How to Become a Data Scientist

Clearly data science is very hot right now. Where I think data science contributes the most is basically converting numbers and data into consumable information for human brains; data science helps with decision-making. Beyond the hype and the application of the scientific method to business data, [data science] is a great way to convert the information hidden in the numbers and data into visually and conceptually understandable models that managers can make decisions upon

Source: www.information-management.com

With any position like data science, there’s a lot of excitement as people realize they can benefit from it. People see the value and the industry is really excited, which I think is great, but also there is a lot of confusion. The confusion [will die] down as people are getting used to what data science does and how it can [help decision-making], and some of the demand may die down as the extra excitement and hype goes down. But because of that root problem of data containing information which needs to be rotated and converted for humans to understand and make decisions, data science will stay here for a very, very long time – as long as businesses are generating data, and I don’t think that’s going anywhere. So I think there will be some clarification and some dying down of the hype in the near future, but I think data science is not just a fad and it’s actually a fundamental part of data-driven businesses.

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You can crunch it all you like, but the answer is NOT always in the data

But I think the issue has become much worse recently as data has become more freely available. For example, data journalism has emerged as a field in its own right. Some journalists have taken to applying tortuous analysis to large data sets and the results are then used to “prove” a particular point. Note the use of the word “some” in that last sentence; there are many excellent journalists who use data properly; but not all do so. And it is not just my fellow scribes who are guilty, it is increasingly apparent (although less publicly so) in the commercial world.

Source: www.theregister.co.uk

I am not (obviously) saying that data analysis is wrong; given my day job that would be an odd stance to take. But I do want to caution against the practices of the data analysis zealots and to make the point that context is vital because (despite what the zealots appear to believe) judgement and context are a major part of any good analysis.

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Energy Efficiency and Big Data Analysis | The Energy Collective

Consider that a one-time benchmarking exercise or an onsite audit is only a snapshot of a building’s performance and cannot capture the dynamic responses of a building. Therefore, this portfolio management platform must provide continuous tracking and benchmarking so that profiles are always up to date as the buildings’ physical systems evolve and external factors like weather and utility prices change. 

Source: theenergycollective.com

Consider that a one-time benchmarking exercise or an onsite audit is only a snapshot of a building’s performance and cannot capture the dynamic responses of a building. Therefore, this portfolio management platform must provide continuous tracking and benchmarking so that profiles are always up to date as the buildings’ physical systems evolve and external factors like weather and utility prices change. 

See on Scoop.itData Nerd’s Corner

The New Recruits in Moore’s Huge Data Program – Inside Philanthropy: Fundraising Intelligence – Inside Philanthropy

The Gordon and Betty Moore Foundation has a highly influential science program, giving big money to a spread of topics that includes earthquake detection, quantum materials, and marine microbiology. Oh, and the foundation is also building the world’s most powerful telescope in Hawaii, a project that it says “has the potential to transform the study of the universe.”

Source: www.insidephilanthropy.com

This is an extremely active field right now in research and particularly in science philanthropy, as we try to catch up with the rapidly expanding body of information in everything from genomics to economics. Moore kicked off its five-year, $60 million program with a bang by establishing with the Sloan Foundation a $37.8 million partnership with three universities, forming a hub for academics harnessing data. 

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New fundamental applied math result for Wall Street | LinkedIn

The fundamental result from section 2, the fact that E[M(n)] = SQRT(n/2), has important consequences for Wall Street traders. Basically, it means that the highest value a stock, index or commodity will reach (on average), during a period of n days, is

Max price = exp{c*SQRT(n)} / P,

where c is a coefficient depending on the commodity or stock in question (it’s higher for volatile stocks), and P is the value of the commodity or stock in question at the beginning of the time period in question.

Source: www.linkedin.com

You must have a diversified portfolio with many stock clusters or indices that are (1) not too volatile and (2) un-correlated. Assumption (2) needs careful analysis. This is required, because the result essentially applies to portfolios, not individual stocks.

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How Big Data Projects Are Different

An organization measuring the impact of social media in a marketing mix might have the following inputs: Customer satisfaction scores, likelihood to recommend, social media sentiment, marketing measures such as email clickthroughs, website visits, conversions, abandonment rates, sales transaction metrics across categories, and customer demographics. The organization might correlate participation in social media marketing using tracking URLs for attribution and determine correlation with uplift on the ecommerce site. This mix will have a number of inputs, since shopping conversion is only the last step in a potentially long series of activities and interactions, each of which strengthens or weakens the brand and the relationship.

Source: www.cmswire.com

Several important questions can be asked and answered: What content is most effective in engaging across various social media vehicles? How does variation in tone (humorous versus factual for example) impact the next behavior? How does that behavior change according to product line, web channel, specific web property, demographic segment, geographic territory, or user intent? The overall hypothesis consists of a range of questions about the impact of campaigns using a variety of methods for touching, attracting, engaging, converting and retaining customers

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Big Data As Boogeyman

Gibbs acknowledges that this foresight can be “pretty good” but worries about the potential downside: “Anonymized data often isn’t that … so actually tracking specific people could be possible and could lead to abuse in real world deployments.” Not to sound like a reactionary, but we have that now. With proper evidence, law enforcement officials can order wiretaps and surveillance and who knows what else. If the data is there, why not use it? I don’t like those signs that say “we ask for ID for your protection” but if you’ve ever had someone steal your credit card, it’s nice to have someone checking to make sure it’s really you passing the card.

Source: www.forbes.com

The problem here is one of boundaries – specifically the boundary between personal data and anonymous data. Big data can identify both, and its value comes from the ability to render both. It can recognize demographic patterns and trends on a grand scale. Its ability to identify personal trends – teen-age pregnancy notwithstanding – is less accurate. I once bought a book of French poetry on Amazon for my now-ex-father-in-law, an isolated action that probably confused the site’s algorithms for a while

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Building the next generation of female IT professionals

“What’s concerning to us is the dire need for diversity in the IT industry, and we see this huge gap in science, technology, engineering and math (STEM) skills and training, especially with women and minorities,” Bischke says. “While we have tools within our Entelo solution that allows recruiters and hiring managers to specifically focus on hiring from these underrepresented groups, we wanted to do more to encourage women’s interest in STEM starting very early,” he says.

Source: www.networkworld.com

While woman make up 48 percent of the US workforce, they comprise only 24 percent of STEM workers, according to the Census Bureau’s 2009 American Community Survey (ACS). In other words, half as many women are working in STEM jobs as one might expect if gender representation in STEM professions mirrored the overall workforce, according to data from a 2011 US Department of Commerce Economics and Statistics Administration report.

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Women in Data Science Are Invisible. We Can Change That | WIRED

I GOT LUCKY. I WAS TURNED DOWN FOR A JOB AT A GOOD BUSINESS SCHOOL BECAUSE I WAS JUDGED TO BE “TOO TECHNICAL” BY THE (MALE) HEAD OF THE DEPARTMENT. IN HINDSIGHT I SHOULD BE ETERNALLY GRATEFUL

Source: www.wired.com

Why Are Women in Data Science Invisible?

There are many excellent women in my field (I know many of them personally), but for the most part they are not on the radar for keynote speeches and rather few of them have titles like Chief Scientist. So, why do they seem rather invisible?

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Counting the cost of conflict minerals compliance – Rivo

This June was the first time that US-regulated companies were to provide any information on their conflict minerals compliance and only 6% met an acceptable standard.  It is obviously still early days, and organisations are not finding it easy to get the information they need from their complex supply chains.  After all, the minerals affected might be three or four degrees of separation down the chain from the actual manufacturer.  Additionally, the requirements of the rules (for now at least) are simply to identify and acknowledge the use of conflict minerals.  There’s plenty of assistance on offer out there too, organisations like the Conflict-Free Sourcing Initiative (CFSI), the Conflict-Free Tin Initiative and Solutions for Hope specialising in making it easier for companies to find responsible sourcers of materials.  Even the big consultancies have conflict mineral compliance practices.  So yes, it isn’t easy, but it’s not impossible.

Source: www.rivosoftware.com

So, this Fairphone which, just to recap, has been four years in the making, no doubt with much time and effort going into finding the conflict-free mines to source the materials from, can’t be particularly fairly priced surely?

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