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Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics

BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.

In-Memory Analytics with Apache Arrow

Discover the power of in-memory data analytics with "In-Memory Analytics with Apache Arrow." This book delves into Apache Arrow's unique capabilities, enabling you to handle vast amounts of data efficiently and effectively. Learn how Arrow improves performance, offers seamless integration, and simplifies data analysis in diverse computing environments. What this Book will help me do Gain proficiency with the datastore facilities and data types defined by Apache Arrow. Master the Arrow Flight APIs to efficiently transfer data between systems. Learn to leverage in-memory processing advantages offered by Arrow for state-of-the-art analytics. Understand how Arrow interoperates with popular tools like Pandas, Parquet, and Spark. Develop and deploy high-performance data analysis pipelines with Apache Arrow. Author(s) Matthew Topol, the author of the book, is an experienced practitioner in data analytics and Apache Arrow technology. Having contributed to the development and implementation of Arrow-powered systems, he brings a wealth of knowledge to readers. His ability to delve deep into technical concepts while keeping explanations practical makes this book an excellent guide for learners of the subject. Who is it for? This book is ideal for professionals in the data domain including developers, data analysts, and data scientists aiming to enhance their data manipulation capabilities. Beginners with some familiarity with data analysis concepts will find it beneficial, as well as engineers designing analytics utilities. Programming examples accommodate users of C, Go, and Python, making it broadly accessible.

Microsoft Power BI Data Analyst Certification Guide

This book is your ultimate companion to mastering Microsoft Power BI and becoming proficient in data analysis and visualization. With a focus on understanding and utilizing Power BI to its fullest extent, this guide also prepares you comprehensively for the PL-300 certification exam. You will go from the basics to advanced techniques enabling you to confidently analyze and present data. What this Book will help me do Understand and connect to various data sources using Power BI. Gain skills in transforming and preparing data for advanced analysis. Develop expertise in designing and optimizing data models. Learn to create insightful reports and dashboards to convey information clearly. Prepare for and succeed in the PL-300 certification exam with practice questions. Author(s) Authors None Edenfield and None Corcoran bring extensive experience in business intelligence and data analytics to this book. They have years of hands-on expertise with Power BI and a passion for teaching analytics in a practical and accessible way. Together, they aim to empower readers to master Power BI and achieve their certification goals. Who is it for? This book is perfect for data analysts, business intelligence professionals, and anyone aiming to deepen their knowledge of Microsoft Power BI. Beginners will find approachable content to quickly get started while experienced users will find detailed topics to refine their expertise. By covering exam preparation and practical applications, this guide benefits a wide range of learners who wish to get certified and excel in data-centric roles.

AI-Powered Business Intelligence

Use business intelligence to power corporate growth, increase efficiency, and improve corporate decision making. With this practical book featuring hands-on examples in Power BI with basic Python and R code, you'll explore the most relevant AI use cases for BI, including improved forecasting, automated classification, and AI-powered recommendations. And you'll learn how to draw insights from unstructured data sources like text, document, and image files. Author Tobias Zwingmann helps BI professionals, business analysts, and data analytics understand high-impact areas of artificial intelligence. You'll learn how to leverage popular AI-as-a-service and AutoML platforms to ship enterprise-grade proofs of concept without the help of software engineers or data scientists. Learn how AI can generate business impact in BI environments Use AutoML for automated classification and improved forecasting Implement recommendation services to support decision-making Draw insights from text data at scale with NLP services Extract information from documents and images with computer vision services Build interactive user frontends for AI-powered dashboard prototypes Implement an end-to-end case study for building an AI-powered customer analytics dashboard

We talked about: 

Gloria’s background Working with MATLAB, R, C, Python, and SQL Working at ICE Job hunting after the bootcamp Data engineering vs Data science Using Docker Keeping track of job applications, employers and questions Challenges during the job search and transition Concerns over data privacy Challenges with salary negotiation The importance of career coaching and support Skills learned at Spiced Retrospective on Gloria’s transition to data and advice Top skills that helped Gloria get the job Thoughts on cloud platforms Thoughts on bootcamps and courses Spiced graduation project Standing out in a sea of applicants The cohorts at Spiced Conclusion

Links:

LinkedIn: https://www.linkedin.com/in/gloria-quiceno/ Github: https://github.com/gdq12

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html

Our events: https://datatalks.club/events.html

We in the West have watched Russia's invasion of Ukraine with disbelief and horror. How could this happen to a European country in the 21st century? Is there any justifiable rationale for the wanton destruction of people and property there? As we ponder these questions, our data colleagues in Ukraine have experienced the war firsthand.

To help us get a handle on Ukraine's role in the data economy and how teams based there are coping with Russia's military onslaught, Wayne interviews two software executives today who share how the war has affected their companies and how they are adapting to the evolving situation.

Dragos Georgescu is vice president and chief technology officer of DataClarity, an innovative data analytics vendor with a development shop in Lviv, Ukraine.

Bogdan Steblyanko is CEO of CHI Software, a software development company based in Ukraine with more than 500 employees spread across four development centers, including hard-hit Kharkiv in the east, which is the company's headquarters.

Artificial Intelligence with Power BI

Discover how to enhance your data analysis with 'Artificial Intelligence with Power BI,' a resource designed to teach you how to leverage Power BI's AI capabilities. You will learn practical methods for enriching your analytics with forecasting, anomaly detection, and machine learning, equipping you to create intelligent, insightful BI reports. What this Book will help me do Learn how to apply AI capabilities such as forecasting and anomaly detection to enrich your reports and drive actionable insights. Explore data preparation techniques optimized for AI, ensuring your datasets are structured for advanced analytics. Develop skills to integrate Azure Machine Learning and Cognitive Services into Power BI, expanding your analytical toolset. Understand how to build Q&A interfaces and integrate Natural Language Processing into your BI solutions. Gain expertise in training and deploying your own machine learning models to achieve tailored insights and predictive analytics. Author(s) None Diepeveen is an experienced data analyst and Power BI expert with a passion for making advanced analytics accessible to professionals. With years of hands-on experience working in the data analytics field, they deliver insights using intuitive, practical approaches through clear and engaging tutorials. Who is it for? This book is ideal for data analysts and BI developers who aim to expand their analytics capabilities with AI. Readers should already be familiar with Power BI and are looking for a resource to teach them how to incorporate predictive and advanced AI techniques into their reporting workflow. Whether you're seeking to gain a professional edge or enhance your organization's data storytelling and insights, this guide is perfect for you.

The Tableau Workshop

The Tableau Workshop offers a comprehensive, hands-on guide to mastering data visualization with Tableau. Through practical exercises and engaging examples, you will learn how to prepare, analyze, and visualize data to uncover valuable business insights. By completing this book, you will confidently understand the key concepts and tools needed to create impactful data-driven visual stories. What this Book will help me do Master the use of Tableau Desktop and Tableau Prep for data visualization tasks. Gain the ability to prepare and process data for effective analysis. Learn to choose and utilize the most appropriate chart types for different scenarios. Develop the skills to create interactive dashboards that engage stakeholders. Understand how to perform calculations to extract deeper insights from data. Author(s) Sumit Gupta, None Pinto, Shweta Savale, JC Gillet None, and None Cherven are experts in the field of data analytics and visualization. With diverse backgrounds in business intelligence and hands-on experience with industry tools like Tableau, they bring valuable insights to this book. Their collaborative effort offers practical, real-world knowledge tailored to help learners excel in Tableau and data visualization. With their passion for making technical concepts accessible, they guide readers step by step through their learning journey. Who is it for? This book is ideal for professionals, analysts, or students looking to delve into the world of data visualization with Tableau. Whether you're a complete beginner seeking foundational knowledge, or an intermediate user aiming to refine your skills, this book offers the practical insights you need. It's designed for those who want to master Tableau tools, explore meaningful data insights, and effectively communicate them through engaging dashboards and stories.

Bioinformatics and Medical Applications

BIOINFORMATICS AND MEDICAL APPLICATIONS The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms analyses massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. The book delivers various bioinformatics computational methods used to identify diseases at an early stage by assembling cutting-edge resources into a single collection designed to enlighten the reader on topics focusing on computer science, mathematics, and biology. In modern biology and medicine, bioinformatics is critical for data management. This book explains the bioinformatician’s important tools and examines how they are used to evaluate biological data and advance disease knowledge. The editors have curated a distinguished group of perceptive and concise chapters that presents the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to healthcare. Applying deep learning techniques for data-driven solutions in health information allows automated analysis whose method can be more advantageous in supporting the problems arising from medical and health-related information. Audience The primary audience for the book includes specialists, researchers, postgraduates, designers, experts, and engineers, who are occupied with biometric research and security-related issues.

Visualizing Google Cloud

Easy-to-follow visual walkthrough of every important part of the Google Cloud Platform The Google Cloud Platform incorporates dozens of specialized services that enable organizations to offload technological needs onto the cloud. From routine IT operations like storage to sophisticated new capabilities including artificial intelligence and machine learning, the Google Cloud Platform offers enterprises the opportunity to scale and grow efficiently. In Visualizing Google Cloud: Illustrated References for Cloud Engineers & Architects, Google Cloud expert Priyanka Vergadia delivers a fully illustrated, visual guide to matching the best Google Cloud Platform services to your own unique use cases. After a brief introduction to the major categories of cloud services offered by Google, the author offers approximately 100 solutions divided into eight categories of services included in Google Cloud Platform: Compute Storage Databases Data Analytics Data Science, Machine Learning and Artificial Intelligence Application Development and Modernization with Containers Networking Security You’ll find richly illustrated flowcharts and decision diagrams with straightforward explanations in each category, making it easy to adopt and adapt Google’s cloud services to your use cases. With coverage of the major categories of cloud models—including infrastructure-, containers-, platforms-, functions-, and serverless—and discussions of storage types, databases and Machine Learning choices, Visualizing Google Cloud: Illustrated References for Cloud Engineers & Architects is perfect for Every Google Cloud enthusiast, of course. It is for anyone who is planning a cloud migration or new cloud deployment. It is for anyone preparing for cloud certification, and for anyone looking to make the most of Google Cloud. It is for cloud solutions architects, IT decision-makers, and cloud data and ML engineers. In short, this book is for YOU.

Simplify Big Data Analytics with Amazon EMR

Simplify Big Data Analytics with Amazon EMR is a thorough guide to harnessing Amazon's EMR service for big data processing and analytics. From distributed computation pipelines to real-time streaming analytics, this book provides hands-on knowledge and actionable steps for implementing data solutions efficiently. What this Book will help me do Understand the architecture and key components of Amazon EMR and how to deploy it effectively. Learn to configure and manage distributed data processing pipelines using Amazon EMR. Implement security and data governance best practices within the Amazon EMR ecosystem. Master batch ETL and real-time analytics techniques using technologies like Apache Spark. Apply optimization and cost-saving strategies to scalable data solutions. Author(s) Sakti Mishra is a seasoned data professional with extensive expertise in deploying scalable analytics solutions on cloud platforms like AWS. With a background in big data technologies and a passion for teaching, Sakti ensures practical insights accompany every concept. Readers will find his approach thorough, hands-on, and highly informative. Who is it for? This book is perfect for data engineers, data scientists, and other professionals looking to leverage Amazon EMR for scalable analytics. If you are familiar with Python, Scala, or Java and have some exposure to Hadoop or AWS ecosystems, this book will empower you to design and implement robust data pipelines efficiently.

Data Analytics, Computational Statistics, and Operations Research for Engineers

This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements.

We talked about:

Juan Pablo's Backround Data engineering resources Teaching calculus Transitioning to Analytics Data Analytics bootcamp Getting money while studying Going to meetups to get a job Looking for uncrowded doors Using LinkedIn Portfolio Talking to people on meetups Eight tips to get your first analytics job Consider contracts and temporary roles Getting experience with non-profits Create your own internship Networking Website for hosting a portfolio I’m a math teacher. What should I learn first? Analytics engineering Best suggestion: keep showing up Networking on online conferences Communication skills and being organized

Links:

Website: https://www.thatjuanpablo.com/ Twitter: https://twitter.com/thatjuanpablo BROKE teacher to FAANG engineer Twitter thread: https://twitter.com/thatjuanpablo/status/1475806246317875203 LinkedIn: https://www.linkedin.com/in/thatjuanpablo/

Join DataTalks.Club: https://datatalks.club/slack.html

Our events: https://datatalks.club/events.html

Data Lakehouse in Action

"Data Lakehouse in Action" provides a comprehensive exploration of the Data Lakehouse architecture, a modern solution for scalable and effective large-scale analytics. This book guides you through understanding the principles and components of the architecture, and its implementation using cloud platforms like Azure. Learn the practical techniques for designing robust systems tailored to organizational needs and maturity. What this Book will help me do Understand the evolution and need for modern data architecture patterns like Data Lakehouse. Learn how to design systems for data ingestion, storage, processing, and serving in a Data Lakehouse. Develop best practices for data governance and security in the Data Lakehouse architecture. Discover various analytics workflows enabled by the Data Lakehouse, including real-time and batch approaches. Implement practical Data Lakehouse patterns on a cloud platform, and integrate them with macro-patterns such as Data Mesh. Author(s) Pradeep Menon is a seasoned data architect and engineer with extensive experience implementing data analytics solutions for leading companies. With a penchant for simplifying complex architectures, Pradeep has authored several technical publications and frequently shares his expertise at industry conferences. His hands-on approach and passion for teaching shine through in his practical guides. Who is it for? This book is ideal for data professionals including architects, engineers, and data strategists eager to enhance their knowledge in modern analytics platforms. If you have a basic understanding of data architecture and are curious about implementing systems governed by the Data Lakehouse paradigm, this book is for you. It bridges foundational concepts with advanced practices, making it suitable for learners aiming to contribute effectively to their organization's analytics efforts.

Welcome to the show notes! 🎉 I always put interesting things in the show notes, so make sure you check them every episode! 

In today's podcast episode, I'll be sharing a recording of a seminar I gave this week to about 50 undergraduate students, specifically in the chemical engineering program at the University of Utah.

I'll be talking about: 1) what I wish I knew while I was in college and trying to break into data science 2) how data science can be applied in industrial systems and engineering

Although this was given to a live audience, I do think a lot of the advice you might find applicable to you and your situation.

Want to come to my project analyzing Ken Jee's YouTube data? Register here: https://www.linkedin.com/video/event/urn:li:ugcPost:6899114723149705216/

If you want a free way to kickstart your analytics career, check out my free 33-page PDF giving you an introduction to everything you need to know: https://www.datacareerjumpstart.com/roadmap

If you’re just starting out, you can check out my 21 Day To Data Challenge: https://www.datacareerjumpstart.com/challenge

Want to learn data science while building your portfolio? Check out Data Career Jumpstart: https://www.datacareerjumpstart.com/data-career-jumpstart-course

MORE DATA ANALYTICS CONTENT HERE:

📺 Subscribe YouTube: https://www.youtube.com/c/AverySmithDataCareerJumpstart/videos

🎙Listen to My Podcast: https://podcasts.apple.com/us/podcast/data-career-podcast/id1547386535

👔 Connect with me on LinkedIn: https://www.linkedin.com/in/averyjsmith/

📸 Instagram: https://www.instagram.com/datacareerjumpstart/

👾Join My Discord: https://www.datacareerjumpstart.com/discord

🎵 TikTok: https://www.tiktok.com/@verydata? 

Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

In this episode, I’ll explain what THE best project you can do for data science and how you can accomplish it.

I’ll give you my 5 step recipe for making a great data science project so you can find a data analytics job.

If you need to find datasets, check out Kaggle.com and Google Dataset Search Engine

Want to build more projects for your portfolio? Check out my course, Data Career Jumpstart: https://www.datacareerjumpstart.com/data-career-jumpstart-course

✅ If you liked this video, please rate and review the podcast to help against the war against the algorithm 

If you want a free way to kickstart your analytics career, check out my free 33-page PDF giving you an introduction to everything you need to know: https://www.datacareerjumpstart.com/roadmap

If you’re just starting out, you can check out my 21 Day To Data Challenge: https://www.datacareerjumpstart.com/challenge

MORE DATA ANALYTICS CONTENT HERE:

📺 Subscribe YouTube: https://www.youtube.com/c/AverySmithDataCareerJumpstart/videos

🎙Listen to My Podcast: https://podcasts.apple.com/us/podcast/data-career-podcast/id1547386535

👔 Connect with me on LinkedIn: https://www.linkedin.com/in/averyjsmith/

📸 Instagram: https://www.instagram.com/datacareerjumpstart/

👾Join My Discord: https://www.datacareerjumpstart.com/discord

🎵 TikTok: https://www.tiktok.com/@verydata? 

Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

In this episode, I explain the importance of having data before starting a machine learning project by sharing a story of freelancing in data science

LAST DAY TO JOIN 21 DAYS TO DATA: https://www.datacareerjumpstart.com/challenge

If you want a free way to kickstart your analytics career, check out my free 33-page PDF giving you an introduction to everything you need to know: https://www.datacareerjumpstart.com/roadmap

Want to learn data science while building your portfolio? Check out Data Career Jumpstart: https://www.datacareerjumpstart.com/data-career-jumpstart-course

MORE DATA ANALYTICS CONTENT HERE:

📺 Subscribe YouTube: https://www.youtube.com/c/AverySmithDataCareerJumpstart/videos

🎙Listen to My Podcast: https://podcasts.apple.com/us/podcast/data-career-podcast/id1547386535

👔 Connect with me on LinkedIn: https://www.linkedin.com/in/averyjsmith/

📸 Instagram: https://www.instagram.com/datacareerjumpstart/

👾Join My Discord: https://www.datacareerjumpstart.com/discord

🎵 TikTok: https://www.tiktok.com/@verydata? 

Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

The advent of big data, self-service analytics, and cloud applications has created a need for new ways to manage data access. New data access governance tools promise to simplify and standardize data access and authorization across an enterprise. Data management expert, Sanjeev Mohan, provides an industry perspective on this emerging technology and what it means for data analytics teams.