kingers Posted March 22 Report Share Posted March 22 Databricks: Master Data Engineering, Big Data, Analytics, Ai Published 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 21.70 GB | Duration: 53h 3mMaster Databricks for data engineering, analytics, machine learning, and cloud integration with real-world applications. What you'll learn Understand Databricks Architecture - Learn the key components, workspace features, and advantages of Databricks over traditional data platforms. Set Up and Configure Databricks - Create a Databricks workspace, manage clusters, and navigate notebooks for data processing. Perform ETL Operations - Use Apache Spark in Databricks for extracting, transforming, and loading (ETL) large datasets efficiently. Work with Delta Lake - Implement incremental data loading, schema evolution, and time travel features using Delta Lake. Run SQL Queries in Databricks - Utilize Databricks SQL for querying and analyzing structured data, optimizing performance, and creating dashboards. Build and Deploy Machine Learning Models - Use MLflow for model tracking, hyperparameter tuning, and deploying ML models within Databricks. Integrate Databricks with Cloud Services - Connect Databricks with AWS S3, Azure Data Factory, Snowflake, and BI tools like Power BI. Optimize Cluster Performance - Learn auto-scaling, partitioning, bucketing, and performance tuning techniques for handling big data workloads. Implement Real-Time Data Processing - Develop streaming analytics pipelines for IoT and real-time event processing in Databricks. Secure Data in Databricks - Apply role-based access control (RBAC), encryption, and auditing to protect sensitive data. Develop CI/CD Pipelines for Databricks - Automate deployment and testing using GitHub, Azure DevOps, and Databricks REST API. Manage Data Warehousing in Databricks - Design scalable data lakes, data marts, and warehouse architectures for enterprise solutions. Perform Graph and Time Series Analysis - Use GraphFrames for graph processing and time-series forecasting in Databricks. Monitor and Audit Databricks Workloads - Track resource utilization, job performance, and cost optimization strategies for efficient cloud usage. Apply Databricks to Real-World Use Cases - Work on projects like customer segmentation, predictive maintenance, and fraud detection using Databricks. Requirements Enthusiasm and determination to make your mark on the world! Description A warm welcome to the Databricks: Master Data Engineering, Big Data, Analytics, AI course by Uplatz.Databricks is a cloud-based data engineering, analytics, and machine learning platform built on Apache Spark. It provides an integrated environment for processing big data, performing analytics, and deploying machine learning models. Databricks simplifies data engineering and collaboration by offering a unified workspace where data engineers, data scientists, and analysts can work together efficiently. It is available on Microsoft Azure, Amazon Web Services, and Google Cloud, making it a versatile choice for enterprises working with large datasets.Databricks is widely used in industries such as finance, healthcare, retail, and technology for handling large-scale data workloads efficiently. It provides a powerful and scalable solution for organizations looking to leverage big data for analytics, machine learning, and business intelligence.How Databricks WorksDatabricks operates as a fully managed, cloud-based platform that automates and optimizes big data processing. The workflow typically involves:Creating a workspace where users manage notebooks, clusters, and data assets.Configuring clusters using Apache Spark for scalable and distributed computing.Importing and processing data from multiple sources, including data lakes, relational databases, and cloud storage.Running analytics and SQL queries using Databricks SQL for high-performance querying and data visualization.Building and deploying machine learning models using MLflow for tracking experiments, hyperparameter tuning, and deployment.Optimizing performance through auto-scaling, caching, and parallel processing to handle large-scale data workloads efficiently.Integrating with cloud services and APIs such as Azure Data Factory, AWS S3, Power BI, Snowflake, and REST APIs for seamless workflows.Core Features of DatabricksUnified data analytics platform combining data engineering, analytics, and machine learning in a single environment.Optimized runtime for Apache Spark, improving performance for big data workloads.Delta Lake for improved data reliability, versioning, and schema evolution in data lakes.Databricks SQL for running high-performance SQL queries and building interactive dashboards.MLflow for streamlined machine learning development, including model tracking, experimentation, and deployment.Auto-scaling clusters that dynamically allocate resources based on workload requirements.Real-time streaming analytics for processing event-driven data from IoT devices, logs, and real-time applications.Advanced security features, including role-based access control, encryption, and audit logging for compliance.Multi-cloud support with deployment options across AWS, Azure, and Google Cloud.Seamless integration with third-party analytics and business intelligence tools like Power BI, Tableau, and Snowflake.Benefits of Using DatabricksAccelerates data processing by optimizing Spark-based computations for better efficiency.Simplifies data engineering by automating ETL processes, reducing manual intervention.Enhances collaboration by allowing engineers, analysts, and data scientists to work in a shared, cloud-based workspace.Supports AI and machine learning with an integrated framework for training and deploying models at scale.Reduces cloud computing costs through auto-scaling and optimized resource allocation.Ensures data reliability with Delta Lake, enabling ACID transactions and schema enforcement in large datasets.Provides real-time analytics capabilities for fraud detection, IoT applications, and event-driven processing.Offers flexibility with multi-cloud deployment, making it easier to integrate with existing enterprise infrastructure.Meets enterprise security and compliance standards, ensuring data protection and regulatory adherence.Improves business intelligence with Databricks SQL, enabling organizations to gain deeper insights and make data-driven decisions.Databricks - Course Curriculum1. Introduction to DatabricksIntroduction to DatabricksWhat is Databricks? Platform OverviewKey Features of Databricks WorkspaceDatabricks Architecture and ComponentsDatabricks vs Traditional Data Platforms2. Getting Started with DatabricksSetting Up a Databricks WorkspaceDatabricks Notebook BasicsImporting and Organizing Datasets in DatabricksExploring Databricks ClustersDatabricks Community Edition: Features and Limitations3. Data Engineering in DatabricksIntroduction to ETL in DatabricksUsing Apache Spark with DatabricksWorking with Delta Lake in DatabricksIncremental Data Loading Using Delta LakeData Schema Evolution in Databricks4. Data Analysis with DatabricksRunning SQL Queries in DatabricksCreating and Visualizing DashboardsOptimizing Queries in Databricks SQLWorking with Databricks Connect for BI ToolsUsing the Databricks SQL REST API5. Machine Learning & Data ScienceIntroduction to Machine Learning with DatabricksFeature Engineering in DatabricksBuilding ML Models with Databricks MLFlowHyperparameter Tuning in DatabricksDeploying ML Models with Databricks6. Integration and APIsIntegrating Databricks with Azure Data FactoryConnecting Databricks with AWS S3 BucketsDatabricks REST API BasicsConnecting Power BI with DatabricksIntegrating Snowflake with Databricks7. Performance OptimizationUnderstanding Databricks Auto-ScalingCluster Performance Optimization TechniquesPartitioning and Bucketing in DatabricksManaging Metadata with Hive Tables in DatabricksCost Optimization in Databricks8. Security and ComplianceSecuring Data in Databricks Using Role-Based Access Control (RBAC)Setting Up Secure Connections in DatabricksManaging Encryption in DatabricksAuditing and Monitoring in Databricks9. Real-World ApplicationsReal-Time Streaming Analytics with DatabricksData Warehousing Use Cases in DatabricksBuilding Customer Segmentation Models with DatabricksPredictive Maintenance Using DatabricksIoT Data Analysis in Databricks10. Advanced Topics in DatabricksUsing GraphFrames for Graph Processing in DatabricksTime Series Analysis with DatabricksData Lineage Tracking in DatabricksBuilding Custom Libraries for DatabricksCI/CD Pipelines for Databricks Projects11. Closing & Best PracticesBest Practices for Managing Databricks Projects Overview Section 1: Introduction to Databricks Lecture 1 Introduction to Databricks Section 2: Databricks Platform Overview Lecture 2 Databricks Platform Overview Section 3: Key Features of Databricks Workspace Lecture 3 Key Features of Databricks Workspace Section 4: Databricks Architecture and Components Lecture 4 Databricks Architecture and Components Section 5: Databricks vs. Traditional Data Platforms Lecture 5 Databricks vs. Traditional Data Platforms Section 6: Setting up a Databricks Workspace Lecture 6 Setting up a Databricks Workspace Section 7: Databricks Notebook Basics Lecture 7 Databricks Notebook Basics Section 8: Importing and Organizing Datasets in Databricks Lecture 8 Importing and Organizing Datasets in Databricks Section 9: Exploring Databricks Clusters Lecture 9 Exploring Databricks Clusters Section 10: Databricks Community Edition: Features and Limitations Lecture 10 Databricks Community Edition: Features and Limitations Section 11: Introduction to ETL in Databricks Lecture 11 Introduction to ETL in Databricks Section 12: Using Apache Spark with Databricks Lecture 12 Using Apache Spark with Databricks Section 13: Working with Delta Lake in Databricks Lecture 13 Working with Delta Lake in Databricks Section 14: Incremental Data Loading using Delta Lake Lecture 14 Incremental Data Loading using Delta Lake Section 15: Data Schema Evolution in Databricks Lecture 15 Data Schema Evolution in Databricks Section 16: Running SQL Queries in Databricks Lecture 16 Running SQL Queries in Databricks Section 17: Creating and Visualizing Dashboards Lecture 17 Creating and Visualizing Dashboards Section 18: Optimizing Queries in Databricks SQL Lecture 18 Optimizing Queries in Databricks SQL Section 19: Working with Databricks Connect for BI Tools Lecture 19 Working with Databricks Connect for BI Tools Section 20: Using the Databricks SQL REST API Lecture 20 Using the Databricks SQL REST API Section 21: Introduction to Machine Learning with Databricks Lecture 21 Introduction to Machine Learning with Databricks Section 22: Feature Engineering in Databricks Lecture 22 Feature Engineering in Databricks Section 23: Building ML Models with Databricks MLFlow Lecture 23 Building ML Models with Databricks MLFlow Section 24: Hyperparameter Tuning in Databricks Lecture 24 Part 1 - Hyperparameter Tuning in Databricks Lecture 25 Part 2 - Hyperparameter Tuning in Databricks Section 25: Deploying ML Models with Databricks Lecture 26 Deploying ML Models with Databricks Section 26: Integrating Databricks with Azure Data Factory Lecture 27 Integrating Databricks with Azure Data Factory Section 27: Connecting Databricks with AWS S3 Buckets Lecture 28 Connecting Databricks with AWS S3 Buckets Section 28: Databricks REST API Basics Lecture 29 Databricks REST API Basics Section 29: Connecting Power BI with Databricks Lecture 30 Connecting Power BI with Databricks Section 30: Integrating Snowflake with Databricks Lecture 31 Integrating Snowflake with Databricks Section 31: Understanding Databricks Auto-Scaling Lecture 32 Understanding Databricks Auto-Scaling Section 32: Cluster Performance Optimization Techniques Lecture 33 Cluster Performance Optimization Techniques Section 33: Partitioning and Bucketing in Databricks Lecture 34 Part 1 - Partitioning and Bucketing in Databricks Lecture 35 Part 2 - Partitioning and Bucketing in Databricks Section 34: Managing Metadata with Hive Tables in Databricks Lecture 36 Managing Metadata with Hive Tables in Databricks Section 35: Cost Optimization in Databricks Lecture 37 Cost Optimization in Databricks Section 36: Securing Data in Databricks using Role-Based Access Control Lecture 38 Securing Data in Databricks using Role-Based Access Control Section 37: Setting up Secure Connections in Databricks Lecture 39 Setting up Secure Connections in Databricks Section 38: Managing Encryption in Databricks Lecture 40 Managing Encryption in Databricks Section 39: Auditing and Monitoring in Databricks Lecture 41 Auditing and Monitoring in Databricks Section 40: Real-Time Streaming Analytics with Databricks Lecture 42 Real-Time Streaming Analytics with Databricks Section 41: Data Warehousing Use Cases in Databricks Lecture 43 Data Warehousing Use Cases in Databricks Section 42: Building Customer Segmentation Models with Databricks Lecture 44 Building Customer Segmentation Models with Databricks Section 43: Predictive Maintenance using Databricks Lecture 45 Predictive Maintenance using Databricks Section 44: IoT Data Analysis in Databricks Lecture 46 IoT Data Analysis in Databricks Section 45: Using GraphFrames for Graph Processing in Databricks Lecture 47 Using GraphFrames for Graph Processing in Databricks Section 46: Time Series Analysis with Databricks Lecture 48 Time Series Analysis with Databricks Section 47: Data Lineage Techniques in Databricks Lecture 49 Data Lineage Techniques in Databricks Section 48: Building Custom Libraries for Databricks Lecture 50 Building Custom Libraries for Databricks Section 49: CI/CD Pipelines for Databricks Projects Lecture 51 CI/CD Pipelines for Databricks Projects Section 50: Best Practices for Managing Databricks Projects Lecture 52 Best Practices for Managing Databricks Projects Data Engineers - Professionals working with ETL pipelines, data transformation, and big data processing.,Data Scientists - Those looking to use Databricks for machine learning, feature engineering, and predictive analytics.,Big Data Analysts - Individuals working with large-scale datasets, SQL queries, and business intelligence tools.,Cloud Engineers - Professionals integrating Databricks with AWS, Azure, and Google Cloud for scalable data solutions.,Machine Learning Engineers - Those building and deploying ML models using MLflow, hyperparameter tuning, and automation.,Business Intelligence Professionals - Users working with Databricks SQL, Power BI, and dashboarding tools.,Database Administrators - DBAs managing data lakes, Delta Lake, Hive tables, and metadata in Databricks.,Software Engineers - Developers looking to understand Apache Spark, API integrations, and data pipeline automation.,AI & IoT Specialists - Professionals working on real-time analytics, IoT data processing, and AI-driven insights.,Enterprise Architects - Those designing scalable, cost-effective, and high-performance data platforms.,Cloud Data Professionals - Individuals managing data migration, cost optimization, and auto-scaling clusters.,Students & Graduates - Learners interested in big data technologies, cloud computing, and machine learning.,Finance & Healthcare Analysts - Professionals working with large datasets for fraud detection, risk analysis, and patient insights.,Consultants & Freelancers - Independent professionals offering Databricks consulting, cloud data engineering, and analytics solutions.,Technology Leaders & Decision Makers - CTOs, data managers, and tech leads looking to implement Databricks for business transformation.TurboBithttps://turbobit.net/zubozpqzqk47/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part01.rar.htmlhttps://turbobit.net/z5f2ko09rdwa/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part02.rar.htmlhttps://turbobit.net/2pkt955yqdii/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part03.rar.htmlhttps://turbobit.net/g0posm6r08ax/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part04.rar.htmlhttps://turbobit.net/ln45x0m842ig/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part05.rar.htmlhttps://turbobit.net/gqz2qucxsusf/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part06.rar.htmlhttps://turbobit.net/kj58a3tbtezd/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part07.rar.htmlhttps://turbobit.net/3gnypd8u3z12/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part08.rar.htmlhttps://turbobit.net/y32o7ln7tr77/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part09.rar.htmlhttps://turbobit.net/wo3qjb4qbvxg/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part10.rar.htmlhttps://turbobit.net/ualuv5vwkqhw/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part11.rar.htmlhttps://turbobit.net/6d6cojuqtwrb/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part12.rar.htmlhttps://turbobit.net/pkki7e7fmnvv/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part13.rar.htmlhttps://turbobit.net/f1d1orznmnqg/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part14.rar.htmlhttps://turbobit.net/cmeuujqmwpgo/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part15.rar.htmlhttps://turbobit.net/y2ihrnxm71p2/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part16.rar.htmlhttps://turbobit.net/e380uwq2cc6r/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part17.rar.htmlhttps://turbobit.net/f6w9obbe5svt/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part18.rar.htmlhttps://turbobit.net/a9hkder2cobf/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part19.rar.htmlhttps://turbobit.net/82cm9kvhut92/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part20.rar.htmlhttps://turbobit.net/wboa3t57bms5/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part21.rar.htmlhttps://turbobit.net/x4tebvj1lvsn/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part22.rar.htmlhttps://turbobit.net/c0ejua2vjg8a/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part23.rar.htmlhttps://turbobit.net/t51x3ghfb2gg/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part24.rar.htmlhttps://turbobit.net/0pucinczsuy9/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part25.rar.htmlRapidGatorhttps://rapidgator.net/file/8601a0214b6322d7a7fa5c53160aaee5/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part01.rarhttps://rapidgator.net/file/9357c8e8689164b71b995e6861f2e559/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part02.rarhttps://rapidgator.net/file/642e844391dbc5e2f2e508ca7ec5c640/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part03.rarhttps://rapidgator.net/file/8bc7cfb0fffd333548b34b76ca775ca4/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part04.rarhttps://rapidgator.net/file/bfe102dabee18fa20425e86b9f8f763d/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part05.rarhttps://rapidgator.net/file/4100d5eab65ce6576eedc38554291c9b/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part06.rarhttps://rapidgator.net/file/d3fc8f80b97e59ce8e9e38da8db95a14/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part07.rarhttps://rapidgator.net/file/17442d44df386ba5c24ee947b5747e35/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part08.rarhttps://rapidgator.net/file/d55e6f5754deca6178c73156d2cb0d91/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part09.rarhttps://rapidgator.net/file/b0937421da91bd3ca4930d52832b51f8/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part10.rarhttps://rapidgator.net/file/223e589fdcd9382cff076e6093989ad5/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part11.rarhttps://rapidgator.net/file/9fcd571aaf63f0c130d1bbff7a889372/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part12.rarhttps://rapidgator.net/file/ae660cdc69f5d4c58137669cb85a4573/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part13.rarhttps://rapidgator.net/file/efcb0a91d949b9f543439ffb7be21531/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part14.rarhttps://rapidgator.net/file/b0e2a69fa1ed21b039228ef28f33335f/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part15.rarhttps://rapidgator.net/file/6721a68cbc3adc5c4f4d0791f3787a83/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part16.rarhttps://rapidgator.net/file/775ca09e758e22a6e86709deea66a14f/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part17.rarhttps://rapidgator.net/file/23c70cea66fad52d0a0529bef29cb612/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part18.rarhttps://rapidgator.net/file/de28268e9c93b2c69674430895689567/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part19.rarhttps://rapidgator.net/file/96c54d75914f2995739c395c839b1b70/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part20.rarhttps://rapidgator.net/file/002dea264753cebea9d7aa4d5fc3ecce/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part21.rarhttps://rapidgator.net/file/1af48044a216f9cd0006337dd2228b6b/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part22.rarhttps://rapidgator.net/file/49142a9c427a3bda47ce360d65325ea7/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part23.rarhttps://rapidgator.net/file/6aae567cffa74733267115c0ac236041/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part24.rarhttps://rapidgator.net/file/1045cd74b8e612549f435d120316f6e2/Udemy_Databricks_Master_Data_Engineering_Big_Data_Analytics_AI_2025-3.part25.rarFileFactory Link to comment Share on other sites More sharing options...
Recommended Posts
Please sign in to comment
You will be able to leave a comment after signing in
Sign In Now