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Data Lakes 2: Redressing Big Data Governance

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by Jelani Harper The perceived boons of utilizing a single repository (typically either Hadoop or another NoSQL platform) to store and access all data—structured or unstructured, regardless of schema—as a Data Lake are touted as: Universal enterprise access: Data Lakes enable all users to quickly access data (without time consuming and rigorous modeling constraints) from…

Building a Better Data Supply Chain

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by Jennifer Zaino The data supply chain must be simplified and it must be integrated. That’s the ultimate mission of Metanautix, another startup to emerge – at least in part – from the mind of a former Google employee. (You can read about the startup SpaceCurve, also with ex-Googler origins, here.) “A big part of…

The Mathematics of Data: Graph Analytics as a Service

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by Jelani Harper Graph databases are optimal for running advanced analytics because they indicate the relationship between data elements and allow for readily discernible inferences between them—yielding answers to questions that users never thought to ask. Leveraging the prowess of graph analytics (especially on Big Data sets), however, has traditionally been hampered by: A general…

Bringing the Semantic Web and Linked Data to All

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by Jennifer Zaino The Semantic Web and Linked Data promise so much to so many in the world. They provide the foundation for identifying and classifying content, while exposing, sharing, and connecting pieces of data on the Web via the W3C’s Resource Description Framework (RDF) standard. The vision revolves around increasing the Web’s usefulness and people’s access to…

Starting Small with Big Data

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by Jelani Harper The inhibitors of Big Data initiatives are abundant and include: Upfront capital: There is a general perception that the infrastructure to apply Big Data and options for advanced analytics are costly, and that such initiatives are widely reserved for large organizations instead of small- and mid-sized ones. Technological gaps: Costs notwithstanding, many…

Contemporary Trends in Master Data Management

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by Jelani Harper Master Data Management (MDM) is changing to reflect some of the more influential technologies in the Data Management space today, which includes Big Data, graph databases, Cloud Computing, social media, mobile, and others. Collectively, these technologies reflect the overall trend of MDM’s evolution from specific domains and lines of business, to enterprise…

Best Practices for Master Data Management

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by Jelani Harper There are a number of Master Data Management (MDM) solutions that cater to specific domains (customers or products), multiple domains or even certain industries. The deployment of these options; however, can frequently shift the burden of MDM to technology instead of holistically addressing the consensus required of workers across various departments regarding…

Graph Databases are in the Spotlight, and so is Neo4j

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by Jennifer Zaino Graph databases have had it pretty good the past year or so. Some highlights since the end of 2013 include: Gartner for the first time allowed graph databases to be included in its 2014 Magic Quadrant for Operational Database Management System (ODBMS). Graph database management systems saw a more than 250 percent…

Stop Data Misuse, Speed Data-Driven Innovation

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by Jennifer Zaino Like most companies, yours probably has in place information governance policies to govern the use of the data you collect to ensure compliance with internal and external privacy, and security requirements. Likewise, your business is apt to have a tool-belt of technologies on hand to monitor and log activity around that data,…