Big Data, Cloud & DevOps

User Interface design (UI) or user interface engineering is deployed for machines and software, such as computers, home appliances, mobile devices, and other electronic devices, with the focus on maximizing and simplifying usability and the user experience. User Experience design (UX) dictates UI design. Today UX design has evolved not only because of the omnipresence of smart technology, but also because developed economies are increasingly focused on the service industry, where customer experience is crucial. In the future UI/UX will become the USP for most of the products sold across the globe.

AI has begun to impact nearly everything we do. The same technology that has made consumer internet search more personalised, connected, and ubiquitous is also starting to reveal itself in employee-facing search solutions, supporting enterprise search. Workers who depend on corporate search solutions often struggle to find relevant information in an ever-expanding pool of largely unstructured proprietary data. Companies can expect to see an increase in employee engagement, efficiency, and cost savings thanks to smarter search mechanisms, an embrace of open-source applications, and AI elevating virtually every aspect of data discovery. 

Agile data science research is hard, how can you give time estimation when you are not sure that your problem is solvable? How can you plan your sprint before looking at the data? You probably can’t. Agile data science requires many adjustments. In this post, I am going to share some of the best practices that work best for agile data science research. Every machine learning project should start by defining the goals of the project.

A vastly disproportionate number of hires are the result of referrals from employees who already work at a company. So your best way in, nine times out of ten, will be through a relationship with someone who works at your target company, rather than a generic channel, like a jobs board. Relationships are great because they give you a signal boost, but they also make it much more likely that you’ll get feedback on your application. But how do you build meaningful relationships with established data scientists? 

Open Source Software Foundations Everyone Should Know Open source computing is hugely important to software development. It is the model that everyone benefits from. The open source foundations that support this development play a crucial role. However, their work often goes unnoticed. I had no idea until I research this article that so many projects benefited

What steps are you taking to navigate your organization through one of the biggest business shifts ever? What are the company’s Digital Transformation goals and how will the transformation is successful? Are you considering the “humanscape” of the organization as changes are being integrated into the business? Skills need to be upfitted to adapt to

Do you need a graduate degree for data science?  Maybe so. Maybe not. I’ll level with you: I’m a PhD dropout. I’ve gotten a lot of mileage out of that title, by the way: it hints that I’ve done a lot of grad school, but still maintains the aura of badassery that only the word “dropout” can

Digital transformation and data protection; to some that may feel like a contradiction in terms, but in fact, the two can be interdependent. With digital transformation, there is a temptation. It’s the allure of just focusing on the deluge of information available and the potential for business advancement, if only one can successfully aggregate, interrogate

“There is more to a candidate than identifying if they know how to flatten a multi-dimensional array, what a prototype chain or closure is. Are they approachable and helpful to others? Can they leave pride at the door and do what’s best for the team? …” I’ve had discussions with many friends about a few of

Many organizations have grown comfortable with their business intelligence solution, and find it difficult to justify the need for advanced analytics. The advantages of advanced analytics are numerous and those advantages are based on the ability to further improve the business, increase user adoption (and therefore user empowerment and accountability) and, best of all, improve

We all know a friend who works in tech. And they are usually doing quite well for themselves, probably started coding since the beginning of time and often seem to be spoilt with career choices. Or are they? Here are some common myths about careers in tech and how they hold up against data. The