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Published By: QlikTech UK     Published Date: Nov 24, 2015
Organizations are, or will soon be, producing petabytes – thousands of terabytes or millions of gigabytes – of valuable data. But the ability to transform these massive data sets into actionable insights requires business intelligence (BI) and analytics tools that can uncover the hidden relationships among varied sources of information, provide rich visualizations of trends and don’t require end-users to be trained data scientists.
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healthcare
    
QlikTech UK
Published By: Plotly     Published Date: Jan 30, 2020
Machine learning helps scientists find subtle patterns in data that empower them to quickly examine potential outcomes of complex processes. One such process is genome editing, during which, scientists make targeted modifications to an organism’s genome by inserting, deleting, or modifying its DNA. A recent study published in the international scientific journal, Nature, showcases the usage of machine learning in genome editing. The algorithm, inDelphi, was built by researchers from MIT and Harvard University by using Dash, a flexible Python and R framework for building analytic applications. Through Dash’s visual and reactive components, the researchers were able to create intuitive, elegant data visualizations, without JavaScript, CSS, or DevOps. Dash brought the algorithm predictions of gene editing to life. As a result, the scientists were able to predict the results of a specific mechanism of DNA repair called end-joining, making the genome editing process more predictable, cont
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Plotly
Published By: Plotly     Published Date: Jan 30, 2020
Energy consumption data is a wealth of information that can be utilized to plan for sustainable development. In the last twenty years, South Africa’s energy consumption has transformed dramatically, with electrified households growing from thirty to eighty-five percent. Weibke Toussaint, a researcher and data scientist from the University of Cape Town, wanted to create a user-friendly way to understand this complex energy consumption data. She used Dash, a Python and R framework for data analytics, to quickly and efficiently build visually beautiful, user-friendly, and interactive apps. By using Dash, Toussaint was able to better understand the South African energy consumption data and communicate her findings with the South African National Energy Development Institute, the state-owned utility provider, and the Energy Resource Center. Together, they combined their insight with the power of Dash to uncover opportunity in energy. Get the whitepaper to learn how you can uncover hidden
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Plotly
Published By: Cisco     Published Date: Mar 22, 2019
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
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Cisco
Published By: HERE Technologies     Published Date: Mar 11, 2019
Increasingly sophisticated location technology makes it possible for data scientists to gain a deeper understanding of their target audiences – and how to reach them. Accurate and precise intelligence can give more timely and complete insights into audiences than ever before. As one of the world’s leading location platforms in 2018, HERE shares insights and solutions to buying location data for better audience segmentation.
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location data, ad tech, location targeting
    
HERE Technologies
Published By: SmartLink Health     Published Date: Oct 25, 2018
Payer contracts, relationships, and a strong service portfolio give your lab a license to hunt and an opportunity to compete. But lack of EHR integration continues to be a barrier for independent labs and a differentiator for the largest lab companies. In this webinar, you’ll discover a new, affordable, and innovative lab-to-EHR integration approach that eliminates the need for HL-7 interfaces and can help you: • Reduce incomplete lab orders and associated labor costs • Improve customer satisfaction and “stickiness” in your accounts • Grow both new and existing customer revenue
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SmartLink Health
Published By: IBM APAC     Published Date: Mar 06, 2019
The Forrester Study on cost savings and business benefits enabled by Watson Studio and Watson Knowledge Catalog. Watson Studio provides a suite of tools for data scientists, application developers, and subject matter experts to collaboratively and easily work with data and use that data to build, train and deploy machine learning models at scale. The Forrester provides readers a framework to evaluate the potential financial impact of the Watson Studio and Watson Knowledge Catalog investment on their organizations.
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IBM APAC
Published By: Intel     Published Date: Jun 07, 2017
Intel's Bob Rogers, chief data scientist for big data solutions, sat down with Dan Magestro, research director at the international Institute of Analytics (IIA), to discuss the power of asking questions when assessing an organisation's analytics maturity. Read on to find out more.
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intel, analytics, data, data analytics, data science
    
Intel
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: Virgin Pulse     Published Date: Jun 02, 2017
This report includes analysis from behavior and data scientists to help you understand why your employees may not be working at optimal levels and discover ways to address this growing problem.
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presenteeism, employee presenteeism, workforce presenteeism, job presenteeism, presenteeism in the workplace, worker productivity, workforce productivity
    
Virgin Pulse
Published By: TIBCO Software     Published Date: Aug 15, 2018
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms. Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
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TIBCO Software
Published By: HP Inc.     Published Date: Jun 12, 2018
HP scientists had a bright idea. If they could modify materials to absorb infrared light – the light we can’t see – they could successfully fuse color to that material. It’s a story of how HP “cracked the code” in 3D color printing by drawing upon deep experience in the science of ink. Read this innovation story to why HP Jet Fusion 300/500 3D printers make it possible to produce engineering-grade functional parts faster and more affordably. Download HP’s innovation story
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HP Inc.
Published By: Group M_IBM Q1'20     Published Date: Feb 10, 2020
A data and AI platform shouldn't limit you - it should provide flexible capabilities to build on your current infrastructure and optimize your ability to operationalize AI. IBM Cloud Pak for Data is a platform that enables you to do just that with open by design technology built on Red Hat OpenShift. <> Join the webinar to learn more about the open source capabilities built into Cloud Pak for Data, and how developers, data scientists, and more can start to transform their businesses by unlocking the hidden insights within their organization's data
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Group M_IBM Q1'20
Published By: SAS     Published Date: Apr 20, 2015
To create real business value with data scientists, top management must learn how to manage them effectively.
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SAS
Published By: EMC Corporation     Published Date: Jul 07, 2013
3TIER helps organizations understand and manage the risks associated with renewable energy projects. A pioneer in wind and solar generation risks analysis, 3TIER uses science and technology to frame the risk of weather-driven variability, anywhere on Earth. 3TIER's unique expertise is in combining the latest weather data with historical weather patterns, and using the expertise of 3TIER's meteorologists, engineers and data scientists to create a detailed independent assessment of the future renewable energy potential of any location.
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renewable energy, customer profile, emc, risk management, best practices, storage, technology, security, it management, data management, business technology
    
EMC Corporation
Published By: HP Inc.     Published Date: Apr 11, 2018
HP scientists had a bright idea. If they could modify materials to absorb infrared light – the light we can’t see – they could successfully fuse color to that material. It’s a story of how HP “cracked the code” in 3D color printing by drawing upon deep experience in the science of ink. Read this innovation story to why HP Jet Fusion 300/500 3D printers make it possible to produce engineering-grade functional parts faster and more affordably. Download HP’s innovation story
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HP Inc.
Published By: Veritas     Published Date: Oct 03, 2016
This benchmark report, the Data Genomics Index, encompasses a community of like-minded data scientists, industry experts, and thought leaders together with the purpose of better understanding the true nature of the unstructured data that we are creating, storing, and managing on a daily basis - a report on real storage environments’ composition.
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Veritas
Published By: IBM     Published Date: Jul 14, 2016
This video describes how data scientists, analysts and business users can save precious time by using a combination of SPSS and Spark to uncover and act on insights in big data.
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ibm, data, analytics, predictive business, ibm spss, apache spark, coding, data science, software development, enterprise applications, data management, business technology, data center
    
IBM
Published By: Group M_IBM Q1'20     Published Date: Jan 14, 2020
Ten years ago, the journey began to find a flexible, versatile approach to build a central data store where all enterprise data could reside. The solution was the data lake — a general-purpose data storage environment that would store practically any type of data. It would also allow business analysts and data scientists to apply the most appropriate analytics engines and tools to each data set, in its original location. As these data lakes began to grow, a set of problems became apparent. While the technology was physically capable of scaling to capture, store and analyze vast and varied collections of structured and unstructured data, too little attention was paid to the practicalities of how to embed these capabilities into business workflows. Today, many organizations have recognized their failures, have changed leadership teams for the data lake implementation and are launching a second, third or even fourth attempt to implement a data lake successfully – this time leading with da
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data ops, data lake, data storage, data governance, data integration
    
Group M_IBM Q1'20
Published By: Oracle     Published Date: Mar 01, 2019
To keep up with rapid growth and stay ahead, disruptor fintechs must stay agile and go on innovating. Bangkok-based Forth Smart provides payment gateways that turn cash into digital currency via its thousands of vending machines. They needed to approach ITin new ways in order to free up budgets, resources and imaginations to focus on innovation. Oracle Cloud Specialist Marek Winiarski, talked to Forth Smart’s Data Scientist, Pawarit ‘Taa’ Ruengsuksilp about how the company has made cost savings and improved customer experience by adopting Oracle Autonomous Data Warehouse.
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Oracle
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: 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: IBM     Published Date: Oct 21, 2016
Between the Internet of Things, customer experience and loyalty programs, social network monitoring, connected enterprise systems and other information sources, today's organizations have access to more data than they ever had before-and frankly, more than they may know what to do with. The challenge is to not just understand that data, but actualize it and use it to recognize real business value. This ebook will walk you through a sample scenario with Albert, a data scientist who wants to put text analytics to work by using the Word2vec algorithm and other data science tools.
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ibm, analytics, aps, aps data, open data science, data science, word2vec, enterprise applications, business technology, data center
    
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
It's all well enough for an organization to collect every slice of data it can reach, but having more data doesn't mean you'll automatically get better insights. First, you have to figure out what you want from your data you have to find its value.
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ibm, aps data, data science, open data science, analytics, enterprise applications
    
IBM
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