you may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time. SAS® Visual Analytics is a data visualization and business intelligence solution that uses intelligent autocharting to help business analysts and nontechnical users visualize data. It creates the best possible visual based on the data that is selected. The visualizations make it easy to see patterns and trends and identify opportunities for further analysis.
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data visualization, sas, big data, visual analytics, data exploration, analysis, networking, knowledge management
    
SAS
Published By: Teradata     Published Date: Oct 15, 2012
Does your organization struggle to get new business insights from all data types with rapid exploration?
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data scientists, analyst, statistician, quants, quantitative analyst, scientist, data science, business technology
    
Teradata
Published By: IBM     Published Date: Apr 14, 2017
Today, all consumers can obtain any piece of data at any point in time. This experience represents a significant cultural shift: the beginning of the democratization of data. However, the data landscape is increasing in complexity, with diverse data types from myriad sources residing in a mix of environments: on-premises, in the cloud or both. How can you avoid data chaos?
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations
    
IBM
Published By: Google Analytics     Published Date: Jul 28, 2017
Today’s marketing leaders need sophisticated tools to turn data into cross-channel insights that improve performance. In a new report, Gartner compares 11 digital marketing analytics solutions across five key areas: data integration, exploration, advanced models, platform integrations, and measurement. Selecting the best solution for your team requires thoughtful analysis. How will you determine the best fit? Gartner’s Magic Quadrant can help.
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Google Analytics
Published By: Drillinginfo     Published Date: Nov 18, 2015
The Bakken is a very large hydrocarbon-bearing subsurface rock formation underneath a large portion of the Williston Basin in North Dakota, Montana, Saskatchewan and Winnepeg. The Bakken has been the scene of many advancements in drilling technology – horizontal drilling, pad drilling and downspacing, to name a few. This first Edition of the DI Expert eBook by Drillinginfo, the premier provider of data and insights for oil and gas exploration decisions, is a collection of articles posted by our staff of engineers, analysts and geologists about the Bakken over the past year.
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geologists, downspacing, innovations, oil, gas exploration, drilling
    
Drillinginfo
Published By: Drillinginfo     Published Date: Nov 18, 2015
This second edition of the DI Expert eBook provides a collection of articles written by staff analysts from Drillinginfo, the premier provider of data and insights for oil and gas exploration decisions. These articles focus on the Eagle Ford Shale play in south central Texas. The Eagle Ford Shale boom began in 2008 and has transformed the lives of mineral rights owners, communities and E&P operators throughout Texas and the United States. The Eagle Ford Shale is a cretaceous formation with a favorable brittleness index, which makes the formation ideal for hydraulic fracturing and economical unconventional production.
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exploration, best practices, hydraulic fracturing, geologists, downspacing, innovations, oil, gas exploration
    
Drillinginfo
Published By: Drillinginfo     Published Date: Nov 18, 2015
The Permian basin, a long time oil and gas producing region nestled in west Texas and southeastern New Mexico was once believe to have reached “Peak Oil” extraction levels. A significantly larger play than the booming Eagle Ford Shale, the Permian Basin has reemerged as a production pillar for the US, thanks to advancements in horizontal drilling and hydraulic fracturing. Although still in early stages of new production, the Permian has already transformed the local economies surrounding the play, adding to the energy security of the U.S. In this issue of the DI Expert eBook, by Drillinginfo, the premier provider of data and insights for oil and gas exploration decisions, our expert analysts have delved into the complexities of the geology in the Permian, highlighted the successes of operators in the region and provided in-depth analyses on the play’s re-emergence.
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basin, permian, peak oil, extraction, energy security, geologists, downspacing, innovations
    
Drillinginfo
Published By: IBM     Published Date: Aug 08, 2016
Imagine expanding your business and monetizing your bank's data. Imagine bringing services together and delighting customers. API's can connect your bank to a whole ecosystem of business. With innovative thinking and exploration your bank can capitalize on API's in the new digital economy.
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ibm, api, api economy, integration, application program interface, cloud, middleware, banking
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
In today’s highly distributed, multi-platform world, the data needed to solve any particular decision making need is increasingly likely to be found across a wide variety of sources. As a result, traditional manual approaches requiring prior collection, storage and integration of extensive sets of data in the analyst’s preferred exploration environment are becoming less useful. Data virtualization, which offers transparent access to distributed, diverse data sources, offers a valuable alternative approach in these circumstances.
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IBM
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. To perform data discovery and exploration, use analytics to define desired business outcomes, and derive insights to help attain those outcomes, users need good, relevant data. Executives, managers, and other professionals are reaching for self-service technologies so they can be less reliant on IT and move into advanced analytics formerly limited to data scientists and statisticians. However, 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.
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Waterline Data & Research Partners
Published By: Looker     Published Date: Dec 03, 2015
The focus of modern business intelligence has been self-service; pushing data into the hands of end users more quickly with more accessible user interfaces so they can get answers fast and on their own. This has helped alleviate a major BI pain point: centralized, IT-dominated solutions have been too slow and too brittle to serve the business. What has been masked is a lack of innovation in data modeling. Data modeling is a huge, valuable component of BI that has been largely neglected. In this webinar, we discuss Looker’s novel approach to data modeling and how it powers a data exploration environment with unprecedented depth and agility. Topics covered include: • A new architecture beyond direct connect • Language-based, git-integrated data modeling • Abstractions that make SQL more powerful and more efficient
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Looker
Published By: CyrusOne     Published Date: Jul 05, 2016
Many companies, especially those in the Oil and Gas Industry, need high-density deployments of high performance compute (HPC) environments to manage and analyze the extreme levels of computing involved with seismic processing. CyrusOne’s Houston West campus has the largest known concentration of HPC and high-density data center space in the colocation market today. The data center buildings at this campus are collectively known as the largest data center campus for seismic exploration computing in the oil and gas industry. By continuing to apply its Massively Modular design and build approach and high-density compute expertise, CyrusOne serves the growing number of oil and gas customers, as well as other customers, who are demanding best-in-class, mission-critical, HPC infrastructure. The company’s proven flexibility and scale of its HPC offering enables customers to deploy the ultra-high density compute infrastructure they need to be competitive in their respective business sectors.
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environment, cyrusone, best practices, productivity, flexibility
    
CyrusOne
Published By: Google Analytics     Published Date: Jul 27, 2017
Today’s marketing leaders need sophisticated tools to turn data into cross-channel insights that improve performance. In a new report, Gartner compares 11 digital marketing analytics solutions across five key areas: data integration, exploration, advanced models, platform integrations, and measurement. Selecting the best solution for your team requires thoughtful analysis. How will you determine the best fit? Gartner’s Magic Quadrant can help.
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Google Analytics
Published By: Pentaho     Published Date: Mar 08, 2016
If you’re evaluating big data integration platforms, you know that with the increasing number of tools and technologies out there, it can be difficult to separate meaningful information from the hype, and identify the right technology to solve your unique big data problem. This analyst research provides a concise overview of big data integration technologies, and reviews key things to consider when creating an integrated big data environment that blends new technologies with existing BI systems to meet your business goals. Read the Buyer’s Guide to Big Data Integration by CITO Research to learn: • What tools are most useful for working with Big Data, Hadoop, and existing transactional databases • How to create an effective “data supply chain” • How to succeed with complex data on-boarding using automation for more reliable data ingestion • The best ways to connect, transport, and transform data for data exploration, analytics and compliance
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data, buyer guide, integration, technology, platform, research, enterprise applications
    
Pentaho
Published By: Cisco     Published Date: Nov 17, 2015
With 50 to 100 billion things expected to be connected to the Internet by 2020, we are now experiencing a major paradigm shift that is revolutionizing business. More and more of the objects we use every day—including those in our factories, utilities, and railroads—are used to capture and distribute information that is helping us know more and do more. The TechWiseTV team and guest experts take an in-depth look at how industries like these are utilizing the data they are gathering from the factory floor all the way out to the field. This exploration into how the Internet of Things actually works in the real world and what your organization must do to take full advantage of it is a great opportunity to understand the practical challenges and specific technology involved in bringing all this potential to life.
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cisco, connected factory, internet of things, iot solutions, data management, convergence, business process management, data integration
    
Cisco
Published By: Adobe     Published Date: Apr 17, 2014
Discover new opportunities for maturing your data practices—and building your business results. You’ll learn how to move beyond mere web analytics to build a more comprehensive marketing analytics approach that includes mobile, social, and offline channels. And you’ll see how your current analytics capabilities compare to those of similar organizations and where you have opportunities for improvement.
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adobe, analytics, marketing, data collection, data automation, marketing automation, web analytics, marketing analytics
    
Adobe
Published By: Box     Published Date: Feb 13, 2015
IDC's 3rd IT Platform — defined by the nascent and confluent mobile, cloud, social business and big data technologies — will drive 98 % of future IT industry growth over the next seven years. In 2013, industry transition to the 3rd Platform will move from the exploration stage to full-blown high stakes competition, resetting the leadership ranks in the IT sector forever.
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idc, it platform, mobile, mobile content, 3rd platform technologies, it management
    
Box
Published By: SAS     Published Date: Mar 14, 2014
Stop to think about how - and how often - your business interacts with customers. Most organizations believe that only a small fraction of data on interactions generated are effectively put to use. Why is that? Check out this whitepaper to see.
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sas, voc, voice of customer, visual text analytics, best practices, customer voice, sound of sentiment, text data
    
SAS
Published By: IBM     Published Date: Apr 07, 2017
Data science platforms are engines for creating machine-learning solutions. Innovation in this market focuses on cloud, Apache Spark, automation, collaboration and artificial-intelligence capabilities. We evaluate 16 vendors to help you make the best choice for your organization. This Magic Quadrant evaluates vendors of data science platforms. These are products that organizations use to build machine-learning solutions themselves, as opposed to outsourcing their creation or buying ready-made solutions.
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations
    
IBM
Published By: IBM     Published Date: Jan 14, 2015
Big data has been big news in recent years. Organizations recognize that they must now begin to focus on using big data technologies to solve business problems. The pressure is on for organizations to move past the discussion phase toward well-planned projects.
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big data, data management, data exploration, gain visibility, security extension, business intelligence, explore data, data analytics
    
IBM
Published By: IBM     Published Date: Jan 14, 2015
Bloor Research investigated several key critical success factors for big data analytics. Their findings show that governance, data cleansing, and privacy and security have never been more important. Read this paper to see their conclusions.
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big data, data management, data exploration, gain visibility, security extension, business intelligence, explore data, data analytics
    
IBM
Published By: IBM     Published Date: Jan 14, 2015
Explore this interactive infographic to discover how IBM makes it possible to manage all of these priorities while significantly reducing storage and maintenance costs.
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big data, data management, data exploration, gain visibility, security extension, business intelligence, explore data, data analytics
    
IBM
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