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Free Download Udemy - GCP Data Engineering-End to End Project-Healthcare Domain Published: 4/2025 Created by: Saidhul Shaik MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 10 Lectures ( 7h 47m ) | Size: 3.51 GB Industry Standard Project in Healthcare Domain using GCP services like GCS, BigQuery, Dataproc, Composer, GitHub, CICD What you'll learn Understand the End to End Data Engineering Project Design and Implement Scalable ETL Pipelines for Healthcare Data Implement Key Techniques like Incremental Data, SCD2, Metadata driven approach, Medallion Arch, Error Handling, CDM , CICD & Many more.. Develop and Deploy Data Solutions with CI/CD Practices Requirements Basic Knowledge on Python and SQL Description This project focuses on building a data lake in Google Cloud Platform (GCP) for Revenue Cycle Management (RCM) in the healthcare domain. The goal is to centralize, clean, and transform data from multiple sources, enabling healthcare providers and insurance companies to streamline billing, claims processing, and revenue tracking.GCP Services Used:Google Cloud Storage (GCS): Stores raw and processed data files.BigQuery: Serves as the analytical engine for storing and querying structured data.Dataproc: Used for large-scale data processing with Apache Spark.Cloud Composer (Apache Airflow): Automates ETL pipelines and workflow orchestration.Cloud SQL (MySQL): Stores transactional Electronic Medical Records (EMR) data.GitHub & Cloud Build: Enables version control and CI/CD implementation.CICD (Continuous Integration & Continuous Deployment): Automates deployment pipelines for data processing and ETL workflows.Techniques involved : Metadata Driven ApproachSCD type 2 implementationCDM(Common Data Model)Medallion ArchitectureLogging and MonitoringError HandlingOptimizationsCICD implementationmany more best practicesData SourcesEMR (Electronic Medical Records) data from two hospitalsClaims filesCPT (Current Procedural Terminology) CodeNPI (National Provider Identifier) DataExpected OutcomesEfficient Data Pipeline: Automating the ingestion and transformation of RCM data.Structured Data Warehouse: gold tables in BigQuery for analytical queries.KPI Dashboards: Insights into revenue collection, claims processing efficiency, and financial trends. Who this course is for Aspiring Data Engineers, Data Professionals Homepage: https://www.udemy.com/course/gcp-data-engineering-end-to-end-project-healthcare-domain/ [b]AusFile[/b] https://ausfile.com/esj36caecj9j/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part1.rar.html https://ausfile.com/imabxlnc65ax/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part2.rar.html https://ausfile.com/2325s97rzcd9/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part3.rar.html https://ausfile.com/wamb9xrsf42t/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part4.rar.html Rapidgator https://rg.to/file/862792cb3adf5bec6b799e69f9a5d642/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part1.rar.html https://rg.to/file/7ec74bbc461616f914280ff43302e6b7/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part2.rar.html https://rg.to/file/a17f6cc8a93b962a7ac831f1659a65dc/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part3.rar.html https://rg.to/file/9d2c09112f0d44d6c0ddb22f4057bb13/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part4.rar.html Fikper Free Download https://fikper.com/fkUXO1QW8R/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part1.rar.html https://fikper.com/dfwulFzfkj/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part2.rar.html https://fikper.com/3W6Oxt9wFx/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part3.rar.html https://fikper.com/tzqaWKnTxr/uhtbk.GCP.Data.EngineeringEnd.to.End.ProjectHealthcare.Domain.part4.rar.html No Password - Links are Interchangeable

Free Download Udemy - Excel Data Analysis Mastery Practical Step-By-Step Guide Published: 4/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 4.93 GB | Duration: 6h 12m Practical hands-on, step-by-step Excel data analysis lessons designed to boost your career and skill set - No experience What you'll learn Navigate Microsoft Excel like a pro, understanding key components of the interface and mastering efficient data entry. Import data from the web and other sources directly into Excel for analysis and reporting. Clean and format messy datasets using tools like Flash Fill, Conditional Formatting, and Data Validation to ensure accuracy and consistency. Write and apply essential Excel formulas and functions-both basic and advanced-to perform complex calculations with ease. Create professional charts and graphs, including XY charts and histograms, to visualize trends and make your data speak. Sort, filter, and summarize large datasets to uncover insights quickly using Excel's built-in tools. Build and customize PivotTables and use slicers and timelines to create interactive data summaries. Perform statistical analysis in Excel, including calculating descriptive statistics, correlations, and frequency distributions. Use What-If Analysis tools to forecast outcomes and make data-driven decisions. Troubleshoot and fix common Excel errors, boosting your accuracy and confidence in working with large data sets. Requirements Basic Computer Skills Access to Microsoft Excel A Reliable Internet Connection Willingness to Learn by Doing A PC or Mac with Excel Installed Optional: A Notebook or Digital Notes App Description Excel Data Analysis Mastery: A Practical, Step-by-Step Guide with Hands-On ProjectsPractical hands-on, step-by-step Excel data analysis lessons designed to boost your career and skill set - No experienceThis course is designed to help you explore Excel by doing. You'll build essential data analysis skills step by step and have the opportunity to apply what you learn through guided, hands-on projects.Why This Course Was CreatedMany learners feel overwhelmed when using Excel for data analysis. Common challenges include:Navigating Excel's many tools and functionsStruggling to organize or clean messy spreadsheetsFeeling stuck when it comes to making sense of dataFinding it hard to stay motivated with random or disconnected tutorialsThis course offers a structured, beginner-friendly path to help you build confidence and start using Excel more effectively.How This Course Is DifferentRather than just focusing on theory or memorizing formulas, this course emphasizes practical application. Every lesson is followed by a mini-project to help reinforce your learning and show how each concept works in real scenarios. Hands-On LearningAfter each lesson, you'll complete a small project using real data-giving you the chance to practice skills in context. Step-by-Step SupportAll activities are broken down into clear, manageable steps to help you stay on track and make steady progress. Relevant ExamplesLessons are built around situations similar to those learners may encounter in work, school, or personal projects. Beginner-Friendly StructureNo prior Excel experience? No problem. We keep things simple, clear, and focused on practical use.What You'll ExploreYou'll cover essential Excel data analysis topics, including:Importing and organizing data from various sourcesCleaning and preparing spreadsheets for analysisCreating charts and graphs to visualize dataUsing functions and formulas to solve problemsExploring PivotTables, slicers, and timelinesApplying What-If analysis and conditional formattingManaging data validation, formatting, and print setupEach topic is paired with a hands-on project to help reinforce the lesson.Who this course is for This course is ideal for:Beginners who want a structured introduction to ExcelStudents learning to work with data more effectivelyProfessionals looking to use Excel more confidently in daily tasksBusiness users managing spreadsheets and reportsAnyone interested in learning Excel through practiceWhat's Included Lifetime access to the course Certificate of completion Downloadable resources, templates, and practice files Instructor support through the Q&A section Replay lessons anytime, at your own paceBuild Skills Step-by-StepWith our "Learn, Apply, Repeat" approach, you'll develop a deeper understanding of Excel and gain practical experience along the way.Whether you're just starting or refreshing your skills, this course offers a supportive, hands-on path to learning Excel for data analysis.[Enroll Now] - Start building your Excel skills today, one step at a time. .this course is designed for you. 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Free Download Udemy - Data Science Mastery - Journey into Machine Learning Last updated: 4/2025 Created by: Tech Career World MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English + subtitle | Duration: 530 Lectures ( 49h 5m ) | Size: 15.6 GB Learn Machine Learning, Data Science and Deep Learning with Python What you'll learn Gain proficiency in using Python libraries commonly used in data science and machine learning, such as NumPy, Pandas, and Matplotlib. Learn how to clean and preprocess datasets, including handling missing data, outliers, and feature scaling. Acquire knowledge of exploratory data analysis techniques to extract insights and patterns from data. Master the fundamentals of statistical analysis and apply statistical methods to interpret and draw conclusions from data. Understand the principles of machine learning and its various algorithms, such as regression, classification, and clustering. Learn how to select appropriate machine learning models and techniques for different types of problems and datasets. Develop skills in feature engineering and selection to enhance the performance of machine learning models. Requirements Just passion for learning! Description The Python for Data Science and Machine Learning course is designed to equip learners with a comprehensive understanding of Python programming, data science techniques, and machine learning algorithms. Whether you are a beginner looking to enter the field or a seasoned professional seeking to expand your skillset, this course provides the knowledge and practical experience necessary to excel in the rapidly growing field of data science.Course Objectives:1. Master Python Programming: Develop a strong foundation in Python programming, including syntax, data structures, control flow, and functions. Gain proficiency in using Python libraries such as NumPy, Pandas, and Matplotlib to manipulate and visualize data effectively.2. Data Cleaning and Preprocessing: Learn how to handle missing data, outliers, and inconsistent data formats. Acquire skills in data cleaning and preprocessing techniques to ensure the quality and reliability of datasets.3. Exploratory Data Analysis: Understand the principles and techniques of exploratory data analysis. Learn how to extract insights, discover patterns, and visualize data using statistical methods and Python libraries.4. Statistical Analysis: Gain a solid understanding of statistical concepts and techniques. Apply statistical methods to analyze data, test hypotheses, and draw meaningful conclusions.5. Machine Learning Fundamentals: Learn the foundations of machine learning, including supervised and unsupervised learning, regression, classification, and clustering. Understand the strengths and limitations of different machine learning algorithms.6. Machine Learning Implementation: Gain hands-on experience in implementing machine learning models using Python libraries such as scikit-learn. Learn how to train, evaluate, and optimize machine learning models.7. Feature Engineering and Selection: Develop skills in feature engineering to create meaningful and informative features from raw data. Learn techniques for feature selection to improve model performance and interpretability.8. Model Evaluation and Optimization: Learn how to assess the performance of machine learning models using techniques like cross-validation and evaluation metrics. Understand the importance of hyperparameter tuning and regularization for model optimization.9. Deep Learning Concepts: Explore the basics of deep learning, including neural networks, activation functions, and gradient descent optimization. Gain an understanding of deep learning architectures and their applications.10. Practical Deep Learning: Acquire practical experience in building and training neural networks using popular deep learning frameworks such as TensorFlow or PyTorch. Learn how to apply deep learning techniques to solve real-world problems. Who this course is for Aspiring data scientists and machine learning enthusiasts who have a basic understanding of Python programming. Learners who want to acquire comprehensive knowledge and practical skills in Python, data science, and machine learning. The course content is tailored to provide valuable insights and hands-on experience to individuals aiming to excel in data-driven problem-solving and analysis. 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Free Download Linkedin - Introduction to Modern Data Engineering with Snowflake Released: 04/2025 Duration: 3h | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 454 MB Level: Beginner | Genre: eLearning | Language: English In this technical, hands-on course, learn how to build and orchestrate modern data pipelines with Snowflake. The course focuses on practical concepts and tools to get you up and running quickly. Learn how to build and maintain data pipelines in Snowflake, including data ingestion, transformation, delivery, and orchestration. Throughout the course, follow along with the instructor using a combination of Snowflake, Visual Studio Code, GitHub, the command line, and more. The course is supplemented with readings containing plenty of resources to level up your understanding of specific concepts. Homepage: https://www.linkedin.com/learning/introduction-to-modern-data-engineering-with-snowflake [b]AusFile[/b] https://ausfile.com/lnentne8cem4/tbdzf.Linkedin..Introduction.to.Modern.Data.Engineering.with.Snowflake.rar.html Fileaxa https://fileaxa.com/d07bsatoxg3l/tbdzf.Linkedin..Introduction.to.Modern.Data.Engineering.with.Snowflake.rar TakeFile https://takefile.link/5z6ph302panj/tbdzf.Linkedin..Introduction.to.Modern.Data.Engineering.with.Snowflake.rar.html Rapidgator http://peeplink.in/a9ea7870953b Fikper Free Download https://fikper.com/dkbc0mfHdD/tbdzf.Linkedin..Introduction.to.Modern.Data.Engineering.with.Snowflake.rar.html No Password - Links are Interchangeable

Free Download Udemy - Snowflake Master Class for Data Engineers-AWS-Zero to Expert Published 4/2025 Created by Sujith Nair MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Intermediate | Genre: eLearning | Language: English | Duration: 250 Lectures ( 17h 46m ) | Size: 7 GB 18 hours of action packed Snowflake Data Engineering content including Hybrid tables, Iceberg tables and Dynamic Tables. What you'll learn Learn how to load Data into Snowflake Learn how to Mask Data in Snowflake Learn how to Time Travel in Snowflake Learn how to Clone Data in Snowflake Learn Hybrid Tables, Dynamic Tables, Event Tables and Iceberg Tables Requirements Basic SQL Basic AWS (s3) Description Elevate your data engineering and cloud analytics skills with this comprehensive Snowflake Master Class, specifically tailored for professionals leveraging Amazon Web Services (AWS). This intensive course delves deep into the intricacies of the Snowflake Data Cloud, equipping you with the practical knowledge and hands-on experience to design, build, optimize, and manage robust data solutions on AWS.Starting with a foundational understanding of Snowflake's unique architecture and its seamless integration with the AWS ecosystem, you will progress through critical data engineering workflows. Learn to efficiently ingest diverse data sources, including structured and semi-structured formats, utilizing powerful tools like Snowpipe for continuous data loading. Master automation techniques with Snowflake Tasks and track data changes effectively with Streams.Explore Snowflake's innovative features for data management and resilience, including Time Travel and Fail-Safe, and gain a thorough understanding of various Snowflake table types and their optimal use cases. Discover the power of Zero-Copy Cloning for agile development and testing.Crucially, you will learn how to secure your Snowflake environment with granular Roles and Access Controls and implement Dynamic Data Masking for sensitive information. Understand the principles and practicalities of secure Data Sharing both within and outside your organization.The course further explores advanced topics such as optimizing query performance and managing costs effectively using Materialized Views and various tuning strategies. You will also learn techniques for Data Sampling and how to integrate with external data sources via External Tables. Finally, we will explore the exciting new capabilities of Dynamic Tables, Event Tables, Hybrid Tables, and Iceberg Tables, preparing you for the future of data management in Snowflake.This Master Class culminates with a dedicated module focused on preparing you for Snowflake Data Engineer interviews, covering key concepts and practical scenarios. By the end of this course, you will possess the expertise to architect and implement sophisticated, scalable, and cost-efficient data solutions using Snowflake on AWS.Course Topics:Introduction to Snowflake: Overview of the Snowflake Data Cloud, its value proposition, and integration with AWS services.Getting Started with Snowflake on AWS: Account setup, connecting via Snowsight and other clients, navigating the Snowflake interface.Snowflake Architecture: Understanding Snowflake's unique multi-cluster shared data architecture, virtual warehouses, and cloud services layer.Storage Integration with AWS S3: Configuring and managing external stages for seamless data access and loading from AWS S3.Loading Data to Snowflake: Best practices and techniques for bulk loading structured data using COPY INTO statements.Loading Semi-Structured Data to Snowflake: Efficiently loading and querying JSON, Avro, Parquet, and other semi-structured data formats.Snowpipe: Implementing continuous data ingestion pipelines for real-time and near real-time data loading.Tasks: Automating data processing workflows, scheduling SQL statements, and managing dependencies.Streams: Tracking data changes in tables for efficient ETL/ELT processes and incremental updates.Time Travel & Fail-Safe: Understanding and utilizing Snowflake's data recovery and historical data access features.Snowflake Table Types: Deep dive into Permanent, Transient, and Temporary tables and their use cases.Zero Copy Cloning: Leveraging instant, zero-cost cloning for development, testing, and disaster recovery.Roles and Access Controls: Implementing robust security models using Snowflake's role-based access control (RBAC) framework.Dynamic Data Masking: Protecting sensitive data with dynamic masking policies based on user roles.Data Sharing: Securely sharing data with internal and external stakeholders without copying or moving data.Materialized Views: Optimizing query performance by creating and managing materialized views.Performance Tuning and Cost Optimization: Strategies for analyzing query performance, optimizing SQL, and managing warehouse costs.Data Sampling: Techniques for extracting representative subsets of data for analysis and testing.External Tables: Querying data directly from external storage locations like AWS S3 without loading.Dynamic Tables: Understanding and implementing declarative data transformation pipelines with automatic refresh.Event Tables: Capturing and analyzing event data within Snowflake.Hybrid Tables: Exploring the capabilities and use cases of Snowflake's Hybrid Tables.Iceberg Tables: Working with Iceberg tables in Snowflake for enhanced data lake functionality.Snowflake Data Engineer Interview : Snowflake interview for those who are trying to get a Snowflake job and want to know what a Snowflake interview sounds like. Who this course is for Entry Level Developers or Fresher who has basic knowledge of SQL and AWS s3 Experience Cloud Data Developer with experience on non-Snowflake Databases like Redshift or Azure Synapsis Experienced Snowflake Developer who is looking to expand Snowflake Knowledge Recently added to a project that has Snowflake and you want to learn it to get ready to be able to work there Experienced on-prem data engineer who is looking to transition to the cloud Homepage https://www.udemy.com/course/snowflake-master-class-for-data-engineers-aws-zero-to-expert/ [b]AusFile[/b] https://ausfile.com/ql11uj4xkdvb/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part1.rar.html https://ausfile.com/ouc5ghyru03q/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part2.rar.html https://ausfile.com/zy37lqlanfxu/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part3.rar.html https://ausfile.com/60tfml6hjkst/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part4.rar.html https://ausfile.com/mosqxxeurrvt/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part5.rar.html https://ausfile.com/pq0dce3z6s8n/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part6.rar.html https://ausfile.com/pp2xr3ljzvlj/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part7.rar.html https://ausfile.com/biak5ikopq32/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part8.rar.html Rapidgator https://rg.to/file/47a79f02373299c58d1ab8cc0269cf84/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part1.rar.html https://rg.to/file/083d1d4619eb9e239e898a1b330a8160/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part2.rar.html https://rg.to/file/fa6a9666d209c13360e60782578c4d67/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part3.rar.html https://rg.to/file/35375b763e4d95348dcf57dbcb31fcb1/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part4.rar.html https://rg.to/file/2717baf4399c05a220b26a973bf850fd/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part5.rar.html https://rg.to/file/240365edd5e029bb9a230b0a53f6c038/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part6.rar.html https://rg.to/file/3b2c3b1842d202520ec3f107272644dc/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part7.rar.html https://rg.to/file/7895dcde15d6c270b7f2d8bf4bfa673d/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part8.rar.html Fikper Free Download https://fikper.com/WbcwOeZOjp/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part1.rar.html https://fikper.com/fldRaFSHOC/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part2.rar.html https://fikper.com/niYjABAbl8/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part3.rar.html https://fikper.com/OlGyMVLWIv/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part4.rar.html https://fikper.com/pxSBbdxOVY/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part5.rar.html https://fikper.com/4J0XRQ6FcG/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part6.rar.html https://fikper.com/WoP6vFgdDl/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part7.rar.html https://fikper.com/JnfDjkSRCg/enzcs.Snowflake.Master.Class.for.Data.EngineersAWSZero.to.Expert.part8.rar.html No Password - Links are Interchangeable

Free Download Udemy - How To Tell A Story With Data Last updated 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 530.04 MB | Duration: 1h 49m Learn how to pique and keep your audience's attention so they will understand and remember your data presentation. What you'll learn Give better spoken and written presentations about data! Have an arsenal of strategies for creating memorable data stories. Know and apply the "5-stage arc" for memorable data storytelling. Requirements An interest in improving data presentations. Description Welcome to the course "How to Tell a Story with Data". If you've ever had to explain complex data to others or if you're interested in improving how you talk about data, this course is perfect for you.Data are everywhere. Data are used by businesses to make decisions, by governments to create policies, and by researchers to understand the world around us. But data can be hard to understand -- and even harder to explain to others.This is why being able to explain data in a simple, easy-to-understand way is so important. This skill is called data storytelling. This course will help improve your skills at data storytelling.In this course, you will learn how to keep your audience interested, whether they're in front of you or reading your words on a page. You'll learn tips and tricks on how to explain the main points of your data graphs in a way that's easy to understand and remember.But why learn data storytelling?We live in a world full of data. Businesses, governments, and researchers use data to make important decisions. But understanding this data can be hard. This is where data storytelling comes in.Data storytelling helps us understand and remember data. It's a skill that's becoming more and more important as we use more data in our everyday lives. This course will help you improve your data storytelling skills.So, what will you get from this course?Simply put, this course will give you a framework that you can use to make your data exciting and memorable to your audience. You'll also get lots of tips on how to make and present data graphics. This course is designed to help you become a better, more confident data storyteller. So, if you're ready to learn, I'm ready to help :) Anyone from student to professional who wants to improve their data-storytelling skills. Homepage https://www.udemy.com/course/tell-a-story-with-data/ [b]AusFile[/b] https://ausfile.com/htxan39isiex/qybbn.How.To.Tell.A.Story.With.Data.rar.html Rapidgator https://rg.to/file/8a708bb8c135dfa17d86625d8087b189/qybbn.How.To.Tell.A.Story.With.Data.rar.html Fikper Free Download https://fikper.com/5McMddqPv0/qybbn.How.To.Tell.A.Story.With.Data.rar.html No Password - Links are Interchangeable

Free Download Pluralsight - Scalable Data Processing with Python Released 4/2025 By Yasir Khan MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 55m | Size: 135 MB Learn to process large-scale data efficiently with Python. This course will teach you to leverage PySpark and Dask for scalable, parallel, and distributed data processing, and to optimize performance and handle real-world scaling challenges. Scalable data processing is essential for handling large datasets efficiently, yet many struggle with optimizing performance. In this course, Scalable Data Processing with Python, you'll gain the ability to process and manage large-scale data using PySpark and Dask. First, you'll explore the fundamentals of scalability, including parallel, distributed, and batch processing. Next, you'll discover how to use PySpark to process massive datasets with transformations, caching, and optimizations. Finally, you'll learn how to leverage Dask for parallel computation, optimizing execution with task graphs and lazy evaluation. When you're finished with this course, you'll have the skills and knowledge to efficiently process large datasets and handle performance challenges in scalable data processing. Homepage https://app.pluralsight.com/library/courses/python-scalable-data-processing/table-of-contents [b]AusFile[/b] https://ausfile.com/fkadspr3rrbv/rajho.Pluralsight..Scalable.Data.Processing.with.Python.rar.html Fileaxa https://fileaxa.com/kt03z6s4ns4a/rajho.Pluralsight..Scalable.Data.Processing.with.Python.rar TakeFile https://takefile.link/ucp3kp7unxod/rajho.Pluralsight..Scalable.Data.Processing.with.Python.rar.html Rapidgator http://peeplink.in/3cb2cb791397 Fikper Free Download https://fikper.com/LEUepPwq7Q/rajho.Pluralsight..Scalable.Data.Processing.with.Python.rar.html No Password - Links are Interchangeable

Free Download Udemy - Data Warehousing with Azure Synapse Analytics Published: 4/2025 Created by: eTech School MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 79 Lectures ( 6h 40m ) | Size: 3.16 GB Unlock the power of data with Azure Synapse Analytics-design, manage, and optimize data warehouses like a pro! What you'll learn Core concepts of data warehousing and business intelligence Azure Synapse Analytics architecture and components Data extraction, transformation, and loading (ETL) techniques Advanced analytics with Apache Spark and integration with Power BI Performance optimization and scaling strategies Security best practices and compliance in Azure Hands-on experience with Azure Synapse Studio, SQL pools, and data pipelines Requirements Basic understanding of databases and SQL Familiarity with cloud computing concepts Some experience with data analysis or business intelligence tools is helpful but not required Description Introduction:In today's data-driven world, organizations rely on powerful data warehousing solutions to make informed decisions, gain business insights, and drive strategic growth. This course, Mastering Data Warehousing with Azure Synapse Analytics, is designed to equip you with the skills needed to design, implement, and optimize data warehouses on Microsoft Azure. Through comprehensive modules covering foundational concepts, advanced analytics, performance tuning, and security, you'll learn to harness Azure Synapse Analytics to handle complex data workloads efficiently. Whether you're preparing for Azure certifications, enhancing your career in data engineering, or leading data-driven projects, this course provides the expertise you need to excel.Section-wise Write-Up:Module 1: Understanding Data Warehousing FundamentalsThis module introduces the foundational concepts of data warehousing, explaining what a data warehouse is, why it's essential, and how it differs from other data storage solutions like data lakes. You'll explore the architecture and design principles that underpin data warehouses, including the key components that make them effective for business intelligence (BI) applications. The session also distinguishes between data lakes and data warehouses, helping you understand when to use each. Furthermore, we'll cover the key concepts of data warehousing, including ETL processes, dimensional modeling, and data governance, as well as the various types of data warehouses, from on-premises solutions to cloud-based architectures.Module 2: Introduction to Azure Data Services for Data WarehousingTransitioning into the Azure ecosystem, this module introduces the Azure Data Platform, highlighting its key features and benefits. You'll gain an understanding of how Azure supports modern data warehousing needs through services like Azure Synapse Analytics and Azure SQL Data Warehouse. The module covers the architecture of Azure Synapse, its integration with other Azure services, and the role of big data components in a unified analytics environment. By the end of this section, you'll understand how Azure enables seamless data processing, from structured data to big data analytics.Module 3: Designing Data Warehouse ArchitectureIn this module, you'll learn best practices for designing and implementing data warehouses tailored for business intelligence. The focus will be on designing architectures that are scalable, efficient, and optimized for performance. You'll explore data modeling techniques, including star and snowflake schemas, and learn how to load data into dedicated and serverless SQL pools within Azure Synapse Analytics. Best practices for managing Azure data services, integrating NoSQL databases, and utilizing Azure Streaming services for real-time analytics will also be covered. This module ensures you're equipped to design robust data warehouse architectures for various business scenarios.Module 4: Data Extraction, Transformation, and Loading (ETL)This module delves into the ETL process, which is critical for preparing data for analysis. You'll learn about data extraction techniques, methods of loading data into Azure Synapse, and data transformation processes using Azure Data Factory. The course will cover various transformation types, from simple data cleansing to complex data manipulations, and demonstrate how to perform these tasks both natively in Azure Synapse Analytics and using data flows in Azure Data Factory. Practical exercises will help solidify your understanding of ETL pipelines, ensuring you can efficiently move and transform data across systems.Module 5: Implementing Azure Synapse Analytics for Data WarehousingThis module provides an in-depth look at Azure Synapse Analytics, focusing on its implementation and operational capabilities. You'll explore how to create and configure Synapse workspaces, manage dedicated SQL pools, and optimize performance through effective resource management. The hands-on labs will guide you through practical scenarios, such as creating dedicated SQL pools, configuring Apache Spark pools, and managing data security through role-based access control and column-level security. You'll also learn about dynamic data masking and authentication methods to protect sensitive information within your data warehouse.Module 6: Data Integration and Orchestration with Azure SynapseData integration is at the heart of any data warehouse project. In this module, you'll learn how to ingest data from various sources into Azure Synapse Analytics, including on-premises databases, cloud services, and third-party applications. You'll explore the orchestration of data workflows using Synapse pipelines, managing dependencies, scheduling tasks, and automating data movement. This section ensures you can build robust data pipelines that are reliable, scalable, and efficient.Module 7: Advanced Analytics in Azure Synapse AnalyticsThis module focuses on leveraging Azure Synapse for advanced analytics. You'll dive into using Apache Spark within Synapse to perform complex data analyses, including data exploration, statistical analysis, and machine learning. The course covers how to visualize data using Spark and integrate with Power BI for rich, interactive dashboards. Hands-on labs will guide you through real-world data exploration scenarios, helping you unlock actionable insights from your data.Module 8: Performance Optimization in Azure SynapseOptimizing performance is crucial for efficient data processing and cost management. In this module, you'll learn about performance tuning strategies, including query optimization, resource scaling, and identifying performance bottlenecks. The course will cover indexing techniques, managing large datasets effectively, and creating statistics to improve query performance. Practical exercises will demonstrate how to diagnose and resolve common performance issues within Azure Synapse.Module 9: Data Partitioning and Distribution StrategiesEffective data partitioning and distribution can significantly enhance query performance and reduce costs. This module covers advanced techniques for partitioning tables in dedicated SQL pools, choosing the right data distribution strategy, and assessing the suitability of different approaches based on workload Requirements. You'll explore the trade-offs of hash, round-robin, and replicated distribution methods, ensuring you can design optimized data models for performance and scalability.Module 10: Advanced Security and Compliance in Azure SynapseSecurity and compliance are critical in data warehousing environments. This module covers the security baseline for Azure Synapse Analytics, including data encryption (both at rest and in transit), authentication mechanisms, and role-based access control. You'll also learn about regulatory compliance Requirements, data governance practices, and how to leverage Microsoft Purview for data lineage and cataloging. This section ensures your data warehouse is secure, compliant, and aligned with best practices.Module 11: Scaling and Managing Azure Synapse AnalyticsIn the final module, you'll learn how to scale and manage your Azure Synapse environment effectively. The course covers scaling compute resources, managing workloads, and using Azure Monitor to track performance. You'll explore Azure Advisor for optimizing resource utilization and troubleshooting common issues in dedicated SQL pools. Hands-on labs will provide practical experience with scaling strategies, workload management, and monitoring best practices.Conclusion:By the end of this course, you'll have a comprehensive understanding of data warehousing concepts, Azure Synapse Analytics, and the skills needed to design, implement, and optimize data warehouses in the cloud. You'll be prepared to tackle real-world data challenges, manage large-scale analytics projects, and confidently pursue Azure certifications. Whether you're a data engineer, business analyst, or IT professional, this course will empower you to harness the full potential of Azure Synapse for transformative data solutions. 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Free Download Udemy - Data Visualization using Tableau by Swapnil Saurav Published: 4/2025 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 35m | Size: 220 MB Unlock the Power of Data with Tableau - From Basics to AdvancedTechniques What you'll learn Fundamentals of data visualization and how Tableau stands out in the analytics field. Step-by-step guide to installing Tableau and setting up your first data visualization project. Techniques to connect Tableau to various data sources and perform data preparation. Mastery of creating dynamic and interactive dashboards and stories. Advanced data analysis techniques, including calculated fields, parameters, and Tableau analytics pane features. Best practices for data storytelling and creating visually appealing reports. Tips and tricks to optimize your Tableau workflow and enhance performance. Requirements No prior experience with Tableau or data visualization is required. A willingness to learn through practice. Description Embark on a comprehensive journey through the world of data visualization with our Data Visualization using Tableau course. Designed for beginners and intermediate users alike, this course offers a deep dive into Tableau, one of the leading data visualization tools used by businesses and data analysts worldwide. Whether you're looking to enhance your career, make data-driven decisions, or simply bring your data to life, this course is your gateway to mastering Tableau.You'll Learn:Fundamentals of data visualization and how Tableau stands out in the analytics field.Step-by-step guide to installing Tableau and setting up your first data visualization project.Techniques to connect Tableau to various data sources and perform data preparation.Mastery of creating dynamic and interactive dashboards and stories.Best practices for data storytelling and creating visually appealing reports.Tips and tricks to optimize your Tableau workflow and enhance performance.Why This Course:Hands-On Projects: Apply what you learn with real-world data visualization projects.Expert Instruction: Gain insights from an instructor with extensive experience in data analytics and Tableau.Flexible Learning: Study at your own pace, and become expert with Data Analytics skills and Tableau working knowledgeCommunity Support: Join a community of fellow learners to share insights and get feedback. Who this course is for Aspiring data analysts and business intelligence professionals. Individuals seeking to switch careers into data analytics. Business professionals and managers who want to make data-driven decisions. Marketers, finance professionals, and researchers looking to visualize data more effectively. Students and educators seeking practical knowledge in data visualization tools. Homepage: https://www.udemy.com/course/tableau-data-visualization-mastery/ [b]AusFile[/b] https://ausfile.com/39mfw3qxpdms/heuib.Data.Visualization.using.Tableau.by.Swapnil.Saurav.rar.html Rapidgator https://rg.to/file/de9e6e4a2081a547b44802282e9f95aa/heuib.Data.Visualization.using.Tableau.by.Swapnil.Saurav.rar.html Fikper Free Download https://fikper.com/aVag20mH7J/heuib.Data.Visualization.using.Tableau.by.Swapnil.Saurav.rar No Password - Links are Interchangeable

Free Download Linkedin - The AI-Driven Data Scientist Optimize, Innovate, Transform Released: 04/2025 Duration: 49m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 109 MB Level: Intermediate | Genre: eLearning | Language: English Artificial intelligence is transforming data science-and data science jobs. How do you stay on top of current and future trends? To stay ahead in an increasingly AI-driven world, you need AI agents that make AI smart, faster, and more adaptable. This course offers an introduction to AI agents along with practical tips for applying AI technology in popular tech job roles, across different industries like energy and utilities, media, transportation, healthcare, agriculture, and more. Join instructor Matthew Blasa as he shows you how to leverage game-changing AI agents to reshape your workflows, drive smarter decisions, and future-proof your data science career. Homepage: https://www.linkedin.com/learning/the-ai-driven-data-scientist-optimize-innovate-transform [b]AusFile[/b] https://ausfile.com/9uplbchvmtr3/arysz.Linkedin..The.AIDriven.Data.Scientist.Optimize.Innovate.Transform.rar.html Fileaxa https://fileaxa.com/c8z3c9skhrqj/arysz.Linkedin..The.AIDriven.Data.Scientist.Optimize.Innovate.Transform.rar TakeFile https://takefile.link/towmsn0j0hmu/arysz.Linkedin..The.AIDriven.Data.Scientist.Optimize.Innovate.Transform.rar.html Rapidgator http://peeplink.in/c893f025746c Fikper Free Download https://fikper.com/2TLhvnB0QY/arysz.Linkedin..The.AIDriven.Data.Scientist.Optimize.Innovate.Transform.rar No Password - Links are Interchangeable

Free Download Udemy - Identifying Causal Effects for Data Scientists Published: 4/2025 Created by: Zach Flynn MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Intermediate | Genre: eLearning | Language: English | Duration: 13 Lectures ( 2h 1m ) | Size: 1.3 GB Causal Inference from First Principles Using Methods like Instrumental Variables and Difference-in-Differences and More What you'll learn Measure the causal impact of treatments for product analytics and policy evaluation Think through causal inference problems from first principles Map information you know about the world and the industry you work in into measures of causal impacts Distinguish between what the data tells you about causal effects and what comes via your assumptions Translate knowledge about how an industry or product works into bounds on treatment effects Think carefully and deductively about making inference on treatment effects Use instrumental variables with both heterogenous treatment effects and homogenous effects Use the Conditional Independence Assumption to Identify Average Treatment Effects and the risks and potential bias from using the assumption Use the parallel trends assumption to motivate difference-in-difference estimation, the downsides of the assumption, and a more robust alternative Requirements Basic statistics and probability. CDFs. Conditional Expectations. Useful to have some background on linear regression. Not a math-heavy course. Some algebra and basic properties of probability and expectations. Description The most common question you'll be asked in your career as a data scientist is: What was/is/will be the effect of X? In many roles, it's the only question you'll be asked. So it makes sense to learn how to answer it well.This course teaches you how to identify these "treatment effects" or "causal effects". It teaches you how to think about identifying causal relationships from first principles. You'll learn to ask:What does the data say by itself?What do I know about the world that the data doesn't know?What happens when I combine that knowledge with the data?This course teaches you how to approach these three questions, starting with a blank page. It teaches you to combine your knowledge of how the world works with data to find novel solutions to thorny data analysis problems.This course doesn't teach a "cookbook" of methods or some fixed procedure. It teaches you to think through identification problems step-by-step from first principles. As for specifics:This course takes you through various weak assumptions that bound the treatment effect-oftentimes, the relevant question is just: "Is the treatment effect positive?"-and stronger assumptions that pin the treatment effect down to a single value. We learn what the data alone-without any assumptions-tells us about treatment effects, and what we can learn from common assumptions, like:Random treatment assignment (Experimentation)Conditional independence assumptions (Inverse propensity weighting or regression analysis)Exclusion restrictions (Instrumental variable assumptions)Repeated Measurement assumptionsParallel Trends (Difference-in-difference)And many assumptions you will probably not see in other courses, like:Monotone instrumental variablesMonotone confoundingMonotone treatment selectionMonotone treatment responseMonotone trends(Why do they all include "monotone" in the name? The answer to that question is beyond the scope of this course.)Lectures include lecture notes, which make it easy to review the math step by step. The course also includes quizzes and assignments to practice using and applying the material.My background: I have a PhD in Economics from the University of Wisconsin - Madison and have worked primarily in the tech industry. I'm currently a Prin[beeep]l Data Scientist, working mainly on demand modeling and experimentation analysis problems-both examples of treatment effect estimation! I am from sunny San Diego, California, USA. I hope you'll try the Preview courses and enroll in the full course! I'm always available for Q/A.-Zach Who this course is for Data Scientists looking to expand their repertoire of methods for estimating causal effects Data Scientists looking to improve their skills to derive novel approaches for measuring causal effects from first principles People who know statistics but want to learn how to think carefully about identifying causal treatment effects Anyone who wants to better understand how assumptions and data work together to identify treatment effects Homepage: https://www.udemy.com/course/identifying-causal-effects-for-data-scientists/ [b]AusFile[/b] https://ausfile.com/2s604d411ik0/nlbge.Identifying.Causal.Effects.for.Data.Scientists.part1.rar.html https://ausfile.com/4ez3x3ae19wy/nlbge.Identifying.Causal.Effects.for.Data.Scientists.part2.rar.html Rapidgator https://rg.to/file/03cccf48e4427376340e9babccb51c6f/nlbge.Identifying.Causal.Effects.for.Data.Scientists.part1.rar.html https://rg.to/file/3fa803db5067138cf3b9cc7ddd52f301/nlbge.Identifying.Causal.Effects.for.Data.Scientists.part2.rar.html Fikper Free Download https://fikper.com/EOCW1DjLN3/nlbge.Identifying.Causal.Effects.for.Data.Scientists.part1.rar.html https://fikper.com/yoP2TPiXgI/nlbge.Identifying.Causal.Effects.for.Data.Scientists.part2.rar.html No Password - Links are Interchangeable

Free Download Udemy - Master in Data Analysis and Analytics Published: 4/2025 Created by: Arun Singhal B-Tech, MBA (IIM-B),Unilever, J&J, Danone, IIMU, Cello MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 38 Lectures ( 5h 36m ) | Size: 5.83 GB A Data Analyst course learning use of advanced excel, power bi, tableau and python to draw insights to better decisions What you'll learn What is Data Analysis & Analytics How is Data Analysis & Analytics different from Business Analytics and Data Science Case Studies of Excellence in Data Analysis & Analytics How to build excellence in Data Analysis & Analytics Ensuring Data Quality & Integrity Centralizing Data with a Modern Infrastructure Learning & Applying Different Types of Analytics Using the Right Tools & Technologies Understanding Business Needs & KPIs Developing Data-Driven Decision-Making Culture Automating Reporting and Dashboards Adopting Scalable Cloud & AI Solutions Developing Strong Visualization Skill Translating Data into Actionable Insights Ensuring Data Privacy & Compliance Preventing Bias & Ensuring Transparency Requirements 5 hours Description Want to become an Successful Data Analyst but don't know what to do and how?Take a look at this course where you willNot only learn about the Data Analysis and Analytics in depth interactively with a lot of examples and case studies including Ensure Data Quality & Integrity, Centralize Data with a Modern Infrastructure, Learn & Apply Different Types of Analytics, Using the Right Tools & Technologies, Automating Reporting and Dashboards, Adopting Scalable Cloud & AI Solutions, Developing Strong Visualization Skill, Translating Data into Actionable Insights, Ensuring Data Privacy & Compliance, Preventing Bias & Ensure Transparency but also learnUnderstanding Business Needs & KPIs, Developing Data-Driven Decision-Making CulturePreview many lectures for free to see the content for yourselfClear your doubts on this topic any time while doing the courseGet Udemy's 30 days Money Back GuaranteeMy exposure to Data Analysis started 40 years back in 1979-81 at Indian Institute of Management Bangalore when I learnt about various methodologies and tools like Multivariate and Conjoint Analysis to make better management decisions. Data Analytics was not yet born as it has developed and matured now with developments in Machine Learning and other Algorithms that have made it possible to use those methodologies and toolsWhile I continued to use the Data Analysis during next about 30 years while working in Unilever, Johnson and Johnson and Danone, I came to know about the fully developed Data Analytics in 2016 when I started working at IIM Udaipur teaching an coaching MBA studentsWhile I had a good understanding of the Understanding Business Needs & KPIs, Developing Data-Driven Decision-Making Culture from my earlier years of management education and experience, I had to learn all about Ensuring Data Quality & Integrity, Centralizing Data with a Modern Infrastructure, Learning & Applying Different Types of Analytics, Using the Right Tools & Technologies, Automating Reporting and Dashboards, Adopting Scalable Cloud & AI Solutions, Developing Strong Visualization Skill, Translating Data into Actionable Insights, Ensuring Data Privacy & Compliance, Preventing Bias & Ensure Transparency.I continued my learning journey in this rapidly evolving field since then while working with many of my clients in data analysis and analytics till nowI bring in this course my learnings from this journey and share with you how can you also become a Successful Data AnalystPreview for yourself many lectures free. If you like the content, enrol for the course, enjoy and skill yourself to become a Master in Data Analysis and Analytics! 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Free Download Linkedin - Intro to Snowflake for Devs, Data Scientists, Data Engineers Released 04/2025 With Snowflake, Inc MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 5h 4m 27s | Size: 1 GB Learn the basics of Snowflake as a platform for building applications, data pipelines, and AI models. Course details Ready to get started with Snowflake, the easy-to-use platform for building applications, data pipelines, AI models, and workflows? In this course, you'll progress from having zero technical know-how with Snowflake all the way to creating user-defined functions, using a Snowflake Cortex LLM function, editing a Streamlit app, and more. Learn to use Snowflake's core objects such as virtual warehouses, stages, and databases, before turning to more advanced objects and features such as time travel, cloning, and stored procedures. By the end of this course, you'll be ready to start building with Snowflake on data engineering, generative AI, machine learning, and app development projects. Homepage: https://www.linkedin.com/learning/intro-to-snowflake-for-devs-data-scientists-data-engineers [b]AusFile[/b] https://ausfile.com/7pqkm4zxlbqb/rqubw.linkedin..Intro.to.Snowflake.for.Devs.Data.Scientists.Data.Engineers.part2.rar.html https://ausfile.com/h157zzu6p2nc/rqubw.linkedin..Intro.to.Snowflake.for.Devs.Data.Scientists.Data.Engineers.part1.rar.html Fileaxa https://fileaxa.com/vkaisu9zpya8/rqubw.linkedin..Intro.to.Snowflake.for.Devs.Data.Scientists.Data.Engineers.part2.rar https://fileaxa.com/xzg1rema5gsx/rqubw.linkedin..Intro.to.Snowflake.for.Devs.Data.Scientists.Data.Engineers.part1.rar TakeFile https://takefile.link/1okqnp32l7qt/rqubw.linkedin..Intro.to.Snowflake.for.Devs.Data.Scientists.Data.Engineers.part1.rar.html https://takefile.link/lvip1mr16ntl/rqubw.linkedin..Intro.to.Snowflake.for.Devs.Data.Scientists.Data.Engineers.part2.rar.html Rapidgator http://peeplink.in/0f1d9a51deee Fikper Free Download https://fikper.com/S69CaZgkls/rqubw.linkedin..Intro.to.Snowflake.for.Devs.Data.Scientists.Data.Engineers.part1.rar.html https://fikper.com/qopacSInZT/rqubw.linkedin..Intro.to.Snowflake.for.Devs.Data.Scientists.Data.Engineers.part2.rar.html No Password - Links are Interchangeable

Free Download Linkedin - Excel Managing and Analyzing Data (2025) Released 04/2025 With Oz du Soleil MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 4h 47m 4s | Size: 843 MB Learn to clean, manage, and analyze data in Excel efficiently using modern tools like Power Query, dynamic arrays, and PivotTables to extract meaningful insights. Course details In this course, Oz du Soleil-an Excel MVP, author, and trainer with a passion for clean data and reliable reporting-equips you with the skills to effectively manage and analyze large or complex datasets in Excel. Learn how to check data quality, clean and organize data, and leverage Excel's advanced tools like Power Query and dynamic arrays. Find out how to split columns, structure data, and combine datasets while maintaining integrity and scalability. Plus, get an introduction to sorting, filtering, and PivotTable techniques, along with essential functions and visualization tools for clear data representation. When you complete the course, you will be proficient in transforming raw data into actionable insights and enhancing decision-making processes. Homepage: https://www.linkedin.com/learning/excel-managing-and-analyzing-data-25384011 [b]AusFile[/b] https://ausfile.com/zd17l2u7qxoj/fnxfh.linkedin..Excel.Managing.and.Analyzing.Data.2025.rar.html Fileaxa https://fileaxa.com/w57xwf6hbj70/fnxfh.linkedin..Excel.Managing.and.Analyzing.Data.2025.rar TakeFile https://takefile.link/5osmi38ry4il/fnxfh.linkedin..Excel.Managing.and.Analyzing.Data.2025.rar.html Rapidgator http://peeplink.in/56b5f4527ecc Fikper Free Download https://fikper.com/BvgMzCttLW/fnxfh.linkedin..Excel.Managing.and.Analyzing.Data.2025.rar.html No Password - Links are Interchangeable

Free Download Linkedin - Data Analytics for Business Professionals (2025) Released 04/2025 With John Johnson MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 20m 31s | Size: 202 MB Learn how to apply foundational data concepts and subject matter expertise to assess and validate complex analyses in an AI analytics environment through detailed case studies. Course details Hearing the phrase "AI analytics" can sound daunting but don't fret. In this course, instructor John Johnson teaches you how to think about AI as a super tool that can make you more efficient and effective. Data analytics can help cut costs, speed up delivery, generate forecasts, and improve outcomes for your business over time. Rather than trying to teach the complicated mathematical and statistical techniques that an AI tool may use, John focuses on the role of a business professional in assessing, interpreting, and applying their outputs in the context of complex business decisions through targeted case studies. Find out how to collect, clean, and aggregate data from different sources across your organization, and identify when data is flawed. John gives you pointers on planning and deploying an analytics strategy that fits the specific needs of your business, covering a variety of simple techniques: averages, sampling, cherry picking, forecasting, correlation, causality, and more. Homepage: https://www.linkedin.com/learning/data-analytics-for-business-professionals-24832385 [b]AusFile[/b] https://ausfile.com/dordlcr3gp3w/thisi.linkedin..Data.Analytics.for.Business.Professionals.2025.rar.html Fileaxa https://fileaxa.com/vssnflxub8cu/thisi.linkedin..Data.Analytics.for.Business.Professionals.2025.rar TakeFile https://takefile.link/qbs794ceu7ws/thisi.linkedin..Data.Analytics.for.Business.Professionals.2025.rar.html Rapidgator http://peeplink.in/2a97d7d3b44a Fikper Free Download https://fikper.com/y8oxaGjBoq/thisi.linkedin..Data.Analytics.for.Business.Professionals.2025.rar.html No Password - Links are Interchangeable

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Free Download Udemy - Mastering Data Structures & Algorithms in Swift & iOS Published: 4/2025 Created by: Stephan Dowless MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 22 Lectures ( 4h 36m ) | Size: 1.74 GB Master Data Structures & Algorithms to Ace iOS Interviews and Land Six-Figure Offers What you'll learn Master Essential Data Structures - Understand arrays, linked lists, stacks, queues, and binary trees to solve real-world problems efficiently. Crack Coding Interviews with Confidence - Learn proven strategies to tackle technical questions from top tech companies like Meta, Google, and Uber. Optimize Code with Big O Notation - Analyze time and space complexity to write scalable, high-performance algorithms. Solve Problems Like a Pro - Develop a structured approach to solving algorithmic challenges, improving problem-solving speed and accuracy. Requirements No Requirements or pre requisites! Just be ready to learn Description Want to land a six-figure iOS engineering job at top tech companies? This course will teach you the data structures and algorithms you need to pass technical interviews at companies like Meta, Google, Uber, and top fintech startups. This stuff is complicated, and I'm here to break it down step by step for you. I'm Stephan Dowless, a former Senior Engineer at Meta, and I've successfully passed interviews at multiple FAANG and high-paying tech firms. In this course, I'll share the exact problem-solving techniques that helped me land offers and that can help you crack the coding interview.What You'll Learn:- Arrays & Strings - Commonly tested problems and optimal solutions- Linked Lists - Master traversal, insertion, and deletion techniques- Stacks & Queues - Learn their real-world applications in coding interviews- Binary Trees - Get comfortable with recursion and tree traversal algorithms- Big O Notation - Learn how to write efficient, scalable code- Recursion - Advanced techniques to improve algorithm performanceThis course is designed for both beginners and experienced developers, covering everything from fundamentals to advanced topics. Whether you're preparing for your first iOS job interview or aiming for a higher-paying role, this course will equip you with the skills to succeed.Enroll now and take your coding interview prep to the next level! Who this course is for Developers of all levels looking to learn data structures and algorithms Homepage: https://www.udemy.com/course/mastering-data-structures-algorithms-in-swift-ios/ [b]AusFile[/b] https://ausfile.com/e83spjpbxkkl/tmwnb.Mastering.Data.Structures..Algorithms.in.Swift..iOS.part1.rar.html https://ausfile.com/6fblwt9azvms/tmwnb.Mastering.Data.Structures..Algorithms.in.Swift..iOS.part2.rar.html Rapidgator https://rg.to/file/f12fc7ac06a15b6b36e8403a125b01e7/tmwnb.Mastering.Data.Structures..Algorithms.in.Swift..iOS.part1.rar.html https://rg.to/file/731172fa64998ddfe9e331879e293ed5/tmwnb.Mastering.Data.Structures..Algorithms.in.Swift..iOS.part2.rar.html Fikper Free Download https://fikper.com/wGQBI43j8B/tmwnb.Mastering.Data.Structures..Algorithms.in.Swift..iOS.part1.rar.html https://fikper.com/1v5HbRW6c7/tmwnb.Mastering.Data.Structures..Algorithms.in.Swift..iOS.part2.rar.html No Password - Links are Interchangeable

Free Download Udemy - Azure DataBricks - Data Engineering With Real Time Project Last updated: 4/2025 Created by: Ragunathan Ramanujam MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English + subtitle | Duration: 155 Lectures ( 14h 41m ) | Size: 6.71 GB Real Time Project on Retail Data Using PySpark ,SQL, Delta/Delta Live Table, Unity Catalogue, Auto Loader and Streaming What you'll learn Medallion Architecture , Dimensional Data Modelling Design , DeltalakeHouse Design , Spark Core Architecture , Unity Catalogue Setup , Spark Cluster Setup PySpark Dataframe Reader , Writer , Transformation Functions , Action Functions , DateTime Functions , Aggregation Functions , Dataframe Joins , Complex Data Spark SQL External Tables , Managed Tables , Delta Lake Tables , Create Table As Script(CTAS) , Temp Views , Table Joins , Data Transformation Functions Four Reusable Ingestion Pipelines To Ingest Source Data From Web(HTTP) Service , Database Tables , API Source Systems , Incremental Loading & Job Scheduling Seven Data Transformation Pipelines to process source data in Silver & Gold Layers and Build Reporting Database And Datalake With Change Data Capture Spark Streaming Reader & Writer Configuration To Process Real Time Steaming Data , CHECKPOINTLOCATION setup for automated Incremental Loading in Streaming Data Delta Live Tables - Materialised Views , Streaming Tables setup , Delta Live Table Pipeline Configuration , Data Quality Checks , AUTOLOADER and APPLY CHANGES Monitoring And Logging Setup To Monitor Production Job Runs, Setup Alerts for Job Failure and Extended Logging of Job Runs and Service Metrics Security Settings in Azure using Microsoft Entra ID , IAM Role Based Access Control(RBAC) And Databricks Workspace Admin Settings Configure Github Repository , Git Repos Folders in Databricks Workspace , Ways of Working with Git branches , Merging Code & PULL requests Setup Production Environment , CI/CD Pipeline to automate Code Deployment Using GitHub Actions Requirements None , Course Includes all of the Basic Python Skils and SQL skills necessary to develop the code Description By Completing this course you will be equipped with below Data Engineer Roles & Responsibilities in the real time project• Designing and Developing Databricks(PySpark) Notebooks to Ingest the data from Web(HTTP) Services• Designing and Developing Databricks(PySpark) Notebooks to Ingest the data from SQL Databases• Designing and Developing Databricks(PySpark) Notebooks to Ingest the data from API source Systems• Designing and Developing Spark SQL External and Managed Tables• Developed Databricks Spark SQL Reusable Notebooks To Create Delta Lake Tables• Developed Databricks SQL Code to populate Reporting Dimension tables• Developed Databricks SQL Code to populate Reporting Fact Table• Designing and Developing Databricks(PySpark ) Notebooks to Process and Flatten Semi Structured JSON Data • Designing and Developing Databricks(PySpark ) Notebooks to Integrate Data and load into Datalake Gold Layer• Designing and Developing Databricks(PySpark) Notebooks to Process Semi Structured JSON Data in DataLake Silver Layer• Designing and Developing Databricks(SQL) Notebooks to Integrate Data and load into Datalake Gold Layer• Designing and Configuring Unity Catalogue for Better Access Control & Connecting to External Data Stores• Developed Databricks Jobs for Scheduling the Data Ingestion and Transformation Notebooks• Designing and Configuring Delta Live Tables in all layers for seamless Data Integration• Setup Azure Monitor and Log Analytics for Automated Monitoring of Job Runs and Stored Extended Log Details• Setup Azure Key Vault and Configure Key Vault Backed Secret Scopes in Databricks Workspace• Configuring GitHub Repository and creating Git Repo Folders in Databricks Workspace• Designing and Configuring CI/CD Pipelines to release the code into multiple environment Who this course is for Anyone 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