Full Stack Big Data

The data science and analytics job market is growing rapidly. What's more, after a year of wages staying comparatively flat, data science and analytics experts can look forward to rises in 2019. That's according to a series of 2019 predictions from quantitative recruitment specialist firm BurtchWorks' managing director, Linda Burtch. If your organization plans to recruit these professionals in 2019, or if you are a data scientist looking to make some career moves this year, these predictions offer some useful insight about what you can assume in the year ahead. What's driving some of the changes? How can you leverage these opportunities? There are several forces in play right now, Burtch told InformationWeek in an interview. Organizations across almost all industries have recognized that analytics can make them more intelligent and more profitable. Career-focused young people are taking degrees to prepare themselves for such jobs. That has extended the talent

With humans and machines joining forces more than ever before, AI is no longer restricted to innovation labs and is being hailed for its immense transformational possibilities. Though, organizations need to overcome particular challenges before they can realize the real potential of this evolving technology. The key lies in leveraging the right prospects in AI. Provability Companies involved in AI cannot validate clearly why it does and what it does. No matter AI is a "black box." People are uncertain about it, as they fail to comprehend how it makes decisions. Provability – the level of mathematical cert behind AI predictions – remains a grey area for enterprises. There’s no way they can guarantee that the intellect behind the AI system’s decision-making is clear. The solution lies in making AI explicable, provable, and transparent. Businesses must embrace Explainable AI as a best practice. Data privacy and security Most AI applications depend on massive volum

The newfound passion for data science in the present computing world isn’t baseless. Rated as the top job on offer by Harvard Business Review along with lucrative paychecks, the lacunae in the current skills of experts compared to the industry standard skill-set necessary for the position of a data scientist means there is very much already that comes with learning data science. In such a setting, what gives you a competitive edge? Here are a few steps to follow on your path to becoming a data scientist! 1. Develop Skills in Statistics, Mathematics, and ML A data scientist is someone who is better at mathematics and statistics than any software engineer and also better at software engineering than any statistician. You just need to have the right balance of all these, to ensure you’re set up well to develop your data science skills. 2. Learn to Love (Big) Data Data Scientists have to handle a massive amount of structured and unstructured data on which computations

Artificial intelligence (AI) has now become an integral part of our lives. It’s how Amazon suggests products, Google answers our searches, and Pandora plays another song. AI allows scalable growth, and personalizes customer experiences for marketers. AI is a powerful marketing strategy as it allows marketers to outdo themselves in their roles by interacting with their customers through targeted messaging — all at scale. Here are the five ways AI can assist sales and marketing in finding leads. 1. Support Sales with Appropriate Customer Experiences Customers now expect personalized experiences and interactions through their favorite channel. AI-driven predictive content tools are allowing marketers to be more tactical, while reducing the workload.  These AI-driven marketing programs can examine your website for case studies, white papers, blogs, articles, videos, eBooks, etc. Once the content gathered, AI foresees what will appeal and ultimately convert each audience