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Data Preparation
Workflows

  • Handling Missing and Categorical Data

  • Extracting Date Time Fields

  • Reading and Processing JSON from a URL

  • Removing Duplicate Customer Records

  • Performing Data Cleaning on Titanic Dataset

  • Performing Data Quality on Email Fields

  • Reading CSV File via REST and Parsing

  • Converting String to Timestamp

  • Removing Rows with Null Values

  • Removing Special Characters Using Regex

  • Filtering Columns

  • Concatenating Multiple Columns

  • Cleaning the Data

  • Searching and Replacing Text

  • Casting Datatype

  • Cleaning and Transforming the Data

  • Extracting Text Using OCR

  • Performing Data Profiling on Housing Data

  • Removing Duplicate Rows

  • Selecting, Dropping, and Renaming Columns

  • Manipulating String Columns​

  • Imputing Null Values

  • Identifying Unique Values in Columns

Application

  • Customer Segmentation Analytical App

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Data Engineering
Data Quality
Workflows

  • Performing Data Profiling on Employee Data

  • Performing Schema Validation

  • Performing Address Validation

  • Performing Multi-level Data Validation

  • Performing Complex ETL on Customer Data

  • Performing Advance Data Preparation

  • Performing Data Validation on Housing Data

  • Performing Complex ETL on Customer Data

  • Performing Simple ETL on Customer Data

  • Transforming Housing Data

  • Joining Multiple Datasets

  • Analyzing NYC Taxi Average Speed

  • Reading and Writing to HIVE Table

  • Removing Duplicate Rows

  • Performing Data Wrangling on Transactional Data

  • Manipulating Housing Data Using SQL

  • Preparing Data Using SCALA

  • Performing Data Cleaning on Titanic Data

  • Flattening And Exploding JSON Data

Workflows

  • Performing Data Profiling on Employee Dataset

  • Validating Column Values to Be not Null

  • Validating Column Values to Be Null

  • Validating Column With Unique Values

  • Validating Table Row Count to be in Given Range

  • Performing Data Quality on Housing Data

  • Validating Column Values to be in Given Range

  • Performing Data Cleaning and Data Quality on Employee Data

  • Validating Multiple Columns

  • Reading Flat File

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