More Big Data In Depth
Hive's SQL-like query language and vastly improved speed on huge data sets make it the perfect partner for an enterprise data warehouse
The partnership announced last week isn't just about selling more iPhones. It's part of a big push into the Internet of Things.
It's up to each one of us to figure out what in the daily surge of data is useful, what's crap and what's truly valuable.
Microsoft has jumped in with both feet with the release to Preview of a new Microsoft Azure-based tool that helps organizations do Machine Learning and predictive analysis all from a Web console.
In a recent research survey, ESG asked security professionals to identify the most important type of data for use in malware detection and analysis (note: I am an employee of ESG). The responses were as follows:
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Apache Cassandra is a free, open source NoSQL database designed to manage very large data sets (think petabytes) across large clusters of commodity servers. Among many distinguishing features, Cassandra excels at scaling writes as well as reads, and its "master-less" architecture makes creating and expanding clusters relatively straightforward. For organizations seeking a data store that can support rapid and massive growth, Cassandra should be high on the list of options to consider.
Ever since President Obama signed the Open Data Executive Order, government agencies have been making their vast data stores available to the public. These once-secret data sets are proving a valuable business resource, too.
While the path-to-mastery pattern is conceptually simple, successfully executing it requires courage, perseverance and patience.
Big data and analytics permeate virtually every move Ford makes, from forecasting the worldwide price of commodities to figuring out what exactly consumers want, what it will build, where it should source parts and how to power its lineup of vehicles.
Here's one way to use big-data skills as the holidays approach: Find out what recipes are most popular. Analysts parsed 78 million November page views at Allrecipes.com to see favorite Thanksgiving foods by state.
R is mighty, but it can be complex for data tasks. Learn how to get summaries, sort and do other tasks with relative ease. (Now updated with dplyr examples.)
Companies are taking matters into their own hands with internal controls, open privacy policies, ethical codes and greater candor over how they're collecting and parsing personal data. But many wonder whether it's enough to allay consumers' fears as techniques for manipulating data multiply.
For the CIO job, things are going to get bigger, better and different on a massive scale.
Dat Tran, deputy assistant secretary for data governance and analysis at the Department of Veterans Affairs, says it's not enough to just collect data. He says the VA needs to transform its data into information that gives decision-makers insights into veterans' needs.
The era of big data requires new storage strategies. But thanks to faster and smarter technologies, these approaches don't have to break the bank.
Analyzing very large amounts of data and looking within it for patterns, trends, and insights is a practice that nearly any business, large or small, can use to help make better decisions.
Vanguard Health Systems' IDology platform identifies target populations for marketing efforts, bringing in new revenue.
Harvard's Clean Energy Project is using a distributed volunteer computing platform to perform quantum chemical calculations on millions of organic material candidates. Researchers could perform in three years, what a single computer would need 17,000 years to handle.
Ingram Micro implemented a new contract renewal system that uses data from its ERP and CRM systems, product catalogs, pricing documents, and point of sale, ordering and transaction systems to identify expiring contracts.
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