BDNW Issue - 15

#15 - Oct 23, 2019 Curated news, articles on Big Data,FinTech, Blockchain, IoT,AI

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Big Data LDN (London) is a free to attend conference and exhibition, hosting leading data and analytics experts, ready to arm you with the tools to deliver your most effective data-driven strategy.Hear from 150 expert speakers in 9 technical and business-led conference theatres, with real-world use-cases and panel debates, product launches & demos.Big Data LDN attendees have access to free on-site data consultancy and interactive evening community meetups. Register free today for Big Data LDN on 13-14th November 2019 and learn how to build a bright data-driven future for your business. 5 Data And Analytics Trends To Watch Out For In 2020The automation of over 40 percent of data science tasks is expected to happen by next year. Needless to say, the progress in machine learning technology and its expanding capabilities will be a catalyst to that event.Securing Your Data with AWSOne of the major benefits of cloud services, like AWS, is access to enterprise-level security. This does not mean, however, that you can simply move your database to the cloud and rest easy that it is 100% secure.5 Steps for Moving Big Data Workloads to the CloudThe cloud is a technology that can help you implement big data across your enterprise. However, as powerful as these technologies are, most organizations that attempt to combine them by moving their big data workloads to the cloud fail.How to Succeed with Big Data on AzureAs your business grows and the amount of data you’re amassing grows with it, you’ll likely begin considering a move to the cloud to meet your big data analytics needs. With significant offerings available from AWS, Azure, and Google, it can be hard to know which is best for you.Five Trends Shaping Fintech Into 2020Fintech has become a fast-moving field, and the next decade should be no different. Not every startup threatens small and midsize banks, but community banks and credit unions should stay on top of fintech trends to know when it’s time to act on a new opportunity.How to become a machine learning engineerWhen you stop to think about it, the future can be a little daunting. It’s filled with AI, automation, 3D printing, virtual reality, IoT, and other concepts that until now seemed like science fiction. But if you understand these ideas, it can also be a place filled with opportunities.Different types of NoSQL databases and when to use themThe popularity of NoSQL databases over the last decade or so has been driven by an explosion of data. Before what’s commonly described as ‘the big data revolution’, relational databases were the norm – these are databases that contain structured data.The future of IoT is at the EdgeAccording to a study from the International Data Corporation (IDC), 45 percent of all data created by IoT devices will be stored, processed, analysed and acted upon close to or at the edge of a network by 2020.Command Line Basics Every Data Scientist Should KnowIf you are a data scientist or learning data science and want to move beyond using jupyter notebooks to writing production-ready code, the chances are that you will need to use the command line for some tasksTensorFlow vs PyTorch vs Keras for NLPThese three deep learning frameworks are your go-to tools for NLP, so which is the best? Check out this comparative analysis based on the needs of NLP, and find out where things are headed in the future.5 Tips for Running Cassandra on AWSIn this article, we’ll look at the differences between Cassandra and AWS’ similar offering, DynamoDB, and cover some tips for ensuring that you can maximize the possible benefits if you decide to make the transition to the cloud.     Books       Big Data Science & Analytics: A Hands-On Approach  We are living in the dawn of what has been termed as the "Fourth Industrial Revolution", which is marked through the emergence of "cyber-physical systems" where software interfaces seamlessly over networks with physical systems, such as sensors, smartphones, vehicles, power grids or buildings, to create a new world of Internet of Things (IoT).   Programming Hive: Data Warehouse and Query Language for Hadoop   Need to move a relational database application to Hadoop? This comprehensive guide introduces you to Apache Hive, Hadoop’s data warehouse infrastructure. You’ll quickly learn how to use Hive’s SQL dialect—HiveQL—to summarize, query, and analyze large datasets stored in Hadoop’s distributed filesystem.          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