Data Analytics Complete Course ( English)

Learn multiple tools in data analytics stack through this course, all in one bundle!

What you'll learn

Understand and learn different tool in data analytics.

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

There are no prerequistes for this course, learn everything from scratch.

Description

Note: This is an English course, same course is available in Hindi.This course covers multiple tools and technologies needed to become a data analyst.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!There are no prerequisites.All you need to do is follow the sequence in this course designed for you.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.POWER BI : Learn POWER BI in depth including concepts, reporting, DAX and Power bi service.Databricks: Learn databricks overview, the leading data platform.Python programming: Learn programming in python with simple way.

Overview

Section 1: 1. SQL

Lecture 1 1. Introduction to SQL

Lecture 2 2. SQL Server Installation

Lecture 3 3. Create And Drop Database

Lecture 4 4. System Databases

Lecture 5 5. Create and Drop Tables

Lecture 6 6. Insert Data In Table

Lecture 7 7. Select

Lecture 8 8. InstallAdventureWorksSampleDB

Lecture 9 9.GetUniqueValues

Lecture 10 10. SortData

Lecture 11 11. Comments

Lecture 12 12. SortData

Lecture 13 13. FilterWithWildCharacters

Lecture 14 14. Aggregate Function

Lecture 15 15. GroupingRows

Lecture 16 16.Select..Into

Lecture 17 17. CreateTableWithPrimaryKey

Lecture 18 18. CreateTableWithNOTNULLConstraint

Lecture 19 19. Create Table With Unique Constraint

Lecture 20 20. Create Table With Check Constraint

Lecture 21 21. Create Table With Default Constraint

Lecture 22 22. Create Table With AutoIncrement

Lecture 23 23. UpdateRowsInTable

Lecture 24 24. Delete Rows From Table

Lecture 25 25.StringFunctions-Part1

Lecture 26 26. String Functions - Part 2

Lecture 27 27. Scenario-CombineNames

Lecture 28 28. Scenario - Extract First And Last Names

Lecture 29 29.DateTimeFunctions-Part1

Lecture 30 30. DateTimeFunctions-Part2

Lecture 31 31.DateTimeFunctions-Part3

Lecture 32 32-DataTypes-Part1-Integers

Lecture 33 33-DataTypes-Part2-ApproximateNumeric

Lecture 34 34-DataTypes-Part3-DateTime

Lecture 35 35-DataTypes-Part4-Strings

Lecture 36 36-DataTypes-Part5-Uniqueidentifier

Lecture 37 37. DataTypes-Part6-bit

Lecture 38 38.DataType Conversion

Lecture 39 39.Joins-Part1 – Introduction to joins

Lecture 40 40.Joins-Part2 – Using Joins

Lecture 41 41.Joins-Part3 – Join 3 tables

Lecture 42 42. Joins-Part4 – Using Expressions

Lecture 43 043.Joins-Part5 – Outer Joins

Lecture 44 44.Scenario-Joins-Part6 – Self Join

Lecture 45 45.FactAndDimensions

Lecture 46 46.IIF Function

Lecture 47 47. CASE

Lecture 48 48.IIF & CASE multiple conditions

Lecture 49 49. CustomSorting

Lecture 50 50.UNION & UNION ALL

Lecture 51 51. INTERSECT

Lecture 52 52. EXCEPT

Lecture 53 53. Foreign Key constraint

Lecture 54 54.Subquery-PART1

Lecture 55 55. Subquery-PART2-Using IN & NOT IN

Lecture 56 56.Subquery-PART3-Update

Lecture 57 57.-PART4-Subquery-PART4-Derived Table

Lecture 58 58.Subquery-PART5-EXISTS, NOT EXISTS, Correlated Subquery

Lecture 59 59-Scenario-Get Percent Contribution of each year

Lecture 60 60.HAVING clause

Lecture 61 61. TOP Clause

Lecture 62 62. Scenario-Get TOP BOTTOM products

Lecture 63 63.Window Functions – PART1 – ROWNUMBER()

Lecture 64 64.Window Functions – PART2 – RANK & DENSE_RANK

Lecture 65 65.Window Functions – PART3 – LAG & LEAD

Lecture 66 66.Window Functions – PART4 – FIRST_VALUE & LAST_VALUE

Lecture 67 67.SQL Classification

Lecture 68 68-ALTER TABLE -PART 1 – Columns

Lecture 69 69-ALTER TABLE -PART 2 – Constraints

Lecture 70 70.OFFSET

Lecture 71 71. COALESCE

Lecture 72 72.MERGE

Lecture 73 73. SCHEMA

Lecture 74 74. GROUP BY WITH ROLLUP

Lecture 75 75. GROUP BY WITH CUBE

Lecture 76 76. PIVOT

Lecture 77 77. UNPIVOT

Lecture 78 78. VIEWS

Lecture 79 79.CommonTableExpression-Part1-Introduction

Lecture 80 80-CommonTableExpression-Part2-MultiPart

Lecture 81 81.CommonTableExpression-PART3-Recursion

Lecture 82 82. Variables

Lecture 83 83.IF…ELSE

Lecture 84 84.WHILE LOOP

Lecture 85 85. TempTables

Lecture 86 86. StoredProcedures

Lecture 87 87.Converting a table to JSON

Lecture 88 88. CreatingNestedJSONOutput

Lecture 89 89.OUTPUT Clause

Lecture 90 90. SlowlyChangingDimensions

Section 2: 2. SQL Scenarios

Lecture 91 1. Find Average

Lecture 92 2.Joins Challenge

Lecture 93 3. IdentifyAndDeleteDuplicateRows

Lecture 94 4. CustomMerging

Lecture 95 5. MissingData-FindMissingDepartments

Lecture 96 6. SecondLargestSalary

Lecture 97 7. Find2ndLargestSalaryInEachDepartment

Lecture 98 8. RowNumbering

Lecture 99 9. FindAlternateRows

Lecture 100 10. Palindrome

Lecture 101 11. FindDuplicateEmails

Lecture 102 12. UpdateCorrectGender

Lecture 103 13. TransformStudentsInfo

Lecture 104 14. DefectClassification

Lecture 105 15. DailyRunningTotal

Lecture 106 16. MTD Total

Lecture 107 17. QTDTotal

Lecture 108 18. YTDTotal

Lecture 109 19. PreviousYearTotalAndYOYgrowth

Lecture 110 20. 3 Month Moving Total

Section 3: 3.DataWarehousing

Lecture 111 1.Introduction to DataWarehousing

Lecture 112 2.DataLoads

Lecture 113 3. StorageLayoutModels

Lecture 114 4. RobinRoundDistribution

Lecture 115 5. Hash Distribution

Lecture 116 6. ACID Properties

Lecture 117 7. Normalization

Section 4: 4.POWER BI

Lecture 118 1. Introduction

Lecture 119 2. InstallingPOWERBIDesktop

Lecture 120 3. BuildingBlocks

Lecture 121 4. ImportDataFromExcel

Lecture 122 5. AddDateColumnsUsingPowerQuery

Lecture 123 6. AddDateColumnsUsingCalculatedColumns

Lecture 124 7. IntroductionToMeasures

Lecture 125 8. IntroductionToMeasures

Lecture 126 9. IntroductionToDAX

Lecture 127 10.CALCULATE Function

Lecture 128 11. UnderstandingRelationship

Lecture 129 12.IF Function

Lecture 130 13.SWITCH function

Lecture 131 14. RELATED & LOOKUPVALUE Functions

Lecture 132 15.PowerQuery-AppendAndCombineFiles

Lecture 133 16.PowerQuery-SourceProperties

Lecture 134 17.PowerQuery-EnterData

Lecture 135 18.PowerQuery-ManageRowsAndColumns

Lecture 136 19.PowerQuery-SplitColumn

Lecture 137 20-PowerQuery-DuplicateReferenceGroupBy

Lecture 138 21.PowerQuery-DataTypes

Lecture 139 22.PowerQuery-Headers&Replace

Lecture 140 23.PowerQuery-MergeQuery

Lecture 141 24.PowerQuery-Transpose&ReverseRows

Lecture 142 25.PowerQuery-Fill

Lecture 143 26.PowerQuery-Pivot&Unpivot

Lecture 144 27.PowerQuery-Format

Lecture 145 28.PowerQuery-Extract

Lecture 146 29.PowerQuery-Round&Info

Lecture 147 30.PowerQuery-AddColumnFromExamples

Lecture 148 31.PowerQuery-AddIndex&ConditionalColumn

Lecture 149 32.StringFunctions-UPPER,LOWER,LEFT,RIGHT,MID

Lecture 150 33.BLANK Function

Lecture 151 34.RELATEDTABLE_Function

Lecture 152 35.COUNTX_Function

Lecture 153 36.SUMX_Function

Lecture 154 37.ALL_Function

Lecture 155 38.ALLSELECTED_Function

Lecture 156 39.ALLEXCEPT_Function

Lecture 157 40.GENERATESERIES_Function

Lecture 158 41. UNICHARandUNICODE_Functions

Lecture 159 42.DISTINCTandVALUES_Functions

Lecture 160 43.RowContextAndFilterContext

Lecture 161 44.FILTER_Function

Lecture 162 45.CALENDAR_Function

Lecture 163 46.CALENDARAUTO_Function

Lecture 164 47.DATEADD_Function

Lecture 165 48.CalculatePreviousYearSales

Lecture 166 49.SAMEPERIODLASTYEAR_Function

Lecture 167 50.PARALLELPERIOD_Function

Lecture 168 51.DATESYTD,DATESQTD,DATESMTD_Functions

Lecture 169 52.TOTALYTD,TOTALQTD,TOTALMTD_Functions

Lecture 170 53.FIRSTDATEandLASTDATE_Functions

Lecture 171 54.DATESINPERIOD_Function

Lecture 172 55.DATESBETWEEN_Function

Lecture 173 56.SyncSlicers

Lecture 174 57.DrillThrough

Lecture 175 58.Hierarchy,DrillDown,DrillUp

Lecture 176 59.ConnectionModes

Lecture 177 60.IntroductionToPowerBIService

Lecture 178 61.PowerBiService-CreatingWorkspace

Lecture 179 62.PowerbiService-ManagingWorkspaceAccessAndRoles

Lecture 180 63. RowLevelSecurity

Lecture 181 64. DynamicRowLevelSecurity

Lecture 182 65.DynamicRowLevelSecurity-ManagerAccess

Lecture 183 66. CreateDashboardInPowerBiService

Lecture 184 67. 1,2,3 YearsPerformance

Lecture 185 68. Bookmarks

Lecture 186 69. ButtonNavigation

Lecture 187 70. SwapVisuals

Lecture 188 71.12MonthsTrailingPerformance

Lecture 189 72. 12MonthsTrailingPerformanceBasisSelection

Lecture 190 73. DynamicMonthsTrailingPerformance

Lecture 191 74.SUMMARIZE Function

Lecture 192 76.TOPN Function

Lecture 193 77.KEEPFILTERS Function

Lecture 194 78.REMOVEFILTERS Function

Lecture 195 79.DynamicTopBottom

Lecture 196 80.USERELATIONSHIP Function

Lecture 197 81.TREATAS Function

Lecture 198 82.FNB,LNB,FNBV,LNBV Functions

Section 5: 5. Datrabricks Introduction

Lecture 199 1. IntroductionToDatabricks

Lecture 200 2. CommunityEditionSignUp

Lecture 201 3. DatabricksPlatformOverview

Section 6: 6. Python Programming

Lecture 202 1. IntroductionAndInstallation

Lecture 203 2. print

Lecture 204 3. Variables

Lecture 205 4. Concatenate

Lecture 206 5. Interpolation

Lecture 207 6.If..else

Lecture 208 7.Input

Lecture 209 8.IF..ELIF..ELSE

Lecture 210 9.For..Loop

Lecture 211 10.While..Loop

Lecture 212 11.Break&Continue

Lecture 213 12.Lists-Part1-Introduction&Indexing

Lecture 214 13.Lists-Part2-Len,Existences&Loop

Lecture 215 14.Lists-Part3-Add&RemoveItems

Lecture 216 15.Lists-Part4-Count,Copy,Reverse&Sort

Lecture 217 16.Lists-Part5-UpdatingLists

Lecture 218 17.Set

Lecture 219 18. Tuple

Lecture 220 19.Dictionary

Lecture 221 20. Comments

Lecture 222 21.StringOperations-Part1

Lecture 223 22.StringOperations-Part2

Lecture 224 23.StringOperations-Part3

Lecture 225 24.ListComprehensions

Lecture 226 25. dir

Lecture 227 26.DateTime-Part1-datetimeModule

Lecture 228 27.DateTime-Part2-timedeltaANDtimestamp

Lecture 229 28.DateTime-Part3-monthdeltaModule

Lecture 230 29.DateTime-Part4-relativedeltaModule

Lecture 231 30.DateTime-Part5-Formatting

Lecture 232 31.ExceptionHandling

Lecture 233 32. None

Lecture 234 33. Random

Lecture 235 34.Functions-Part1-Introduction

Lecture 236 35.Functions-Part2-ScopeOfVariable

Lecture 237 36.Functions-Part3-Arguments

Lecture 238 37.Functions-Part4-DocStrings

Lecture 239 38.Lambda

Lecture 240 39. Map

Lecture 241 40.Reduce

Lecture 242 41. Recursion

This course for one who is looking to transition into data analytics as well as for existing data analyst professionals.