Data Articles | Data Science, Business Intelligence, & More

Monetizing the Industrial Internet of Things

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by Jelani Harper The Industrial Internet of Things may well be the ultimate expression of where the data sphere is heading in the next couple of years. It combines Big Data sets with real time and predictive analytics (Operational Intelligence) capabilities through the Cloud to influence decision making and to create and tailor a variety…

Bringing Clarity to the Topic of Cognitive Computing

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by Jennifer Zaino DATAVERSITY’s™ Cognitive Computing Forum is taking place this August in San Jose, and in advance of the event, the team here also has released the 2014 Cognitive Computing Survey as well as conducted the webinar Understanding The World of Cognitive Computing. Just like the upcoming Forum, with presenters tackling topics ranging from…

The Data Architecture Trinity

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by Michael Brackett Past articles have explained the data description, data structure, and data integrity components of a formal data resource architecture.  The diagram below shows those three components in graphical form.  The descriptive component consists of two sub-components for formal data names and comprehensive data definitions (The Missing Descriptive Component, A Suitable Descriptive Component). …

Building More NoSQL Support with Rich Development Experience

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by Jennifer Zaino Know UnQL (Unstructured Query Language)? It was designed to be a community-supported, common database query language that could be used to access document-oriented databases from a range of vendors, enabling application portability across database engines and easing the load on application developers. Its SQL-like syntax was meant to be especially helpful to…

Data Science and Art: RRE Certification

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by Jelani Harper Gartner describes Open Source R—arguably the script of choice for Data Scientists and one of the most pivotal tools for creating advanced and predictive analytics—as “increasingly popular” (Herschel et al, 2014), while Forrester lauds its ubiquity. As one of the earliest champions of Open Source R, Revolution Analytics swiftly addressed its scalability…

Governing Self-Service Analytics

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by Jelani Harper It is possible to simultaneously empower the end user and his or her business objectives with self-service analytics and self-service Business Intelligence, while still ensuring full adherence to existing Data Governance policies, roles, and structure. It is also possible to combine the benefits of the traditional centralized approach to BI (governance, privacy,…

The Open Source Analytics Invasion

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by Jelani Harper Open Source analytics have transformed the analytics space in Data Management in much the same way that Hadoop (another Open Source technology) has transformed Big Data. Open Source analytics have almost single-handedly transfigured the way: Commercial and proprietary Business Intelligence (BI) and Analytics providers provide script support to and integration options with…

Transforming Ecommerce with Predictive Analytics

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by Jelani Harper One of the most tangible ways to justify the use of predictive analytics in a data-driven strategy is to incorporate them into marketing and ecommerce. The goal is simple, yet deceptively elusive to convert Web traffic and onsite ‘clicks’ into customers and purchases. Traditional methods involving Web analytics platforms focus on customer…

Predictive Interaction Technology Frees Up Data Professionals’ Time

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by Jennifer Zaino As a data professional, how much of your time is spent working on fixing up your data, rather than working on answering questions and solving problems with your data? On average data cleansing and transformation takes up 80 percent of data professionals’ time, according to Joseph Hellerstein, a Chancellor’s Professor of Computer…

Big Data Governance Software: Sensitive Data

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by Jelani Harper There are numerous reasons as to why Big Data Governance is one of the foremost concerns for enterprises across vertical industries: Compliance and regulatory issues: Industry specific compliance standards are becoming more strictly enforced, requiring organizations to know what data they have, where it is, and who can access it to avoid…