Open AccessBook
Big Data Analytics: Turning Big Data into Big Money
TLDR
Ohlhorst et al. as mentioned in this paper focused on the business and financial value of big data analytics and discussed how to turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportunities.Abstract:
Unique insights to implement big data analytics and reap big returns to your bottom lineFocusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportunities. Reveals big data analytics as the next wave for businesses looking for competitive advantageTakes an in-depth look at the financial value of big data analyticsOffers tools and best practices for working with big dataOnce the domain of large on-line retailers such as eBay and Amazon, big data is now accessible by businesses of all sizes and across industries. From how to mine the data your company collects, to the data that is available on the outside, Big Data Analytics shows how you can leverage big data into a key component in your business's growth strategy.read more
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Journal ArticleDOI
Big data analytics in healthcare: promise and potential
TL;DR: Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs, and its potential is great; however there remain challenges to overcome.
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Machine Learning With Big Data: Challenges and Approaches
TL;DR: This paper compiles, summarizes, and organizes machine learning challenges with Big Data, highlighting the cause–effect relationship by organizing challenges according to Big Data Vs or dimensions that instigated the issue: volume, velocity, variety, or veracity.
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Big-data applications in the government sector
TL;DR: In the same way businesses use big data to pursue profits, governments use it to promote the public good.
Journal ArticleDOI
Data management in cloud environments: NoSQL and NewSQL data stores
TL;DR: This study has identified challenges in the field, including the immense diversity and inconsistency of terminologies, limited documentation, sparse comparison and benchmarking criteria, and nonexistence of standardized query languages.
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Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph
TL;DR: Case studies results indicate that the proposed data analytic approach enable firms to utilise big data to gain competitive advantage by enhancing their supply chain innovation capabilities.