Deploying Big Data Analytics Applications to the Cloud: Roadmap for Success

May 16, 2014

Big Data focuses on achieving deep business value from deployment of advanced analytics and trustworthy data at Internet scales. Big Data is at the heart of many cloud services deployments. As private and public cloud deployments become more prevalent, it will be critical for end-user organizations to have a clear understanding of Big Data application requirements, tool capabilities, and best practices for implementation. Big Data and cloud computing are complementary technological paradigms with a core focus on scalability, agility, and on-demand availability. Big Data is an approach for maximizing the linear scalability, deployment and execution flexibility, and cost-effectiveness of analytic data platforms. It relies on such underlying approaches as massively parallel processing, in-database execution, storage optimization, data virtualization, and mixed-workload management. Cloud computing complements Big Data by enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction.

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GBL Healthnet Pvt. Ltd.

GBL services medical practices and facilities with a combination of cutting edge technology and old-fashioned respect for each group’s professionalism and individuality.

OTHER WHITEPAPERS
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The Lock and Key of Data Literacy and Data Governance

whitePaper | November 24, 2022

Without a data-literate team, your company doesn’t have a chance of becoming data-driven. “Speaking data” is one of the biggest skills in the coming years as more technical skills (think SQL or R programming) become embedded in the tools themselves, demonstrating what we’ve always known — that tools will only take you so far. Your real resource is people.

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A Review of BioPharma Sponsor Data Sharing Policies and Protection Methodologies

whitePaper | September 12, 2022

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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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Tackling climate change with data science and AI

whitePaper | April 2, 2023

In this white paper, we share how The Alan Turing Institute’s AI for science and government (ASG) programme has been using collaborative and multidisciplinary data science and AI to help tackle climate change.

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IT@Intel: Accelerated Analytics Drives Breakthroughs in Factory Equipment Availability

whitePaper | September 23, 2022

For Intel’s complex factory environments, quickly identifying tools that are operating below their optimal capacity and finding the root cause is crucial for maximizing production output. With thousands of tools involved in production and each manufacturing tool running from one to 50 operations, there are tens of thousands of tools and operations to monitor, analyze and adjust. Knowing where to focus engineering efforts is a monumental challenge.

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The Power of Graph Data Science: Maximizing the Value Of Data Through Predictive Insights

whitePaper | September 28, 2022

Graph data science (GDS) is a scientific approach to gain knowledge from graphs, using the structures of connected data to power predictions, answer questions, and explain outcomes.

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GBL Healthnet Pvt. Ltd.

GBL services medical practices and facilities with a combination of cutting edge technology and old-fashioned respect for each group’s professionalism and individuality.

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