One of our favorite features of Safari is the quality and variety of publishing partners who provide valuable content to our library. A partner that exemplifies this breadth and depth is Elsevier, an international multimedia publishing company that provides content across an incredible range of topics.
As part of a continuing feature here at the Safari blog, we’d like to shine a spotlight on the imprints of Elsevier that provide content to Safari.
by Julian Gamble
Did you know that NASA has debugged a spacecraft 100M miles away with LISP REPL?
Would you like to have that same power in your Java app today? (As an aside, some might contend this powerful enough to create a risk, so you should consider if this fits your needs. Don’t give access to this to anyone who shouldn’t have root access your server.)
Today we’re going to build a web REPL in Clojure. Then we’ll integrate it into a Java application. Then we’ll use it to read a value inside the Java application that otherwise we’d have no visibility of. Read more »
by Robert Maurer and Michelle Gifford
On a daily basis we are called on to help others. We do this as parents, spouses, and friends; and we do this in the workplace, as employees, colleagues, and managers. But how often do we consciously and skillfully pull from our toolbox the right strategy for guiding, motivating, and inspiring another person? And, if our first efforts fail, how creative are we in finding another strategy? Collaboration, coaching, and mentoring are certainly rewarding when done well, but they can be both painful and ineffective when done poorly.
Imagine that you are preparing to talk with a colleague, employee, or a family member. Your goal is to help them improve their current situation, performance, or life. What is your approach? How do you decide what strategy to use? Or, do you think in terms of strategy at all? If one approach isn’t working, do you have a plan B or C ready? When I interview executives who are required to give feedback to employees, I ask them to list their strategies for this challenging task. They often say, hesitantly, “I just tell it like it is…” or “I give it to them straight.” I then inquire, “So, how well is that working?” The answer, usually accompanied by an uncomfortable smile, is “sometimes.” And sometimes, direct feedback – no matter how painful it is to give or receive – is the right response. But not always.
To achieve strong collaboration, different situations call for varying types of feedback and support. For those situations where a more strategic approach is called for, allow me to provide you with a “gourmet guide” of support that will help you to provide assistance and motivate others at work and at home. For those times when you are the one in need of support, you can also use this menu to help identify what you might need from others.
There are seven strategies that are especially useful and are easily recalled using the mnemonic of INSPIRE. The word is a fitting, since inspire means “to take in.” When you are providing feedback or support, you want the other person to take in and be inspired by what you have to say. Read more »
Vision statements on a wall, on a website, or on a piece of paper can serve a purpose for businesses, but they don’t lead to success. The purpose of a vision is to have something not just to move towards, but to achieve. We need to challenge ourselves to move beyond the just the emotional connection to a vision and focus on mapping out the hard work it takes to get somewhere you want to go. A big mistake leaders make is that they think simply having a vision is enough, it’s not.
Research and reality tells us how it is. Psychologist Lien Pham and Shelley Tailor from University of California (Pham & Taylor, 1999) put students into two groups. They asked one group (Group A) to visualize how great it would be to get a high grade. The other group (Group B) wasn’t asked to visualize the positive feelings associated with the end state of a high grade. Both groups kept track of the hours they spent studying. Even though the group that visualized the positive feelings associated with a good grade only did this for a few minutes it had a significant impact on the amount of time they studied as well as their grades. The group of students (Group A) that visualized the positive feelings ended up studying less and ended up with lower grades. The visualization may have made them feel good, but it did not prepare them for success and therefore set them up for the failure. My view is that Group A, that associated the positive feelings with the outcome, became overconfident and were not aware and/or not realistic about how to get to what they wanted.
What makes the point even more clearly is that the researchers had a third group of (Group C). This group was asked to visualize the “how” or process of getting an A for a few moments a day. They were asked to get into more detail and visualize how and what they would do to get an A. Compared to the group (Group A) that just visualized the outcome of getting an A, and to the group that wasn’t asked to do anything (Group B), the group that was asked to visualize the “how” (Group C) ended up studying more hours and earned higher exam grades than both groups. The researchers concluded that visualizing the steps to prepare them for success put them in a more realistic and practical vision to succeed. Read more »
Recently, we were able to ask five questions of Murtaza Haider, about the new book from IBM Press called “Getting Started with Data Science: Making Sense of Data with Analytics.” Below, the author talks about the benefits of data science in today’s professional world.
Only a few years ago there did not exist a job with the title Chief data scientist. But that was then. Small and large corporations, and increasingly government agencies are putting together teams of data scientists and analysts under the leadership of Chief data scientists. Even White House has a Chief data scientist position, currently held by Dr. DJ Patel.
The traditional role for those who analyzed data was that of a computer programmer or a statistician. In the past, firms collected large amounts of data to archive rather than to subject it to analytics to assist with smart decision-making. Companies did not see value in turning data into insights and instead relied on the gut feeling of managers and anecdotal evidence to make decisions.
Big data and analytics have alerted businesses and governments to the latent potential of turning bits and bytes into profits. To enable this transformation, hundreds of thousands of data scientists and analysts are needed. Recent reports suggest that the shortage of such professionals will be in millions. No wonder we see hundreds of postings for data scientists on LinkedIn.
As businesses increasingly depend upon analytics driven decision making, data scientists and analysts are simultaneously becoming front-office superstars, which is quite a change from them being the back office workers in the past. Read more »
I cringe each time I hear the oft repeated declarations that “every company will be compromised” and that “it isn’t a matter of if, but when”. These statements are the basis of the FUD (fear, uncertainty and doubt) driven cyber sales machine. What is closer to the truth is that Internet connected systems have a high probability of being subject to a targeted or opportunistic attack, inadvertent exposure, or malicious subversion. However, it is (and I stress) not inevitable that the attacker will be successful. Motivation, work factor, evasion capabilities, resiliency, and sometimes, luck all play a part. Threat modeling can be used to understand these factors and influence the outcome.
Threat modeling is used to identify and categorize potential threats. Conventional cybersecurity threat modeling uses one of three approach; attacker-centric, architecture-centric, or asset-centric.
Many organizations find this task daunting. Do not despair! Threat modeling does not have to be overwhelming. A simplified approach to threat modeling is to answer four essential questions that identify threat adversary motivation, attack workfactor, organizational threat intelligence and detection capability, and resiliency. Read more »
Problems and opportunities.
They’re becoming more complex and coming at us so fast that we can either get run over by them or strive to identify, understand, and conquer them. Read more »
A data model is a precise representation of an information landscape, in much the same way as a map is a precise representation of a geographic landscape. “Precise” is the key characteristic of a data model, which means that there is a clear, unambiguous way of reading every symbol and term on the model. A team of business analysts for example, will all read the data model the same way and understand exactly what is being communicated, and then afterwards can debate whether the data model reflects their understanding of the business or whether the measures on the data model reflect what is required in the business requirements. An application development team will all read the data model the same way and understand exactly what is being communicated, and afterwards can discuss the ideal way these structures should be implemented.
Without the data model, we rely more on conversations and requirements documents, both of which are traditionally ambiguous. Conversations and requirements documents are often essential inputs to the data model, however.
For example, “A Customer has Accounts” is typical of an ambiguous statement that might be made verbally or appear in print. Business analysts discussing this statement would need to invest valuable time first understanding exactly what is being communicated. Developers discussing this statement might make erroneous assumptions as to what a customer or account is, leading to a poor design choice. Read more »
For C++ programmers, maintaining legacy code has always been important. However, the last few upgrades to the specification have created what some experts have called “a whole new language.” So how do you start using it?
For your own projects, you may want to start using new features which improve your programs without breaking your old code. There are some excellent features that can be used this way.
1) Thousandth-Place Separator
Programs using big constants have always caused readability problems. For example, what number is this?
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1 |
long my_int = 10000000; |
Can you tell at a quick glance what this is? A million? Ten million? A hundred million?
The C++14 specification supports a new place-separator (‘) that makes the identity of the large constant much more obvious:
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1 2 |
// Set to ten million. long my_int = 10'000'000; |
Of course, anyone reading this in English would like to see commas used here instead, but the resulting syntax would be impossible. Consider this function call:
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1 |
process_big_nums(10,100,100); |
If a comma (,) were used as internal-place separator, would this statement call a function taking three arguments—10, 100, and 200—or would it take one argument equal to 10,100,200?
So the apostrophe (‘) works best. The nice thing is that you can start using it right away, even in old programs… old-fashioned literals such as “10000000” are still accepted as always, but for readability’s sake, should be revised whenever you can. Read more »
As we move rapidly into 2016, we take a retrospective look at 2015. It was an important year for Safari and our PubFactory platform. Strategically significant milestones for us as a company and the strength of our technology included:
