kingers Posted May 11 Report Share Posted May 11 Azure Data Engineering End-To-End Course (English) Published 2/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 34.38 GB | Duration: 60h 45mLearn multiple tools in Azure data engineering stack through this course, all in one bundle! What you'll learn Understand end-to-end flow of Azure data engineering stack Be ready to appear for interviews and crack them easily Become independent to maximum level in handling tasks End-to-end project covering entire lifecycle Requirements No pre-requistes for this course as it created from scratch for everyone for every single tool/technology making it easier to learn Description This course covers multiple tools and technologies needed to become an azure data engineer.The best part is there are no pre-requisites!Anyone can enroll and learn through this course.Our videos are simple to understand, to the point, short and yet covering everything you need.The content we are offering in this course is immense and requires full dedication, self -discipline and daily learning to ensure a completion and to make you independent skilled professional.We have trained 1000's of students and shaped their career and you could be the next one, join us by enrolling in the course and benefit immensely through our course offering.You will get best of both quality and quantity!In this course you will learn below tools and technologies from scratch:SQL : Learn structured query language in Microsoft SQL Server.Data warehousing : Learn fundamental concepts of data warehousing.Azure cloud : Learn about cloud computing, benefits and different services.Azure Data factory: Learn ETL on azure cloud, code free.Python programming: Learn programming in python with simple way.Big data fundamentals: Master the big data concepts to build strong foundation.Databricks: Learn databricks, the leading data platform.PySpark: Learn big data processing in pyspark on databricks.Delta lake: Learn the delta lake features.Spark structured streamingAzure devopsEnd-to-end project (Release in progress)This course is for everyone from beginner to architect level! Overview Section 1: Introduction to Azure Data Engineering Lecture 1 Introduction Section 2: SQL Lecture 2 001. Introduction to SQL Lecture 3 002. SQL Server Installation Lecture 4 003. Create And Drop Database Lecture 5 004. System Databases Lecture 6 Create and Drop Tables Lecture 7 006. Insert Data In Table Lecture 8 007. Select Lecture 9 008. InstallAdventureWorksSampleDB Lecture 10 009. GetUniqueValues Lecture 11 010. Sort Data Lecture 12 011. Comments Lecture 13 012. Filter Data Lecture 14 013.Filter With Wild Characters Lecture 15 014. Aggregate Function Lecture 16 015. Grouping Rows Lecture 17 016. Select..Into Lecture 18 017. Create Table With Primary Key Lecture 19 018. Create Table With NOT NULL Constraint Lecture 20 019. Create Table With Unique Constraint Lecture 21 020. Create Table With Check Constraint Lecture 22 021. Create Table With Default Constraint Lecture 23 022. Create Table With AutoIncrement Lecture 24 023.Update Rows In Table Lecture 25 024. Delete Rows From Table Lecture 26 025. String Functions - Part 1 Lecture 27 026. String Functions - Part 2 Lecture 28 027. Scenario - Combine Names Lecture 29 028. Scenario - Extract First And Last Names Lecture 30 029. Date Time Functions - Part 1 Lecture 31 030. Date Time Functions - Part 2 Lecture 32 031. Date Time Functions - Part 3 Lecture 33 032. Data Type - Part 1 - Integers Lecture 34 033. Data Types - Part 2 - Approximate Numeric Lecture 35 034. Data Types - Part 3 - Date Time Lecture 36 035. Data Types - Part 4 - Strings Lecture 37 036. Data Types - Part 5 - Unique identifier Lecture 38 037. Data Types - Part 6 - bit Lecture 39 038. Data Type Conversion Lecture 40 039. Joins Part 1 - Introduction to joins Lecture 41 040. Joins Part 2- Using Joins Lecture 42 041. Joins Part 3- Join 3 tables Lecture 43 042. Joins Part 4- Using Expressions Lecture 44 043. Joins Part 4- Outer Joins Lecture 45 044. Scenario - Joins Part 6 - Self Join Lecture 46 045. Fact And Dimensions Lecture 47 046. IIF Function Lecture 48 047. CASE Lecture 49 048. IIF & CASE multiple conditions Lecture 50 049. Scenario - Custom sorting Lecture 51 50. UNION & UNION ALL Lecture 52 051. INTERSECT Lecture 53 052. EXCEPT Lecture 54 053. Foreign key constraint Lecture 55 054. Subquery - PART 1 Lecture 56 055. Subquery - PART2 -IN & NOT IN Lecture 57 056. Subquery - PART3 - Update Lecture 58 057.Subquery - PART 4-Derived Table Lecture 59 058. Subquery - PART 5 - EXISTS, Correlated subquery Lecture 60 059. Scenario - Subquery - PART 6 - Get contribution yearwise Lecture 61 060. HAVING Clause Lecture 62 061. TOP Clause Lecture 63 062. Scenario - Get TOP & BOTTOM Products Lecture 64 063. Window Functions-PART1 - ROW_NUMBER Lecture 65 064. Window Functions - PART 2 - RANK & DENSE_RANK Lecture 66 065. Window Functions - PART 3-LAG & LEAD Lecture 67 066. Window Functions - PART4 - FIRST_VALUE & LAST_VALUE Lecture 68 067. SQL Classification Lecture 69 068. ALTER TABLE - PART 1 - Columns Lecture 70 069. ALTER TABLE - PART 2- Constraints Lecture 71 070. OFFSET Lecture 72 071. COALESCE Function Lecture 73 072. MERGE Lecture 74 073. SCHEMA Lecture 75 074. GROUP BY WITH ROLLUP Lecture 76 075. GROUP BY WITH CUBE Lecture 77 076. PIVOT Lecture 78 077. UNPIVOT Lecture 79 078. VIEWS Lecture 80 079. Common Table Expression - Part1 - Introduction Lecture 81 080. Common TableExpression - PART 2 - MultiPart Lecture 82 081. Common Table Expression - PART 3 - Recursion Lecture 83 082. Variables Lecture 84 083. IF..ELSE Lecture 85 084. WHILE LOOP Lecture 86 085. Temp Tables Lecture 87 086. Stored Procedures Lecture 88 087. Converting a table to JSON Lecture 89 088. Creating Nested JSON Output Lecture 90 089. Output Clause Lecture 91 090. Slowly Changing Dimensions Section 3: SQL Scenarios Lecture 92 1. Find Average Lecture 93 2. Joins Challenge Lecture 94 3. Identify and delete duolicate rows Lecture 95 4. Custom Merging Lecture 96 005.MissingData-FindMissingDepartments Lecture 97 006.Find2ndLargestSalary Lecture 98 7. 2nd Largest Salary In Each Department Lecture 99 8. RowNumbering Lecture 100 9. Find Alternate Rows Lecture 101 10. Palindrome Lecture 102 11. FindDuplicateEmails Lecture 103 12. UpdateCorrectGender Lecture 104 13. Transform Student Info Lecture 105 14. Defect Classification Lecture 106 015. Daily Running Total Lecture 107 16. MTD Total Lecture 108 17. QTD Total Lecture 109 18. YTD Total Lecture 110 19. Previous Year Sales And YOY Growth Lecture 111 20. 3 month moving sum Section 4: 4. Data warehousing Lecture 112 1.Introduction to DataWarehousing Lecture 113 2. Data Loads Lecture 114 3. Storage Layout Models Lecture 115 4. Robin Round Distribution Lecture 116 5. Hash Distribution Lecture 117 6.ACID Properties Lecture 118 7. Normalization Section 5: 5. Azure Lecture 119 1. Cloud Computing Lecture 120 2. Cloud Providers Lecture 121 3. Azure Introduction Lecture 122 4. Create Azure Trial Account Lecture 123 5. Getting Started With Azure Lecture 124 6. Create Data Lake Lecture 125 7. Create Azure SQL Server And Database Lecture 126 8. CreateDataFactory Lecture 127 9. Upgrade To Pay-as-you-go Section 6: 6.Azure Data Factory Lecture 128 1. Introduction Lecture 129 2. Copy Data Within Datalake Lecture 130 3. Copy Entire Folder Specific Files Lecture 131 4. Copy data from ADLS to SQLDB & vice versa Lecture 132 5. Copy Data Additional Columns Lecture 133 6. Set Variable Activity Lecture 134 7. Copy files in timeframe Lecture 135 8. Get MetaData Activity Lecture 136 9. For Each Activity Lecture 137 10. Copy Each File to New table Lecture 138 11. Truncate & load Lecture 139 12. Copy data with upsert Lecture 140 13. Append Variable Activity Lecture 141 14. Using SQL Queries In Copy Data Activity Lecture 142 15. Column Mapping In Copy Data Activity Lecture 143 16. Delete Activity Lecture 144 17. Copy Data With Stored Procedure Lecture 145 18. Stored Procedure Activity Lecture 146 19. Lookup Activity Lecture 147 20. Filter Activity Lecture 148 21. IF Activity Lecture 149 22. Switch Activity Lecture 150 23. Script Activity Lecture 151 24. Validation Activity Lecture 152 25. Convert CSV to JSON Lecture 153 26. Copy JSON to SQL DB Lecture 154 27. Execute Pipeline Activity Lecture 155 28. Copy Data If File Exists Lecture 156 29. Parameters Vs Variables Lecture 157 30. Delete Blank Files Lecture 158 31. Copy Header Less CSV Lecture 159 32. Retry Logic Lecture 160 33. Copy Behavior Lecture 161 34. Max Rows Per File Lecture 162 35. Split Data Single Criteria Lecture 163 36. Split Data Multiple Criteria Lecture 164 37. Consolidate Data From Multiple Files Lecture 165 38. Consolidate Data From Mutiple Folders Lecture 166 39. Copy Data Custom Mappings SingleTable Lecture 167 40. Copy Data Custom Mappings - MultipleTables Lecture 168 41. Copy Data Pipe Character Lecture 169 42. Copy Data Quote Character Lecture 170 43. Introduction To DataFlows Lecture 171 44. Select Transformation Lecture 172 45. SortTransformation Lecture 173 46. Filter Transformation Lecture 174 47. Derived Column Transformation Lecture 175 48. Conditional Split Transformation Lecture 176 49. Cast Transformation Lecture 177 50. Surrogate Key Transformation Lecture 178 51.Aggregate Transformation Lecture 179 52. Pivot Transformation Lecture 180 53. Unpivot Transformation Lecture 181 54.Rank Transformation Lecture 182 55. Window Transformation Lecture 183 56. Union Transformation Lecture 184 57. Lookup Transformation Lecture 185 58. Join Transformation Lecture 186 59. Exists Transformation Lecture 187 60. Flatten Transformation Lecture 188 61. Parse Transformation Lecture 189 62. Stringify Transformation Lecture 190 65. Integration Runtime Lecture 191 66. Install Self Hosted Integration Runtime Lecture 192 67.Copy Data From Local To ADLS Lecture 193 68. Copy Data From Local to Azure SQL DB Lecture 194 69. Copy Data Local SQL db to Azure SQL db Lecture 195 070. Copy Multiple Tables From Local sql DB to Azure sql DB Lecture 196 071. Using Key Vault Lecture 197 072. Schedule Trigger Section 7: 7.Introduction To Databricks Lecture 198 1. Introduction To Databricks Lecture 199 2. Community Edition Sign Up Lecture 200 3. Databricks Platform Overview Section 8: 8.Python Programming Lecture 201 1. Introduction And Installation Lecture 202 2. print Lecture 203 3. Variables Lecture 204 4. Concatenate Lecture 205 5. Interpolation Lecture 206 6. If..else Lecture 207 7. Input Lecture 208 8. IF..ELIF..ELSE Lecture 209 9. For..Loop Lecture 210 10. While..Loop Lecture 211 11. Break&Continue Lecture 212 12. Lists-Part1-IntroductionAndIndexing Lecture 213 13. Lists-Part2-Len,Existence&Loop Lecture 214 14. Lists-Part 3 - Add&RemoveItems Lecture 215 15. Lists-Part4-Count,Copy,Reverse&Sort Lecture 216 16. Lists-Part5-UpdatingLists Lecture 217 17. Set Lecture 218 18. Tuple Lecture 219 19. Dictionary Lecture 220 20. Comments Lecture 221 21. StringOperations-Part1 Lecture 222 22. StringOperations-Part2 Lecture 223 23.StringOperations-Part3 Lecture 224 24. ListComprehensions Lecture 225 25. dir Lecture 226 26. DateTime-Part1-datetimeModule Lecture 227 27. DateTime-Part2-timedelta×tamp Lecture 228 28. DateTime-Part3-monthdeltaModule Lecture 229 29. DateTime-Part4-relativedeltaModule Lecture 230 30.DateTime-Part5-Formatting Lecture 231 31.ExceptionHandling Lecture 232 32. None Lecture 233 33. Random Lecture 234 34. Functions-Part1-Introduction Lecture 235 35. Functions-Part2-ScopeOfVariable Lecture 236 36. Functions-Part3-Arguments Lecture 237 37.Functions-Part4-DocStrings Lecture 238 38. Lambda Lecture 239 39. Map Lecture 240 40. Reduce Lecture 241 41. Recursion Lecture 242 42. Generators Lecture 243 43. Decorators Section 9: 9. Big Data Fundamentals Lecture 244 1. IntroductionToBigData Lecture 245 2. Evolution Of Big Data Lecture 246 3. Distributed Computing Lecture 247 4. Features Lecture 248 5. Hadoop Ecosystem Lecture 249 6. TypesOfProcessing Section 10: 10.Databricks & PySpark Lecture 250 1. IntroductionToDatabricksAndPyspark Lecture 251 2. Introduction To Apache Spark Lecture 252 3. SparkComponents And API Lecture 253 4. Spark Architecture Lecture 254 5. RDD Lecture 255 6. Create RDD from List Lecture 256 7. Control Partitions In RDD Lecture 257 8. CreateRDDfromTextfile Lecture 258 9. Transformations On RDD Lecture 259 10. Lineage Graph Lecture 260 11. Understanding DAG fundamentals Lecture 261 12. Mapreduce Working Lecture 262 13. ReduceByKey Vs ReduceByKey Locally Lecture 263 14. GroupByKey Lecture 264 15. Filter Transformation On RDD Lecture 265 16. SortBy&SortByKeyTransformationsOnRDD Lecture 266 017. Extract Top Bottom From RDD Lecture 267 18. Save RDD as Textfile Lecture 268 19. Coalesce And Repartition On RDD Lecture 269 20. IntroductionToAccumulators Lecture 270 21. Implementing Accumulators Lecture 271 22. Broadcast Variables Lecture 272 23. Introduction To Dataframes Lecture 273 24. ReadCSVInDataframe Lecture 274 25. DataFrameInsights Lecture 275 26. SelectColumnsFromDataFrame Lecture 276 27. Add Modify Columns In DataFrame Lecture 277 28. Drop Columns In DataFrame Lecture 278 29. RenameColumnsInDataFrame Lecture 279 30. SortColumnsInDataFrame Lecture 280 31. FilterDataInDataFrame Lecture 281 32. RemoveDuplicatesFromDataFrame Lecture 282 33. CombineDataFrames Lecture 283 34. PatternBasedFiltersInDataframe Lecture 284 35. AddColumnOnBasisOfConditionInPyspark Lecture 285 36. CaseConversionInDataFrame Lecture 286 37. AggregationsOnDataFrame Lecture 287 38. AggregationsWithGroupBy Lecture 288 39.Pivot&UnpivotOnDataFrame Lecture 289 40. WindowFunctions Lecture 290 41. FillNullValuesInDataFrame Lecture 291 42. ReadCSVoptions Lecture 292 43. ImposeSchemaOnDataFrame Lecture 293 44. WriteModesInDataFrame Lecture 294 45. DateFunctions Lecture 295 46. ConvertRddtoDFandViceVersa Lecture 296 47. Explode Lecture 297 48. WorkingWithArraytypeColumn Lecture 298 49. dbutils Lecture 299 50. AccessADLSgen2UsingAccessKey Lecture 300 51. SignUpForAzureDatabricks Lecture 301 52. Widgets Lecture 302 53. CallingOtherNotebooks Lecture 303 54. ReadJsonFiles Lecture 304 55. ReadMultipleFilesAndGetFileNames Lecture 305 56. ParquetFileFormat Lecture 306 57. AccessADLSusingSAStoken Lecture 307 58. AccessADLSusingOAUTH Lecture 308 59. Read&WriteParquetFiles Lecture 309 60. DeltaFormat Lecture 310 61. CreateTempViews Lecture 311 62. CreateManagedAndUnManagedTables Lecture 312 63. Partitioning Lecture 313 64. Bucketing Lecture 314 65. ControlNumberOfRecordsWhileWriting Lecture 315 66. MaxPartitionBytes Lecture 316 67. SparkQueryExecutionPlans Lecture 317 68. Joins Lecture 318 69. SparkExecutionPlansForTransformations Lecture 319 70. BroadCastHashJoinAlgorithm Lecture 320 71. SortMergeJoinAlgorithm Lecture 321 72. ShuffleHashJoinAlgorithm Lecture 322 73. SortMergeBucketJoin Lecture 323 74. JoinHints Lecture 324 75. SparkSQL Lecture 325 76. SparkMemoryManagement Lecture 326 77. GarbageCollection Lecture 327 78. CPUTerminologies Lecture 328 79. DatabricksCompute&Clusters Lecture 329 80. ClusterManager Lecture 330 81. ResourceAllocation Lecture 331 82. DynamicAllocation Lecture 332 83. SerializationAndDeserialization Lecture 333 84. CacheAndPersist Lecture 334 85. HashFunctions Section 11: 11.DeltaLake & Lakehouse Lecture 335 1.HistoryOfDataArchitectures Lecture 336 2. IntroductionToDeltaLake Lecture 337 3. ReadAndWriteDeltaFormat Lecture 338 4. UnderstandingDeltaLog Lecture 339 5. VersionHistoryAndTimeTravel Lecture 340 6. CheckPointing Lecture 341 7. CreateDeltaTable Lecture 342 8. GeneratedColumns Lecture 343 9. CreatePartitionedTable Lecture 344 10. SchemaEvolution Lecture 345 11. CopyInto Lecture 346 12. Merge Lecture 347 13. ColumnStatistics Lecture 348 14.Optimize-Vaccum-Zorder Lecture 349 15. LiquidClustering Lecture 350 16. ChangeDataFeed Lecture 351 17. ReorgTable Lecture 352 18. DeletionVectors Lecture 353 19.SCD-Type 1 Lecture 354 20.SCD-Type 2 Section 12: 12.Databricks Lecture 355 1.HiveMetaStore Lecture 356 2. IntroductionToUnityCatalog Lecture 357 3. SettingUpUnityCatalog Lecture 358 4.CreateCatalog, Schema & Table Lecture 359 5. Autoloader Section 13: 13.Spark Structured Streaming Lecture 360 1.SparkStructuredSteaming-Introduction Lecture 361 2. ReadStream Lecture 362 3. WriteStream Lecture 363 4. OutputModes Lecture 364 5.Sources&Sinks Lecture 365 6. Triggers Lecture 366 7. Joins Lecture 367 8. Stateful Vs Stateless Lecture 368 9. WindowOperations Section 14: 14. Azure synapse analytics Lecture 369 1.IntroductionToAzureSynapseAnalytics Lecture 370 2.SQL Pools Lecture 371 3. DedicatedSQLPool Lecture 372 4. ServerlessSQLPool Lecture 373 5. DistributionTypes Lecture 374 6.ProvisionAzureSynapseAnalytics Lecture 375 7. WorkingWithServerlessSQLPool Section 15: 15. End-to-end project Lecture 376 1. Introduction Lecture 377 2. UnderstandingRequirements Lecture 378 3. PurchaseDataModel Lecture 379 4. SalesModel Lecture 380 5. HRModel Lecture 381 6. ResourceSetUp Lecture 382 7. GettingStartedWithAzureDevops Lecture 383 8. UnderstandingDataSource Lecture 384 9. GettingDatabricksReady Lecture 385 10. DevelopingPurchaseNotebooks Lecture 386 11. DevelopingPurchaseModel-Part2 Lecture 387 12. TaskPlanning Lecture 388 13.DevelopingPurchaseBronzeNotebooks Lecture 389 14.FirstDemo Lecture 390 15.DevelopingSilverNotebooks-Part1 Lecture 391 16.DevelopingSilverAndOtherNotebooks Lecture 392 17.DevelopingOtherAndSilverNotebooks-Part2 Lecture 393 18. CreatingRawAndBronzeSalesNotebooks Lecture 394 19.CreatingSalesSilverNotebooks-Part1 Lecture 395 020.CreatingSalesSilverNotebookPart2 Lecture 396 021.CreatingHrModelNotebooks Lecture 397 22. DevelopingDatabricksWorkflows Anyone can enroll this course from beginner, intermediate to architect level!,Anyone looking to transition into azure data engineering or existing data engineers looking to not just enhance their skillset but also learn in 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