Big Data, Analytics & Artificial Intelligence

November 25, 2014

Today’s health care system, in the United States and throughout the world, is still entering the 21st century. Costs remain high, there are great inefficiencies, and, for a large percentage of the population globally, access to care is inadequate. Our health care enterprises tend to focus on treating acute illness rather than improving and maintaining the health and wellness of populations. Today, “digital health” means advanced analytics based on multi-modal data; the “Health Care Internet of Things,” which uses sensors, apps, and remote monitoring to provide continuous clinical information; and data in the cloud that enables clinicians to access the information they need to care for patients in their home, their office, or 300 miles away, and to collaborate with specialists in another country.

Spotlight

Pivotal

Pivotal’s cloud native platform drives software innovation for many of the world’s most admired brands. With millions of developers in communities around the world, Pivotal technology touches billions of users every day. After shaping the software development culture of Silicon Valley's most valuable companies for over a decade, today Pivotal leads a global technology movement transforming how the world builds software.

OTHER WHITEPAPERS
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From Data to Mobility Insight

whitePaper | September 10, 2018

INCREASE RIDERSHIP & PASSENGER EXPERIENCE Due to the growth in urban population, there is an exponentially increasing demand for public transportation. Trains, busses, and other forms of mobility are now experiencing more crowds of people and are forced to deal with the consequences of it. With bigger masses of people comes decreased efficiency. Large floods of people accompanied with rush hour overcrowding, delays, human error, and malfunctioning machines creates a plethora of unhappy customers having to choose between waiting in long lines and finding an alternate mode of transportation.

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Five key principles to secure the enterprise Big Data platform

whitePaper |

Organizations face the risk of financial, legal and reputational damages if they do not take care of security for their data and IT systems. Enterprise Data Governance rules, European legal restrictions like the GDPR but also national or industry-specific data privacy laws such as BDSG or TKG in Germany clearly define how data needs to be protected in IT systems in order to avoid data security breaches. Additionally, regulations like the German BSI security law and the international ISO/IEC 27000-series define standards for minimizing threats to IT systems.

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The Rise of Data Capital

whitePaper |

Data is now a form of capital, on the same level as financial capital in terms of generating new digital products and services. This development has implications for every company’s competitive strategy, as well as for the computing architecture that supports it.

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PUTTING TECHNOLOGY TO WORK HOW FREIGHT RAIL DELIVERS THE 21ST CENTURY

whitePaper | May 14, 2018

POSITIONING FREIGHT RAIL FOR THE FUTURE Technology fuels America’s freight railroads, making a modern network capable of meeting today’s transportation challenges — and those of the future. Integrated teams of data scientists, software developers and engineers develop and apply technology across every aspect of the nationwide freight rail network. Today’s trains are powered by 200-ton locomotives equipped with supercomputers capable of processing a billion data points per second to maximize operational and fuel efficiency. Smart sensors throughout the network assess the health of the nation’s rail infrastructure and equipment to ensure safe operations. Railroad experts at command centers analyze this data to develop real-time maintenance and operational recommendations that improve fluidity and productivity of the rail network.

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Implementing the Enterprise Data Lake

whitePaper |

What is a Data Lake, and how does it help meet the challenges of Big Data? Will the Enterprise Data Warehouse (EDW) and the Data Lake coexist? If so, how? This paper explores what it takes to get started on the journey toward incorporating a Data Lake into an organization’s architecture. At least, that’s been true when we thought of data as finite. But, with the advent of Big Data, it’s pouring in like never before - and while we still want it in any form we can get it, structured or unstructured, the issues of storing, managing, and analyzing it are becoming more complex.

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Data Analytics Integrity Challenges to Implementation of the Automated Data Collection Processes

whitePaper | March 12, 2020

In recent months, my company (Baron Consulting) has been proactively involved in setting up Data Collection Systems for a range of Private and Public Organisations we are servicing. Some of the data collection challenges have already been discussed in our recent Raw Data Collection 2020: Principles and Challenges White Paper. While the RDC (Raw Data Collection) paper analysed the current state of the everchanging Data Collection requirements, it did not have the scope to address technicalities of the RDC processes along with the specific Data Collection tools and methods. The purpose of this paper is to fill the void by looking into implementation of the automated data collection processes.

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Spotlight

Pivotal

Pivotal’s cloud native platform drives software innovation for many of the world’s most admired brands. With millions of developers in communities around the world, Pivotal technology touches billions of users every day. After shaping the software development culture of Silicon Valley's most valuable companies for over a decade, today Pivotal leads a global technology movement transforming how the world builds software.

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