Big Data, Cloud & DevOps

Shadow IT + Digital Certificates = Ticking Timebomb When your employees use software or hardware at work that your IT or security team is unaware of – that’s Shadow IT. Calling the use of these tools “unsanctioned” might be a bit strong, but either way, employees have neglected to go through the proper channels and

While it is true you can easily “containerize” nearly any software quite quickly, this alone will not realize the benefits of an effective container deployment. Those who are serious about containers will do well to learn from others. This blog enumerates nine pillars of best practices for containers. Container Best Practices Leaders explain why containers are

When you run a business, maintaining compliance with all governmental rules and regulations including taxation, worker safety, and environmental measures is key to ongoing viability. Failure to maintain compliance can result in costly lawsuits, penalties and even the closure of your doors. How can busy leaders ensure their teams remain abreast of all necessary compliance

Cyber resilience must not be used to legitimise window-dressing practices around cyber security Although the theme is gaining momentum, there is a certain amount of confusion around what cyber resilience really means for organisations. For many, it is just another piece of consultant jargon: An abstract managerial concept with little real-life substance or meaning. As

The vast majority of data science job descriptions do not convey the actual requirements of the position they’re advertising. When senior data scientists are called upon to recruit, their first move is often to throw away the job posting altogether. A misleading job description means that recruiters get a ton of irrelevant applications, and that candidates waste a ton of time applying to irrelevant positions. But there’s another problem: job descriptions are the training labels that any good aspiring data scientist will use to prioritize their personal and technical skills development.

Competence refers to having sufficient skill, knowledge, and experience to perform the job, i.e. being properly qualified. The common set of skills that are required to be a Chief Data Executive include knowledge of the business and mission, knowledge of computer science, data science, or both, and knowledge of product definition and delivery. A competent Chief Data Executive is a rare mix of technical guru, businessperson, marketer, and adept executive leader — someone able to communicate in all spheres and that can easily translate between each.

Nuances exist within the different Data Science Career Levels. For instance, some rather look for strong engineering than math skills in Junior Data Scientists. Some Senior Data Scientists might discover their passion for building scalable data pipelines and transition to a Data Engineering role. Some Principal Data Scientists prefer to develop technical expertise while others rejoice in focusing on business skills. Whatever career path you take, developing your skills around the three main areas of Data Science expertise will get you far.

These days, ‘quantum’ is a byword for where we are going, although the technology is still in its genesis. To understand quantum computers and what — if our minds and design applications get to grips with them — they can do for us is mindblowing. Quantum theory is for many a subject so difficult to understand, so sheathed in intellectual rhetoric that it frightens the life out of many if only because of its sheer incomprehensibility.  A quantum race could very much be on the cards.

The popularity of open source continues to rise exponentially. Demand for JavaScript, for example, is huge. However, popularity does not infer less vulnerability. The percentage of vulnerable Java components downloaded has increased substantially over the past four years. The rise in overall open source-related breaches should be seen against the background of the massive growth in the use of open source components.  It appears that some open source component users are oblivious to all advice and warnings. 

Your enterprise must take to ensure security, governance, and compliance over the content and communications that take place through your enterprise collaboration tools. The good news is that this work takes place at one level, and what comes from that work can become a set of standard policies to govern team-level collaboration sites. It’s essential to create corporate policies and training for teams that may be opening their collaboration sites to external parties.

How do you know when you have achieved DevOps? and you are likely to get different answers. A practical answer to how do you know when you have DevOps depends on having a definition. While defining DevOps itself has been elusive, an enterprise definition is needed for alignment and progress measurement. Considering that DevOps needs continuous flow to accomplish business goals, it can be said you have DevOps when you have implemented continuous flow for at least one model application.