TMS Prospector reveals new insights.

See on Scoop.itData Nerd’s Corner

Picking out relationships between information contained in thousands of records has recently become much easier thanks to an innovative product launched by Text Mining Solutions. The new product,…

Carla Gentry CSPO‘s insight:

Steve Brewer, Director, Text Mining Solutions said: “In making best use of the power of text mining three key elements need to be combined: collecting, processing and visualising text data. The first two elements are addressed by a structured approach to searching and storing of data, but it is the third element – visualisation – which brings the results to life. By being awarded a Technology Strategy Board Innovation Voucher, we have been able to collaborate with the University of Sheffield to develop this new visualisation programme which we are now ready to take to market.” 

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We Want To Share Your Blog Content, RSS and Expand Your Reach

Starting over two years ago, we evaluated social media and content marketing challenges together and very clear and connected obstacles stood out like a sore thumb. The question of “How do I get more blog traffic?” -or- “How do I increase traffic to my content?” always comes up.


Today Bundle Post begins an expansion from our unique social media content management, curation and scheduling roots, to the addition of content marketing, traffic building and extending reach for blogs and content creators. Today we are announcing the Bundle Post RSS Project that has already begun databasing, categorizing and indexing RSS feeds across the web.

Where’s yours?

Bundle Post RSS IndexFrom the beginning, the aim of Bundle Post was to make social media marketing and curation far more efficient and effective for brands, agencies and marketers. As we have continued to grow and expand our capabilities in this area, we have always realized that tackling the blog, traffic and content marketing issues were also connected digital marketing pains that bloggers, brands and marketers experience.

Starting over two years ago, we evaluated social media and content marketing challenges together and very clear and connected obstacles stood out like a sore thumb. The question of “How…

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Statistical or Clinical Significance… that is the question!

Clinical relevance is commonly assessed as a result of an intervention. Nevertheless, it can be also extended to any other non experimental study design types, for instance, for cross-sectional studies.
To sum up, both significances (statistical and clinical) are not mutually exclusive but complementary in reporting results of clinical research. Researchers should abandon the only use of the p-value interpretation. Here you have a starting point for the evaluation of the clinical relevance.


Most of the times, results coming from a research project – specifically in the health sciences field – use statistical significance to show differences or associations among groups in the variables of interest. Setting up the null hypothesis as no difference between groups and the alternative showing just the opposite –i.e, there is a relationship between the analyzed factors –, and after performing the required statistical method, a p-value is provided. This p-value indicates, under an established threshold of significance (say, Type I or alpha error), the strength of the evidence against the null hypothesis. If the p-value is lower than alpha, results lead to a statistically significant conclusion; otherwise, there is no statistical significance.

According to my personal and other biostatisticians’ experience in the medical area, most of physicians are only interested in the statistical significance of their main objectives. They only want to know whether the p-value

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Free data science courses from Johns Hopkins, Duke, Stanford

See on Scoop.itData Nerd’s Corner

If you’ve thought about trying to boost your data skills, check out Coursera’s catalog of free classes. In particular, Johns Hopkins is about to start a nine-class specialization in data science.

Carla Gentry CSPO‘s insight:

This spring, Johns Hopkins’ data science specialization gets underway. It’s nine classes, the first of which begins April 7 (repeat sessions are also offered during the next few months). Students can earn an optional "Verified Certificate," which costs $49 for each of the nine courses. Those who complete all nine courses plus a final capstone project — and pay for a certificate for each — will earn a Specialization Certificate from Johns Hopkins.

But — to reiterate — any of the nine courses can be taken for free if you don’t mind skipping the certificates.

The professors for Johns Hopkins’ data science specialization include: Brian Caffo, professor in the department of biostatistics; Roger Peng, associate professor of biostatistics; and Jeff Leek, assistant professor of biostatistics.

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Big Data Classes For CXOs – InformationWeek

See on Scoop.itData Nerd’s Corner

Teaching C-suite executives the fundamentals of big data, a topic once confined to the rarefied world of computer scientists, is becoming a growth industry.

Carla Gentry CSPO‘s insight:

Although big data is in the spotlight now — thanks in large part to the volume and variety of data gushing out of social media channels — getting non-IT business executives to pay attention to data isn’t a new problem, said Carla Gentry, a 20-year industry veteran and founder of consultancy Analytical-Solution.


But Gentry is dubious that a two-day seminar will make a difference to business leaders who continue to fly by instinct.

"Do we need to get rid of the prima donnas who think they know better than the data? Yes," she said in a phone interview.

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Mining Student Data To Keep Kids From Dropping Out

See on Scoop.itData Nerd’s Corner

It’s report card day at Miami Carol City Senior High, and sophomore Mack Godbee is reviewing his grades with his mentor, Natasha Santana-Viera.

The first quarter on Godbee’s report card is littered with Ds and Fs. This quarter, there are more Cs and Bs. He’s got an A in English.

“Congratulations on that,” says Santana-Viera. “When you need help, do you know where to go?”


Carla Gentry CSPO‘s insight:

It’s easy to collect information and look at information,” says Scott Crumpler, the South Florida field manager for Diplomas Now. “But what you do with that information is the key element and key component of our program.”

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Develop your brilliant data scientists by going broad without crushing their egos

See on Scoop.itData Nerd’s Corner

Intelligence isn’t the only quality you want in a data scientist. Here’s how to ensure your team members develop their breadth of knowledge and become more effective.

Carla Gentry CSPO‘s insight:

Develop your breadth of knowledge and make it a point to engage your team in conversations about history, geography, politics, and sometimes obscure topics like archeology or ontology. Challenge yourself to draw correlations between world events and something more relevant to their work. For instance, how is the recent posturing by Russia similar to the dynamics in some of our work streams? How does a jetliner just disappear from sight, and how is that similar to our information monitoring risks?

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Data is the customer’s voice, so you need to pay attention to it in as many ways as possible

Uber, however, takes a different approach, according to senior data scientist Henry Lin: the car-service company keeps its data team completely separate from the product management side, he said, so that they can pursue whatever research projects or experiments they think might help make the service more efficient. And the data science team reports directly to CEO Travis Kalanick, he said.


The fact that data is important to the running of most businesses, particularly technological ones, is now taken for granted, but how do you integrate the collection and understanding of that data into your company so that it makes a difference? Three fast-growing web companies — Uber, Airbnb and LinkedIn(s LNKD) — talked about the different ways they do this at Gigaom’s Structure Data conference in New York on Thursday.

Riley Newman, the head of the data science group at Airbnb (which is rumored to be raising a new round of financing that could value the company at $10 billion, according to the Wall Street Journal) said that from his perspective “data is the lifeblood of our business — we think of it as the customer’s voice. It’s them telling us what works and what doesn’t work, so we always start with the data.”

Newman said that Airbnb approaches…

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How to Bridge the Gap Between HR and IT

See on Scoop.itData Nerd’s Corner

A poor IT-HR relationship can lead to bad IT hires. IT managers need to provide HR with sharp questions about applicants’ technical skills. And HR pros need to do their homework about IT.

Carla Gentry CSPO‘s insight:

While HR professionals can find broadly qualified technologists and network administrators, highly specialized skills such as cloud computing, DevOps software development, NoSQL databases and big-data analytics are often beyond HR’s ability to evaluate.

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David F. McCoy of Cloudera talks about being a data scientist

See on Scoop.itData Nerd’s Corner

Big data only means big money because of the people behind the technology. Yesterday, Palo Alto, California-based Cloudera announced a $160 million fundraising round led by T. Rowe Price, Google Ventures and more. But it wasn’t until today that the company pulled the curtain back on one of its ever-so-valuable data scientists, David F. McCoy.

Carla Gentry CSPO‘s insight:

In the Sherlock Holmes stories, his sidekick, Dr. Watson, describes their adventures as a “half-sporting, half-intellectual pleasure.” I like to say data science is a “half-scientific, half-engineering pleasure.” There is the unknown a-ha or eureka factor of scientific investigation paired with the constructive design satisfaction of engineering code to perform the analysis and deal with large size and large dimensionality data sets.

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