BDNW Issue - 26

Make Remote Work Effective for Data Science Teams

#26 - July 2, 2020 Curated news, articles on Big Data, FinTech, Blockchain, IoT, AI

Boosting Your Data Science Competency – COVID-19 Has a Silver LiningIT professionals, including data scientists and analysts, are no exception. Being out of work is certainly stressful, especially when there are bills to pay and food to buy, along with feelings of insecurity over their futures.What Is The Importance of Data Ethics?Data collection and analysis is inseparable from modern business. You’d be hard-pressed to find a medium or large-sized company that didn’t gather data these days. As customer information plays a more prominent role in industry, though, data ethics becomes a more pressing concern.Remote Work During Uncertain Times – How A Modern Intranet Can HelpWith many economies in total lock-downs due to the COVID-19 pandemic, organizations have been forced to implement a remote working policy across the globe. This shift, while may be critical to reduce the spread of the virus, has however drastically affected business continuity.Data Exploration and Data Preparation for Business Insightsin this article, we discuss best-practices and basics behind data exploration and preparation for business analysis.How to Make Remote Work Effective for Data Science TeamsWith the rapidly evolving global crisis surrounding COVID-19, forcing more and more companies to adopt strict work-from-home policies, remote work is further cementing itself as a workplace paradigm to be taken seriously.The Top Five Challenges of IoTIoT deployment is diversifying from consumer-based applications such as smart home devices and wearables to mission-critical applications in the areas of public safety, emergency response, industrial automation, autonomous vehicles and the Internet of Medical Things (IoMT).Is Big Data Analytics Killing Other Jobs or Creating Them?Big data analytics can provide a significant number of benefits for businesses who want their strategies and decisions to be backed up by cold, hard data. As a result, the market for big data analytics has grown rapidly over the past few years .P-values Explained By Data ScientistIn statistical hypothesis testing, the p-value or probability value is, for a given statistical model, the probability that, when the null hypothesis is true, the statistical summary (such as the absolute value of the sample mean difference between two compared groups) would be greater than or equal to the actual observed results.Demystifying Cloud ComputingPut simply, cloud computing is the process of moving computing resources (e.g. servers, databases, and software) from local to remote locations, and accessing these resources over the internet.Top 9 Artificial Intelligence Platforms for 2020As for data scientists and other software engineers that build AI projects, the one thing they can’t do without is an artificial intelligence framework. A long list of top AI platforms has been providing this service, and that includes some of the best machine learning and NLP application examples ever (think TensorFlow, Matlab, etc.)     Courses       Data science courses to jumpstart your future  Popular online courses for data science include introductions to data science, data science in R, Python, SQL, and other programming languages, basic data mining techniques, and the use of data science in machine learning applications.   Become an Azure expert using real-life case studies  With internet-based computing, exchange of information has been facilitated with universal access of the computing resources also allowing enterprises to store and process huge data in data centers provided by third-party.  .        For a detailed list of books covering Big data Data Science, Machine Learning, AI and associated programming languages check out our big data books page.  Want to reach our audience / fellow readers? Consider Sponsoring - grab a spot now.   Big Data | Hadoop News | AI | ML | NoSQL | Education | IoT | Cloud