data analysis

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Published By: SAP     Published Date: Jul 20, 2015
However, here at SAP we have identified four broad technology trends that are currently having a major impact on how retailers conduct business and engage with consumers. They are Big Data, social media, seamless retailing and disruptive technologies. Read this report for an analysis and overview of each trend area, why they are important and what the future likely holds.
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it trends, retail, big data, social media, seamless retailing, disruptive technology, trends
    
SAP
Published By: Waterline Data & Research Partners     Published Date: May 18, 2015
Waterline Data automates the cataloging of data assets and provides an Amazon.com-like guided shopping approach to data discovery that is intended to take the guesswork out of targeting the right data.
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waterline, big data, automation, cataloging, processing, analysis, assets, data science, data management
    
Waterline Data & Research Partners
Published By: Waterline Data & Research Partners     Published Date: May 18, 2015
In this report, Forrester Research recommends that application development and delivery (AD&D) professionals working on BI and big data initiatives get the best out of both by designing and integrating them in a flexible data platform.
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waterline, big data, automation, cataloging, processing, analysis, assets, data science, data management
    
Waterline Data & Research Partners
Published By: GE Power     Published Date: Oct 05, 2016
Gathering machine sensor data for analysis across a power plant is only the beginning. The Digital Twin takes analytics to the next level by creating a virtual analytic model of assets within the plant. With the GE Digital Twin power companies can understand how assets are performing in real time, and predict future performance.
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digital power plant, digital power, digital power station, distributor solution, efficiency of power generation, industrial power
    
GE Power
Published By: Google Analytics 360 Suite     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 360 Suite
Published By: Splunk     Published Date: Nov 29, 2018
Gartner Market Share Analysis: ITOM, Performance Analysis Software, Worldwide, 2017 Splunk Jumps From #5 in 2016 to #2 in Top 10 Named ITOM Performance Analysis Software Vendors, Worldwide, 2017 Splunk is ranked #2 of overall ITOM Performance Analysis Software Vendors, according to Gartner’s report, Market Share Analysis: ITOM, Performance Analysis Software, Worldwide, 2017. This Gartner report also lists Splunk as one of several disruptors in the table “Market Share of Incumbents vs. Disruptors - ITOM Performance Analysis Software.” As a Splunk customer, are you utilizing your machine data platform to its fullest potential? Learn about newest trends in ITOM software tools across AIOps, APM, infrastructure monitoring and Network performance monitoring and diagnostics. Download this report to learn: 2017 rankings of performance analysis software vendors, overall and subsegments How digital business is driving demand for modern, agile monitoring tools via DevOps toolchains Shifts in
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application performance monitoring, network tools, network monitoring tools, network monitoring software, network monitoring, it monitoring
    
Splunk
Published By: Stratoscale     Published Date: Feb 01, 2019
This eBook offers a practical hands-on guide to analyzing and mitigating the risks of migrating to PostgreSQL. With the ongoing shift towards open-source database solutions, it’s no surprise that PostgreSQL is the fastest growing database. While it’s tempting to simply compare the licensing costs of proprietary systems against that of open source, it is both a misleading and incorrect approach when evaluating the potential for return on investment of a database technology migration. A key decision criteria for adopting any technology is whether it can support requirements for existing applications while also fitting into longer term strategies and needs. The first section of this eBook provides a detailed analysis of all aspects of migrating from legacy and commercial solutions to PostgreSQL: ? Schema and code migration ? Data migration ? Application code migration ? Testing and evaluation
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Stratoscale
Published By: Stratoscale     Published Date: Feb 01, 2019
This eBook offers a practical hands-on guide to “Day One” challenges of deploying, managing and monitoring PostgreSQL. With the ongoing shift towards open-source database solutions, it’s no surprise that PostgreSQL is the fastest growing database. While it’s tempting to simply compare the licensing costs of proprietary systems against that of open source, it is both a misleading and incorrect approach when evaluating the potential for return on investment of a database technology migration. An effective monitoring and logging strategy is critical for maintaining the reliability, availability, and performance of database environments. The second section of this eBook provides a detailed analysis of all aspects of monitoring and logging PostgreSQL: ? Monitoring KPIs ? Metrics and stats ? Monitoring tools ? Passive monitoring versus active notifications
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Stratoscale
Published By: Stratoscale     Published Date: Feb 01, 2019
This eBook offers a practical hands-on guide to “Day Two” challenges of accelerating large-scale PostgreSQL deployments. With the ongoing shift towards open-source database solutions, it’s no surprise that PostgreSQL is the fastest growing database. While it’s tempting to simply compare the licensing costs of proprietary systems against that of open source, it is both a misleading and incorrect approach when evaluating the potential for return on investment of a database technology migration. After a PostgreSQL deployment is live, there are a variety of day-two scenarios that require planning and strategizing. The third section of this eBook provides a detailed analysis of all aspects accelerating large-scale PostgreSQL deployments: ? Backups and Availability: strategies, point-in-time recovery, availability and scalability ? Upgrades and DevOps: PostgreSQL upgrade process, application upgrades and CI/CD
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Stratoscale
Published By: Stratoscale     Published Date: Feb 01, 2019
This eBook offers a practical hands-on guide to deploying, managing and scaling PostgreSQL in various environments, in the public cloud and on-premises. With the ongoing shift towards open-source database solutions, it’s no surprise that PostgreSQL is the fastest growing database. While it’s tempting to simply compare the licensing costs of proprietary systems against that of open source, it is both a misleading and incorrect approach when evaluating the potential for return on investment of a database technology migration. The eBook provides a detailed analysis of planning, day-one, and day-two challenges of PostgreSQL deployments, in the context of potential operating environments: ? Public cloud ? Private cloud ? Private DC (bare metal / VM)
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Stratoscale
Published By: Here Technologies     Published Date: Apr 02, 2019
OEMs today face significant challenges that restrict effective fleet analysis. Data is often siloed and held in several incompatible formats, meaning responding to software faults can be a costly and lengthy process. To overcome this, Here have combined OTA technology with the HERE Open Location Platform. By closing this loop, Here provide a one-stop solution for data enrichment and analysis – and Here turn connected vehicle data into over-the-air updates. Watch this webinar and learn how HERE enables: • Early error detection and proactive remote maintenance of software and firmware • Reduction of data management value chain complexity with its one-stop solution • Effective fault response and real-time access to new products and services
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over the air technologies, location data, auto, mapping
    
Here Technologies
Published By: Infor     Published Date: Mar 03, 2017
It is the best of times and the worst of times for elite finance professionals in mid- to largesized organizations. With demands for more information, faster, going nowhere but up, and finance departments playing an increasingly strategic role in determining business direction, CFOs, Controllers and their staffs are finding themselves intellectually stimulated and exhausted in equal measure.
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finance, cfo, finance process, data analysis, risk management
    
Infor
Published By: IBM     Published Date: Apr 14, 2017
Any organization wishing to process big data from newly identified data sources, needs to first determine the characteristics of the data and then define the requirements that need to be met to be able to ingest, profile, clean,transform and integrate this data to ready it for analysis. Having done that, it may well be the case that existing tools may not cater for the data variety, data volume and data velocity that these new data sources bring. If this occurs then clearly new technology will need to be considered to meet the needs of the business going forward.
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data integration, big data, data sources, business needs, technological advancements, scaling data
    
IBM
Published By: Oracle     Published Date: Nov 07, 2018
At many organisations, planning and budgeting take too long and devour resources. Finance teams spend too much time on administrative tasks relating to these processes—collecting, consolidating and reconciling data, for example—and are left with little time for analysis, strategy development and target setting. Accuracycan be patchy, results unreliable.
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Oracle
Published By: NAVEX Global     Published Date: May 06, 2016
This report outlines Data & Analysis to Help You Benchmark Your Programme Against the World’s Largest Ethics & Compliance Hotline Database—and Enhance Your Ethics & Compliance Programme Effectiveness.
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data analysis, benchmarking
    
NAVEX Global
Published By: Teradata     Published Date: Jun 14, 2013
Download this paper for an in-depth look at how advances in mHealth technology and the use of biometric data analytics are important to improving the overall healthcare system.
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biometric data analysis, mobile healthcare, healthcare, mhealth, biometric data
    
Teradata
Published By: Delphix     Published Date: May 28, 2015
In a world of privacy regulation, intellectual property theft, and cybercrime, only a masking solution can secure vital data and enable outsourcing, third party analysis, and cloud deployments. Delphix delivers rapid deployment of masked data in minutes, service-based masking of production systems, and the ability to ship masked data across sites, to third parties, and into the cloud, with minimal network footprint.
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Delphix
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: Datawatch     Published Date: Dec 16, 2015
In this paper, the Top 10 Ways to Supercharge Analyst Productivity with Data Preparation, learn how a self-service data preparation solution saves analysts’ time by allowing them to manipulate, filter, enrich, blend and combine disparate data sets in a matter of minutes.
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data preparation, data wrangling, analyst productivity, data analysis, cleaning data, data blending
    
Datawatch
Published By: Datawatch     Published Date: Feb 03, 2016
Some companies estimate that up to 80 percent of their analysts’ time is spent on data preparation. Thorough, automated data preparation, however, can quickly transform raw information into reliable, consistent data sets ready for analysis. This report from Gartner details why information management and business analytics leaders must introduce data preparation into their big data initiatives in order to improve both the understanding of the data, and the productivity of analysts. Read the report now to learn more.
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datawatch, data preparation, data analytics, data analysis, analyst productivity, information management, business analytics, big data
    
Datawatch
Published By: IBM     Published Date: Jul 27, 2016
IBM i2 Enterprise Insight Analysis helps analysts and investigators turn large data sets into comprehensive intelligence, in near real-time. With the help of advanced analytics and visual analysis capabilities, analysts can uncover hidden connections, patterns and trends buried in disparate data. Equip analysts and those on the front line with the tools they need to generate actionable intelligence, with mission critical speed.
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ibm, cyber threat analysis, ibm i2 enterprise insight analysis, cyber security, business intelligence, security, business technology
    
IBM
Published By: IBM     Published Date: Oct 27, 2016
IBM Analytics for Apache Spark for Bluemix is an open-source cluster computing framework with in-memory processing to speed analytic applications up to 100 times faster compared to other technologies on the market today. Optimized for extremely fast and large scale data processing-you can easily perform big data analysis from one application.
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ibm, apache spark, bluemix, analytics, enterprise applications, business technology
    
IBM
Published By: Veritas     Published Date: May 12, 2016
The Data Genomics Index is a first-of-its-kind benchmark analysis of data stored within a typical enterprise environment. This report reveals insights into data growth, data age, and data type thereby providing organizations with the comparison standard for beginning to take action on their data. In addition to the Index, Veritas has founded the Data Genomics Project. This community of likeminded data scientists, industry experts and thought leaders will come together to surface the true nature of enterprise environments, build the data-genome that matters for information management, and share the discussion with a world struggling to solve tremendous data growth challenges.
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Veritas
Published By: IBM     Published Date: Jan 18, 2017
In the domain of data science, solving problems and answering questions through data analysis is standard practice. Data scientists experiment continuously by constructing models to predict outcomes or discover underlying patterns, with the goal of gaining new insights. But data scientists can only go so far without support.
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ibm, analytics, aps data, open data science, data science, data engineers, enterprise applications
    
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, data management
    
IBM
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