Not A Data Scientist? You Can Still Be Data Savvy


Christian Bonilla says he has been amused for a while by the tone of articles he’s read that marvel at the rise of the data scientist role, while not every article went so far as to declare that data scientists would have the “sexiest job of the 21st Century” as Harvard Business Review did, most of the posts seen lately echoed the we-have-seen-the-future tone.
Christian doesn’t think they’re necessarily wrong (although this short Fortune article is a good reminder that the laws of supply and demand apply to data scientists too) but he doesn’t see what is surprising or a new about this trend. If The Onion were covering this story, he’d expect a headline like: “New study reveals that people who are good at math and programming are employed, affluent.”

Where’s the news here? People with math and programming chops have been getting rich on Wall Street since the seventies. As more companies generate big data, the need for these skills has expanded to new industries, to say nothing of the demand for these skills in the tech sector, but it’s all part of a long-term upward trend of the value of quantitative skills.

At many companies, the mandate of the “customer insights” team is to serve as a shared resource for other departments when they need someone who can understand the damn data and answer their questions. And why is this?

The systems companies have in place are partly to blame. Many enterprises, particularly ones that grew by acquisition and inherited multiple IT departments as a result, store their data in systems that are difficult for non-technical employees to use. That alone discourages the vast majority of people from ever touching their company’s raw data. But the larger obstacle is simply that even if decent tools are available, it takes know-how and patience most people don’t have to analyze data that’s in a relational database as opposed to in a dashboard or an Excel file. It’s not just learning SQL, either. Understanding a company’s data model and how it stores data well enough that you can query it accurately takes patience and a lot of trial and error. There’s a big difference between the data you work with in business school and what you often see in the real world in terms of data reliability and quality. This is why the vast majority of people rely on aggregated reports and cleansed data they get from their IT departments; they can trust the data without thinking twice about it.

The problem with relying on dashboards and pre-built reports to do your analysis is that it’s hard to do work that sets you apart when you’re looking at the same small sliver of the facts as everyone else.

Data quality is important, and companies emphasize having a single version of the truth for good reason, but it can seriously constrain your creativity. That’s the kind of analysis that makes your boss lean in and listen to what you’re saying. Being able to do it on your own is ten times better than having to ask someone else to do it for you.

Best of all, you don’t need more than junior-high math to answer that question. All you need is an inquisitive mind and the right data.

Christian Borilla: It’s said that smart people ask hard questions while really smart people ask simple ones. Indeed, many of the most important questions you can ask about your company are the simplest. Why do people choose our products over our competitors’? Why do customers leave us when they do? Should we offer discounts to boost sales? When you’re up to your neck in being a good do-er it’s easy to lose sight of these fundamental questions because people don’t ask you to answer them when you’re still green. But oh, the liberation when you can! This is how you can begin to understand and contribute to solving some of themost important challenges facing your business today.

Learning SQL and how to interrogate a company’s raw operations data to answer fundamental questions about its business was probably the most useful business skill I acquired in the early years of my career. As it turned out, I was a natural at asking good questions and just needed the tools to be able to answer them. But more than that, a marvelous thing happens inside the business person’s mind as a result of analyzing a business through its internal databases: the discipline of querying databases teaches you to ask better questions. More specifically, it teaches you how to structure big questions in such a way that they can actually be answered with precision. It forces you to clean up lazy thinking, because computers don’t allow vague questions. It teaches you to think in sets, an incredibly valuable mindset, without even realizing it. In short, it makes you a better business person by allowing you to more fully capitalize on your domain expertise. I know it changed my career tremendously for the better.

Original Source (Smart Like How)

Advertisements

Data Science Talent is Key to Analytical Innovators


Technopreneurph

Companies continually look for ways to outperform their competitors. One way they are trying to get ahead is through the application of analytics on their data. Researchers, for example, have found that top-performing businesses were twice as likely to use analytics to guide future strategies and guide day-to-day operations compared to their low-performing counterparts.

Researchers from MIT and SAS suggest that top performing companies use analytics differently than bottom performing companies. They found that Analytic Innovators (businesses where analytics created a competitive advantage and has helped innovation), more so than Analytically Challenged, use analytics primarily to increase value to the customer rather than to decrease costs/allocate resources, aggregate/integrate different business data silos to look for relationships among once-disparate metrics and gain executive support around the use of analytics to encourage sharing of best practices and data-driven insights throughout the company.

Analytics don’t occur in a vacuum. Companies need the right…

View original post 402 more words

How Much Will You Pay to Protect Your Data?


A “Putting a price on data” infographic, very interesting article and arguments on the current Information Society.

What's The Big Data?

View original post

Big Data: The New Natural Resource


BusinessWorld

Facebook, Twitter, Pinterest. Destroyers of our attention span or innovations that make us smarter and closer? We’re still trying to understand how today’s technologies—which many can’t seem to live without—are transforming us.

Still, there is one change they’ve brought about that’s indisputably positive, one that most people intuitively get.And it’s this: if we live in an information age, then the flip side is we’re all information analysts.

Cloud computing, mobile and social computing are all changing how we communicate. Our strategy for big data and analytics has some core tenants, which provide a common experience. The combination of cloud, social, mobile and big data and analytics provides the user with a role-specific experience that is easy-to-use and customizable. The cloud enables organizations to start small, grow rapidly and scale massively.

Why Big Data Is The New Natural Resource.

View original post

Brief Introduction: Dive Into the World of Data


Data Science- All you need to know.

What is Data science?

Data science is magic.

Magic, not just because it can grow exponentially and unpredictably, neither because of the vastness in context of what each data holds within, but also because it has capability to re-define the entire process of how the perfectly armored and sophisticated model or a product (in theory) can be actually nothing but perfectly imperfect. What is interesting is, even when we do not know “why” the product’s marketability is low, we are ready to make decision with “what” is the reason for product’s marketability to be low. The data is everything. Once you understand the concept why it is important, you begin to know that everything could be possibly made perfect (as close to it as possible).


View original post 835 more words

Microsoft Buys Data Science Specialist Revolution Analytics


Gigaom

Microsoft has agreed to acquire Revolution Analytics, a company built around commercial software and support for the popular R statistical computing project. The open source R project is hugely popular among data scientists and research types, and having Revolution’s R experts in-house could be a big deal for Microsoft as it tries to establish itself as the go-to place for data science software.

Among Revolution’s additions to the standard R capabilities were simplifying the use of the program and engineering it to run across big data systems such as Hadoop. Here’s how Joseph Sirosh, Microsoft’s corporate vice president for machine learning, explains what the deal means in a blog post:

As their volumes of data continually grow, organizations of all kinds around the world – financial, manufacturing, health care, retail, research – need powerful analytical models to make data-driven decisions. This requires high performance computation that is “close”…

View original post 412 more words

What Teens Really Want To Know About Sex


ideas.ted.com

Remember how weird it was to ask questions about sex as a teenager? High school teacher Al Vernacchio answers his students’ questions about everything from DIY birth control to how to tell when a guy really likes you, in an excerpt from his new book.

On the first day of my Sexuality and Society class, I don’t pass around anatomy drawings. I don’t hand out pamphlets about safer sex, although those are stacked on a table near the door. Instead, the first thing I do is establish ground rules. People should speak for themselves, laughter is OK, we won’t ask “personal history” questions, and we’ll work to create a community of peers who care about and respect one another. Only then can we get to work.

I’m all about context. Talking about sexuality, intimacy, relationships, and pleasure can’t be done in a vacuum.

In the back corner of my classroom is an…

View original post 1,365 more words

Google Aims to Archive All Human Knowledge


According to an intriguing report in New Scientist, Google is building a next-generation information database called Knowledge Vault that’s designed to index and store what we can reasonably term facts. And not just some facts — the Vault is intended to continually catalog and store all facts about our world and our history.

See also:  Google “Knowledge Vault” To Power Future Of Search Database could be the foundation for array of next-gen applications

The Vault project is building upon Google’s existing crowdsourced database, Knowledge Graph, and so far has cataloged about 1.6 million facts. Google researchers will present a paper on Knowledge Vault next week at the Conference on Knowledge Discovery at Data Mining, in New York.

It’s all part of a larger initiative, in the information technology arena, to improve the manner in which we interact with machines and databases. Similar knowledge bases are being built by companies like Facebook, Amazon and Microsoft and IBM.

One of the first practical applications for these ultra-database systems is to create a new generation of virtual personal assistants.

Down the line, the Knowledge Vault could serve as the foundation for advanced augmented reality networks. The database would provide instant data, via heads-up display, on virtually anything you look at.

The Knowledge Vault could also be used, eventually, to model all of human history and society as a vast collection of pure data. That knowledge, in turn, could be extrapolated to make predictions about the future.

Original Source
Other Source

Will We Have Any Privacy After the Big Data Revolution?


TIME

Does the rise of big data mean the downfall of privacy? Mobile technologies now allow companies to map our every physical move, while our online activity is tracked click by click. Throughout 2014, BuzzFeed’s quizzes convinced millions of users to divulge seemingly private responses to a host of deeply personal questions. Although BuzzFeed claimed to mine only the larger trends of aggregate data, identifiable, personalized information could still be passed on to data brokers for a profit.

But the big data revolution also benefits individuals who give up some of their privacy. In January of this year, President Obama formed a Big Data and Privacy Working Group that decided big data was saving lives and saving taxpayer dollars, while also recommending new policies to govern big data practices. How much privacy do we really need? In advance of the Zócalo event “Does Corporate America Know Too Much About You?

View original post 944 more words