To get the most out of this book, do not be afraid to do a little programming yourself. While we will stick to no-code tools in most cases, in certain areas it is simply easier to run a small Python or R script to ensure smooth operations. For example, we will be pulling data from HTTP REST APIs to build AI predictions into our dashboards. Or we will do some basic data processing in Python's pandas or R's Tidyverse. If you are open and willing to learn some of these practices, this book will give you everything you need to create a first version of an AI use case prototype on your own, without any hand-holding, thanks to ready-to-use code templates.

In this course, we are going to show you how to SUPERCHARGE your Power BI skills, and learn to create INTERACTIVE Dashboards and INCREDIBLE reports. Microsoft Power BI is the easiest to use reporting, data analysis, and interactive dashboard tool available today! Microsoft Power BI is available for free – all you need to do is sign up! There is no coding required! Power BI allows you to do that but it's not necessary.

Clearly there are some big AI and analytics trends for 2020. With so many new opportunities in analytics, how do organizations tap into not just trends, but the value those technologies can create for their companies and customers? As we head into the next decade, I believe the greatest value of analytics will come in the form of clear, fast decision-making, predictive trends, and ROI (which, again, will lead to better decisions). The following are a few trends that can help grow and improve your company this year. An Excel document--flat numbers on a page--won't cut it in 2020, no matter how great your Excel skills are.

You will learn about features in Power BI, R, Analytics, and AI in less than three minutes in every video.

With Hands-On Machine Learning for Algorithmic Trading, create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions. Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics. With Hands-On Blockchain with Hyperledger, write your own chaincode/smart contracts using Golang on hyperledger network. With Mastering Blockchain – Second Edition, build powerful applications using Ethereum to secure transactions and create smart contracts. Explore cryptography, mine cryptocurrencies, and solve scalability issues with this comprehensive guide.

It's not surprising that many of Microsoft's own services are built on Azure, but increasingly Microsoft is also offering Azure services as a way for customers to extend and customise products. When you use dataflows to extract, clean and transform data that you're loading into Power BI, that data is stored in Azure Data Lake. You could also use it in Azure Databricks or for analytics through Azure SQL Data Warehouse, which you can do through the Azure portal, or make interactive using the Power BI Desktop app. The automated machine learning in Power BI is the AutoML feature from Azure Machine Learning, which looks at what you're trying to predict and what data you have available, and iterates through multiple machine-learning algorithms to discover which gets the best score. Or you can take advantage of Azure Cognitive Services to analyse the data in images and text, or build your own machine-learning models and run them.

The data scientist remains one of the most in-demand jobs, and there are a growing number of data science programs across the country to teach techies the necessary skills. But by the time you gain the skills you need, the job and the data science tools may look much different than they do today. Data scientist skills vary depending on the company, but they generally involve the ability to identify business needs and formulate problem statements based on business requirements. They can prepare the right data for analysis to help meet business needs and assist company leaders to help make decisions, according to Adrian Bowles, industry analyst and founder of Storm Insights, in a Dataversity webinar called "The Disappearing Data Scientist." "They can find the right tools, find the right approach to the data, analyze it in a way that makes sense and interpret that," Bowles said in the webinar.

Adobe and Microsoft have joined forces, combining Adobe's Sensei artificial intelligence (AI) with Microsoft's data to give Adobe customers more automated, intelligence-based business feedback. By plugging into Microsoft's ecosystem, Adobe can pull rich insights from Microsoft's customer relationship management (CRM) and data visualization tools, among other platforms. Adobe Sensei is now armed with a new trove of data from Microsoft Dynamics 365, Microsoft Power BI, and Microsoft Azure, from which it can draw on its algorithm-based recommendations. Both companies are also working to add Adobe Sensei to Microsoft tools; however, there is no timeline for when this reverse integration will be available. Here's an excellent example of how Adobe Sensei and Microsoft work together today: A financial services client working within Adobe Analytics can take existing Adobe data, combine it with Microsoft's data ecosystem, and then feed all of that information into Sensei.

With improvements in cloud technology spreading like wildfire, small businesses are in a position where they can take advantage of these advancements. They can leverage tools that will help them run their business more effectively from anywhere at anytime, gain real-time insights into their performance and streamline their selling and customer service initiatives. Considering almost half of small businesses don't have a website, maybe not all businesses are utilizing the wealth of smart technologies at their disposal. Here are three to get you started. For small business owners, being awake used to be the prerequisite for making money.